SURI Apply - Fulton Schools of Engineering

Application Deadline

February 04, 2025 at 2am

Program Information

The Ira A. Fulton Schools of Engineering at Arizona State University offers summer opportunities for qualified students to gain engineering research experience at a top research university. Participants acquire an in-depth understanding of what it would be like to pursue a PhD degree through an 8-week summer research program. Research projects across a wide range of engineering fields are available. Students between the junior and senior years of their undergraduate degree and those pursuing Master's degrees who are considering pursuing a PhD will be given highest consideration. Participants work under the mentorship of research faculty and have opportunities to network with industry partners, other faculty and their peers through a variety of events and activities.

SURI Program Information...

Contact

For questions about the SURI program, please email: suri.fulton@asu.edu

Application Information

Please submit only one application. If you submit more than one application, only your first application will be reviewed.

You may edit your response until the application deadline shown at left.
Important: after you submit your application you must click the link in your confirmation email to view your application and edit your responses.

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Please provide the name of your current or most recently attended university/college.

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Which graduate engineering degree are you interested in pursuing? (The purpose of SURI is to help students understand what it is like and help prepare for advance research leading to the PhD)

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As of Fall 2024, what is your class standing?

What is your undergraduate major?

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What is your major GPA?

For the next four (4) questions please consult the list of SURI 2025 Opportunities which can be found here:

SURI Program Information > (scroll down)

Please select the name of the faculty whose project you are interested in for your FIRST CHOICE

Please indicate the "Program/Expertise Area" selected from the list of available projects on the website for which you are applying for your FIRST CHOICE:

List of Projects for the selected Program/Expertise Area:

Project description: Understand the physical scale-dependent mechanical & dynamic properties of meteoritic materials and gain insight into their deformation mechanisms and fracture & impact dynamics.. Students will: Assist in conducting ballistic impact and quasi-static compressive tests on meteorite samples coupled with digital image correlation techniques, and performing microscopy on the fragments from impact. Prerequisite skills/knowledge: Students from mechanical or aerospace engineering; some experience in hands-on experiments is a plus. Junior status would be preferable, but motivated sophomores who meet the requirements will also be considered.
Project description: The objective of this project is to explore the potential of large language models in generating 3D designs using text-based prompts. Students will: Explore the challenges in generating complex designs, best practices when providing text prompts, and incorporating different type of constraints. Furthremore, we will explore the potential of LLM in generating designs from a family, e.g., making changes to an existing design. Prerequisite skills/knowledge: The work will require knowledge of basic python (or any other) programming language, basic knowledge of large language models and how to use them.
Project description: This project is inspired by EPIXC with an aim to develop highly conductive electric conductors using carbon nanotubes (CNT) and copper, that contribute to the expansion of electrified processes with reduced carbon emission. In this project, a student aims to understand how the composite structure of carbon nanotube (CNT)-metal fibers affects their electrical and thermal conductivities. CNT-metal fiber is expected to offer extraordinary ratio of conductivity to mass, which, however, requires theoretical understanding of its structural (or morphology) effects. Students will: Learn a computational simulation model for electrical and thermal conductivity of CNT-metal fiber. After running simulations for several possible structures of this fiber, the student should discuss the effects of structure on electrical and thermal transport in the fiber, and propose an optimal structure. Prerequisite skills/knowledge: Knowledge of electrical and thermal conductivities in materials, numerical methods (finite element model).
Project description: This project utilizes a longitudinal epidemiological health dataset to advance understanding of cardiovascular health in a diverse U.S. population. By integrating demographic, behavioral, and clinical data, the project aims to provide actionable insights to improve cardiovascular health outcomes and inform public health strategies. Students will: Collaborate to (a) build a comprehensive data inventory, (b) develop predictive models to monitor health trajectories, and (c) explore graphical models to uncover relationships among multi-dimensional health risk factors. Prerequisite skills/knowledge: Programming languages such as R, Python, or MATLAB; Basic Probability, Statistics, and Data Mining.
Project description: The objective of the research is to develop a versatile technique that is capable of printing metallic structures at micrometer- scale resolution feasible for photonics and electrochemical sensing applications. Here we will explore a new solutionbased photochemically induced polymer-assisted deposition (PIPAD) process to produce metallic composite microstructures. Students will: Work with a postdoc on addititive manufacturing by engineering optical system and chemical precursors. Prerequisite skills/knowledge: Photonics; chemistry, electrochemistry, and fabrication skills are desired but not required.
Project description: The objective of the research is to design nanoparticle-based, portable biomolecular sensors and their electronic readout systems that will be suitable for accessible healthcare use. The goal is to make the system suitable for detection of both infectious diseases and chronical diseases for those inexperienced users, which will have significant impact on broadening healthcare in resource-limited areas. Students will: Work with graduate students on assay design process and validation. Prerequisite skills/knowledge: Biochemistry, circuits, and programming skills are desired but not required.
Project description: This research project focuses on designing and fabricating bioinspired structures to mitigate the Leidenfrost effect, a phenomenon where a vapor layer forms between a hot surface and a liquid, inhibiting efficient heat transfer. Drawing inspiration from natural textures and patterns, the project aims to create advanced surface designs that disrupt vapor layer formation and enhance sustained thermal cooling. These structures will be fabricated using state-of-the-art additive manufacturing techniques, enabling precise control of surface geometry and material properties. By overcoming the limitations of conventional cooling methods, this work seeks to improve energy efficiency and thermal management in various applications, including industrial heat exchangers, electronics cooling, and sustainable energy systems. The outcomes of this study have the potential to significantly advance our understanding of thermofluidic interactions while contributing to environmentally friendly cooling solutions. Students will: Be involved in designing micro- and nanoscale surface structures using CAD software, fabricating these structures through advanced 3D printing techniques, and conducting experiments to evaluate their effectiveness in mitigating the Leidenfrost effect. Additional responsibilities may include analyzing heat transfer performance, optimizing surface geometries based on experimental data, and contributing to the development of sustainable cooling solutions. Prerequisite skills/knowledge: CAD, simulation
Project description: This project aims to (i) investigate the potential of utilizing native fungal strains for heavy metal bioremediation and (ii) explore the characteristics of fungi-metal-organic framework (F-MOF) composite materials for tailored applications. Students will: Design and conduct bench-scale laboratory experiments, including culturing fungi in growth media supplemented with metals. They will perform a comprehensive range of characterization tests and analyses, including data collection, compilation, analysis, and reduction, as well as writing up their findings and report. Prerequisite skills/knowledge: Previous experience in a BSL-2 level environmental microbiology lab and a strong interest in fungi mycelium culture will be advantageous. A working knowledge of bioremediation and microbe-metal interactions would also be beneficial.
Project description: This project focuses on the evaluation and assessment of various binary decompilation tools, such as Hex-Rays Decompiler (IDA Pro), Ghidra, Binary Ninja, Reko Decompiler, and angr decompiler. Researchers on this project will investigate potential metrics that measure the quality of binary decompilation output. The project will result in the creation of a data set as well as an online platform that evaluates decompilers on multiple metrics. Students will: Work on one of the following tasks: (a) proposing new metrics and studying existing metrics for evaluaitng the quality of decompilation output; (b) building an online service for evaluating output of existing decompilers. Prerequisite skills/knowledge: Some skills in low-level computing (e.g., assembly, memory errors, etc) are required. Also Python 3 programming experience is a must. Strong interest in compiler theory (or decompiler theory) and/or programming languages.
Project description: This project focuses on building a correct and verifiable binary decompilation technique for a small set of binary programs. By fixing issues and adding new analysis passes into angr decompiler, we will create sound and recompilable decompilation for executables and libraries in old PC games or Windows software (especially healthcare software). Students will: Work on one of the following tasks: (a) evaluating angr decompiler on executables of old PC games and other Windows software (especially healthcare software); (b) curating a data set of old PC games and other Windows software for evaluating angr decompiler. Prerequisite skills/knowledge: Some skills in low-level computing (e.g., assembly, memory errors, etc) are required. Also Python 3 programming experience is a must. Strong interest in compiler theory (or decompiler theory) and/or programming languages.
Project description: The projects aim to develop efficient Machine learning models to fine tune and prompt large language models to understand the root causes of different accident report to understand the major root causes of aviation accidents Students will: Work on ML algorithms implementation and development. Prerequisite skills/knowledge: Python, Pytorch
Project description: Detecting and Remediating Online Study Fraud: Since the bot crisis of 2018, crowdâ€‘sourced studies have been critically hindered by fraudulent responses. Amazon Mechanical Turk surveys, once representative of the USâ€‘census, are now not generalizable; $50,000 surveys have fraud rates as high as 96%; and filtering fraudulent data can take multiple months and still only result in a a single authentic response among 1000. To protect studies, researchers in various fields have independently created adâ€‘hoc mechanisms to distinguish real responses from fraud; however, these mechanisms are often not principled, not adversarially robust, nor address emerging concerns. This project will investigate how to make principled defenses against study fraud. This project will investigate how online study fraud occurs, whether it can be effectively detected, and whether it can be prevented. Students will: Investigate the blackmarket of the fraud ecosystem, systematically evaluating proposed detection methods, or creating a novel detection method, depending on the interests and skills of the applicant. Prerequisite skills/knowledge: Javascript, computer networking, computer security & privacy, basic programming.
Project description: Investigating the Security and Privacy effect of Human-Artificial Intelligence Interaction: Currently, there is a lack of principled methods to construct safe and secure human-ML interaction paradigms. Thus, to prevent harm in ML-based systems, it is paramount that we understand vulnerabilities and apply safeguards now. This set of projects will investigate how human interaction impacts ML security in two ways: How human factors can be 1) exploited to reduce security or 2) harnessed to improve security. Projects topics may include detecting and mitigating the effect of deepfakes (topic 1), or developing ways to prevent vulnerabilities and prevent exploitation in developed machine learning systems (topic 2). The specific topic can be dependent upon the interests and proposals of the applicant. Students will: Develop UI to convey provenance information for media and indicators to reduce the effect of deepfakes, understand how to develop machine learning coursework to include modules on adversarial machine learning topics, or discovering ways that adversarial machine learning exploits occur in practice, and developing methods to mitigate them. Prerequisite skills/knowledge: Machine learning, human factors methodologies (e.g., experimental design, interviews, qualitative coding), computer security & privacy.
Project description: This project aims to build high-performance and reconfigurable computer architectures for deep learning applications. Students will: Work on architectural simulation, hardware design, ML development. Prerequisite skills/knowledge: C/C++, Verilog, Pytorch.
Project description: This project aims to build high-performance GPU programming for scientific computing. Students will: Work on Cuda development. Prerequisite skills/knowledge: CUDA programming, C/C++.
Project description: Learn how to fabricate microfluidics and ancillary components for diagnostic cartridges. Investigate mechanisms for actuating the release of reagents and record data from experiments. Complete a technical report including data analysis for presentation of results. Students will: Investigate the use of methods to remove the need for cold storage of reagents used in point of care diagnostics. The microfluidic environment complicates the mixing and flow of the reagents and samples added to the cartridges. Prerequisite skills/knowledge: Excellent fine motor skills, data analysis, basic wet lab skills, laboratory safety
Project description: Learn how to fabricate test devices using precision fabrication and polymers, complete testing of delicate components, electrical measurements and data analysis, prepare a technical report. Students will: The student will investigate the use and degradation of devices place in brain using a simulated brain environment. The student will use wireless methods of interogating the devices operation and gain information about the patient's health and device degredation. Prerequisite skills/knowledge: Basic electronics including frequency dependent analysis, excellent fine motor skills, data analysis, basic wet lab skills, laboratory safety
Project description: The Weaver lab designs macroencapsulation devices with complex geometries and engineers high-throughput biomanufacturing techniques to encapsulate cells in these devices. This project will entail optimization of hydrogel injection mold design and encapsulation device fabrication, and downstream assessment of cell viability and engraftment. Students will: Assist with a tissue engineering project incorporating cells into hydrogels and assessing cell viability and differentiation. Prerequisite skills/knowledge: Not required, but previous experience in CAD design, 3D printing, cell culture, hydrogel fabrication, or histology techniques are a plus.
Project description: The aim of the project is to simulate a continuum robotic arm with physics-informed data-driven methods (Koopman operator). The student will study how to improve the accuracy of the model and reduce the requirement of the training data. The arm will be controlled to conduct a series of tasks such as maneuvering through tree branches to pick fruits. Students will: Study physics-based and data-driven simulation methods, derive models, and implement the simulation with python/C++. Prerequisite skills/knowledge: Knowledge of solid mechanics, dynamic systems, and numerical methods (ODE/PDE solvers). Proficient in one programming language: Python/C++.
Project description: The aim of this project is to develop an underwater robotic arm. The robotic arm will be remotely controlled to repair nets, monitor fish, or take samples. The desired applicants have a strong interest in research and have hands-on experience in mechanical engineering, electrical engineering, and computer science. Students will: Modify the current mechanical design, especially waterproof the robotics arm hardware, derive dynamics models, and implement the simulation and control algorithm with python/C++. Prerequisite skills/knowledge: Basic mechanical design, mechatronics design, and Arduino programing. Know about robotic operating systems. Students in computer science and electrical engineering are encouraged to apply.
Project description: Faculty leads also include Vikram Kodibagkar. The project involves analysis of simultaneous MRI oximetry / ECoG data. Students will: Analyze previously acquired multi modality data (MRI, ECoG) from rodents with the overall goal of artifact reduction in ECoG data and assessing correlaltions with MR oximetry data. Additionally, the student will gain exposure to data acquisition and analysis using a benchtop MRI scanner as well as hands on techniques for design of multimodal brain implants. Prerequisite skills/knowledge: Previous experience with Python, MATLAB for data analysis is a plus.
Project description: This project aims to explore the potential of combining knowledge-based and learning-based methods to enhance the generation of traffic scenarios for testing and evaluating AV safety. Students will: Leverage both hardware and software tools in the BELIV lab to conduct scenario-based testing of automated vehicles. Prerequisite skills/knowledge: ROS, Linux, Python, Generative AI, Reinforcement learning.
Project description: This project will focus on developing Universal BMS (U-BMS) with Digital Twin technology and AI-powered solutions for Battery Energy Storage Systems (BESS). Students will: Develop digital twin for battery systems and train AI models to enhance BMS accuracy and functionality. Prerequisite skills/knowledge: Matlab/Simulink, Battery Managment System, Digital Twin, Machine Learning.
Project description: This project aims to evaluate the mechanism of action of a biomimetic nanodrug developed in our laboratory using high-throughput transcriptomics and bioinformatic analysis. Students will: Gain hands-on experience with fundamental cellular and molecular biology assays and develop skills in bioinformatics for analyzing RNA-seq data. Prerequisite skills/knowledge: Cell biology, molecular biology, biomaterials.
Project description: This project will focus on finetuning of generative models. Diffusion based generative models are the key components of industrial genAI. However, these models are slow to sample and provide no assurances of fairness in sampling from the input support. Our lab focuses on enhancing the speed of sampling diffusion models and also evaluating their fairness guarantees. Prerequisite skills/knowledge: Student must have a strong background in statistics, probability, and Python programming.
Project description: Compared to traditional rigid structures and robots, soft robots, such as a bio-inspired snake robots, are more adaptable in complex environment. In this project, we will use physics-informed machine learning techniques to design and control the bioinspired soft robots. Students will: Develop graph-based machine-learning methods to model soft robotics and mechanical metamaterials. The student will fabricate the robot using laser cutting and conduct experiments to verify the design. Prerequisite skills/knowledge: Machine learning, Structural mechanics, Python-based programming.
Project description: Fish and birds oftentimes form a collective group to save energy during locomotion. Such phenomena are known as "schooling". In this project, we will understand the benefit of the schooling phenomena involving multiple fish and birds in fluid flows through numerical simulation and dynamical modeling. We will develop model-based control to teach the optimal schooling strategy. Students will: Develop multiple robot to mimick fish schooling in computational fluid dynamics simulation environment. The student will also develop model-based controls to control the robot to accomplish certain tasks, such as search and rescue. Prerequisite skills/knowledge: Machine learning, Fluid mechanics, Python-based programming, and willing to learn new programming language.
Project description: This project aims to develop machine-learning enhancements to incorporate semiconductor packaging analysis to electronic design automation. ML models and design metrics of the multi-physics performance in packaging design will be used to advance co-design algorithm in early stage physical design of electronics. Students will: Work on fine-tuning ML model, CAD simulations to generate datasets, embed ML model into one of the EDA algorithms. Prerequisite skills/knowledge: Knowledgeable in machine learning, project experience on electronic design automation, hands-on experience in programming (C/C++ and/or Python).
Project description: This research will investigate the photomechanical behaviors of flexible photovoltaic materials and devices using multiscale material modeling and experimentation. It will analyze the impact of environmental and mechanical stresses on material defect evolution and overall performance of thin-film solar cells, particularly under cyclic loading and light exposure. The study aims to optimize material properties and structural designs to enhance durability and efficiency, aligning with sustainability goals and contributing to advancements in semiconductor manufacturing. Students will: Gain knowledge of photovoltaic materials and devices, receive training in finite element modeling and atomic-scale material modeling, and develop expertise in micromechanical testing techniques. Prerequisite skills/knowledge: Junior or senior in materials science or mechanical engineering.
Project description: We are developing improved cell culture models of human brain to improve accuracy and work toward effective study and treatment of neurological disease. This project will use microscopy and RNA analysis strategies to assess how changes in cell culture conditions/environment, focused on oxygen and glucose accessibility, impact homeostasis and disease states. Students will: Learn how to process samples for RNA and protein analyses and compare differences across conditions. The analysis of this data will then be implemented to improve the accuracy of our cell culture conditions. Prerequisite skills/knowledge: Working understanding of basic molecular biology and some wet lab experience, would be helpful.
Project description: The research project is to develop a solar drievn hydrogen production system. It involves both hardware and software development. Depending on the academic discipline, the student will be assigned to a task in the project. Some of the sample topics include water treatment for hydrogen production, current and voltage sensors for the system, control algorithm development, safe hydrogen handling, voltage and power matching between electrolyzer and solar array, system operation and maintennance, etc. Students with various engineering backgrounds are encouraged to apply including electrical, chemical, environmental, mechanical, industrial, materials, etc. Students will: Be assigned specifiic tasks that will be determined after an interview with professor and PhD students. Prerequisite skills/knowledge: STEM major.
Project description: Magnetic components (inductors and transformers) bottleneck the size, weight, and loss of many power electronic converters. A critical avenue towards mitigating this bottleneck is to better understand the parasitic characteristics of these materials, especially their inherent self-resonance. In this project, the student will be part of a team developing models of self-resonance and producing high performance magnetic components for power converters. Students will: Assist or take the lead on: designing an experimental testbed to evaluate power magnetic components, developing new printed circuit boards for this effort, soldering these prototypes, testing new magnetic components using the developed hardware, and comparing predicted performance to experimental performance. Prerequisite skills/knowledge: The student must have a strong background in circuit analysis. Ideally, the student will have already completed a course in power electronics and have experience with PCB layout software such as Altium.
Project description: Hydrogen derived from renewable energy sources, called â€œgreen hydrogenâ€�, is a compelling path towards decarbonization. There are many important challenges to be solved. Our group works on power electronic converters and systems which are required to interface large scale renewable energy production (e.g., from wind) to large scale hydrogen electrolyzers. These systems should be as low cost and efficient as possible. Students will: Assist with the development of an electrolysis demonstration unit that illustrates the utility of power electronics in these systems. This includes the creation of custom power electronics hardware. Students will assist or take the lead on: specifying the hydrogen electrolysis demonstration system, devising power electronics demonstrations for this system, and assisting with the advancement of emerging concepts being developed in our research group for these systems. Prerequisite skills/knowledge: Students must have a strong background in circuit analysis. Ideally, the student will have already completed a course in power electronics and have experience with PCB layout software such as Altium.
Project description: In this project, students will engineer an automated test setup for a custom in-house high frequency core loss tester in our laboratory. Students will: Be directly mentored by the faculty and a senior doctoral student with 8 years of software engineering experience. Specific tasks include: requirements engineering, feature implementation for our novel in-house test equipment. Prerequisite skills/knowledge: Working understanding of Python, C, version control
Project description: The research project focuses on developing secure computation techniques tailored for biomedical data, ensuring privacy while enabling meaningful analysis. Biomedical datasets, such as DNA sequences and medical records, are highly sensitive and require robust privacy protections. This project leverages advanced cryptographic methods, including secure multi-party computation (MPC), homomorphic encryption (HE), and private information retrieval (PIR), to facilitate computations on these datasets without exposing raw data. The goal is to address critical challenges such as efficient genomic data alignment, privacy-preserving data sharing, and secure collaborative research. Students will: Focus on designing, implementing, and optimizing secure computation protocols, where feasible. They will work closely with our senior Ph.D. students, gaining hands-on experience in addressing challenges specific to biomedical data. Prerequisite skills/knowledge: C++, Python, BS in Engineering
Project description: A compelling opportunity for higher energy density batteries is solid-state electrolytes (SSEs), which offer a host of advantages over the liquid electrolytes that dominate the market today: they are leak-proof, energy-dense, flame-resistant, contain no toxic organic solvents, and can charge faster. A challenge to the commercialization of solid-state batteries is the development of a stable SSE that can support the film stresses that develop from significant expansion during cycling and can be processed with low-cost manufacturing processes. The objective of this work is to two-fold: to improve the thermomechanical reliability of SSEs and to subsequently produce safe, durable, and high-specific energy solid state batteries with a robust thin film SSE. The overarching questions that will be investigated are the material (ionic and electronic conductivity) from thin-film processing of ceramic-based SSEs and mechanical properties that develop in SSEs for understanding of chemomechanical degradation modes. Students will: Learn how to make battery materials and devices from solution using printing processes and characterize them with electronic and ionic conductivity measurements. There is also funding for additional proejcts to work on perovskite-based photovoltaics materials and devices. Prerequisite skills/knowledge: Knowledge of electrochemistry, materials science, and mechanical properties is a plus (although not required).
Project description: Ultra wide band gap semiconductors (UWBG) such as Ga2O3, AlN and diamond are highly promising for high power applications such as power switching and high frequency power amplification. This project will study the design space of UWBG semiconductor transistors for optimial device performance such as on-resistance, breakdown voltage etc. This project focuses on TCAD modeling of ultra-wide band gap semiconductor devices. Students will: Get exposure to industry relevant experience in TCAD modeling of power semiconductor devices based on emerging ultra wide band gap semiconductors such as Ga2O3, diamond and AlN. Prerequisite skills/knowledge: Knowledge of semiconductor device physics.
Project description: This project will provide exciting opportunities to learn and apply system and web security concepts. The student will work on building a browser extension to monitor data flows from a device to remote servers and analyze these flows to investigate security and privacy issues. Students will: Learn to develop browswer plugin with javascript, use it to collect data from browser activities, and analyze the data to identify private data transmission. Prerequisite skills/knowledge: Knowledge of network traffic analysis tools, browser technology, programming in Javascript and python.
Project description: The project aims to understand and model human decision making process in the context of privacy and security behaviors. Toward this goal, we will collect both qualitative and quantitative data to learn about relevant variables and how they collectively influence decision making. Students will: Learn, apply, and develop theoretical models of human decision making process in the context of data privacy. We will collect data through user studies and analyze that data to build a theory of decision making processes. Prerequisite skills/knowledge: User study methods: interview/surveys, analysis of experimental data.
Project description: This research aims at synthesizing new biobased hydrogels to mitigate shrinkage in 3D printed concrete structures. Students will: Work with a graduate student helping her with the synthesis and characterization of biobased hydrogels and quantify their potential in mitigating the shrinkage in 3D printed concrete. Prerequisite skills/knowledge: Lab safety, previous experience with concrete and biobased materials is advantageous but not necessary.
Project description: The aim of this research is to understand the influence of stress concentrations on metal additive manufactured components. Students will: Be trained to perform mechanical testing on metal AM specimens and FE modeling. The student will be exposed to state-of-the-art mechanical testing and data-driven fracture modeling. Prerequisite skills/knowledge: Previous experience in mechanical testing is a plus, but not necessary.
Project description: The project aims to deliver virtual field trips for student spatial communication. Particularly, automatic scaffolds will be derived from human data to support learning of spatial abilities and communication skills within virtual reality experiences. Students will: Focus on developing machine learning models that can help classify in real-time multimodal data from multiuser converstions (text and audio), spatial information from user interactions in VR, and face expressions from videos. This will include all stages of development from data labeling, model architeture design, and model testing and validation. Prerequisite skills/knowledge: Machine Learning (Python-based), Game Development (e.g., Unity, Unreal), WebGL (not required but willing to learn).
Project description: This project will investigate the tradeoff and cobenefits of floating solar power generation on lake and reservoir surfaces in the arid and semi-arid southwest US. Students will: Work with a graduate student to compile publicly accessible information on energy and water infrastructure, develop analytics to evaluate various standard of infrastructure readiness for floating solar power and hydrogen production. Prerequisite skills/knowledge: Geographic Information system, use of machine learning package.
Project description: Electrification of some industrial processes are already economical in the state of Arizona (e.g., electrifying forklifts) while others need further analysis and development. This SURI project will use techno-economic models to assess the feasibility of current electrification strategies for industrial clients. Students will: Work on the evaluation of multiple electrification strategies that are applicable in industry and assessment of the current capital costs and energy savings to evaluate the return on investment. Prerequisite skills/knowledge: Basic concepts from thermodynamics and energy conversion are beneficial.
Project description: The development of low-power microelectronic devices, quantum computers, and data storage is driven by how the atoms are bonded to one another and their corresponding atomic scale electronic interactions. Transmission electron microscopy and spectroscopy is the most commonly used metrology to image and probe electronic and magnetic interactions. However, the primary challenge for this characterization is sample preparation. During this summer internship, the students will primarily learn to prepare electron transparent sample via mechanical polishing and stamping techniques. Successful optimization of the transfer techniques will result in unique electron microscopy experiments to image spin textures, polarization domains, atomic vibrations, defects, and strain at the buried interfaces in the future. Students will: Learn how to fabricate TEM samples, simulate images and understand diffraction patterns. Prerequisite skills/knowledge: Knowledge about materials science, condensed matter physics and inorganic chemistry (although not required)
Project description: Label-free optical imaging and detection of molecular biomarkers. Develop a point of care. Students will: Work with a grad student or postdoc to develop/test new biosensors. Prerequisite skills/knowledge: BS in biomedical engineer, chemistry or related field.
Project description: Nanophotonics intercrosses nanotechnology and photonics. This research project will study the phenomena of light interacting with matters at the nanoscale. Leveraging the optical design and nanochemical synthesis or 3D printing-assembly that you will learn, we aim to create engineered nanostructures/nanoparticles that can manipulate light in ways not possible with naturally existed materials, prospecting innovations in applications for light (solar) energy harvesting, imaging/sensing, data storage, computing and communication through photons. Students will: Be responsible for the optical design and the desired nanostructure/nanoparticle implementation. Interests and motivation for the described research are required while learning the interdisciplinary knowledge of nanotechnology and photonics. Prerequisite skills/knowledge: STEM major (interests first).
Project description: This research will explore algorithm development for human-robot interactions, with applications in manufacturing, autonomous driving, and assistive devices. Students will: Implement robot learning algorithms into various robot hardware and simulators, and help conduct human experiments to evaluate the performance of the algorithms as well as perform data analysis. Prerequisite skills/knowledge: Experience in robot learning, control systems, and robotics hardware (especially manipulators).
Project description: The Xu Lab at ASU focuses on advancing next-generation solid-state energy storage systems across multiple scales for a variety of applications. At the micro-scale, we develop microbatteries designed to power small devices such as sensors, medical implants, and brain chips. At larger scales, we work on batteries capable of powering electric vehicles, enabling advancements in electric aviation, and supporting grid energy storage. Students in the lab engage in the design and modeling of battery systems tailored for diverse applications, ranging from neural implants, RFID tags to power banks, vehicles and beyond. Through this work, they gain knowledge in electrochemistry and battery systems while utilizing advanced simulation tools such as COMSOL to enhance battery performance and optimize designs. Students will: Work on design and modelling, fabricating cells, and testing. Prerequisite skills/knowledge: Electrochemistry, energy storage, battery, COMSOL.
Project description: This project will explore techniques in the analysis of programs for correctness and the triaging and repair of detected flaws. Students will: Develop new analyses, run experiments on software, analyze the results, and write technical reports, depending on specific abilities and interests. Prerequisite skills/knowledge: Some skills in low-level computing (e.g., assembly, memory errors, etc) are required.
Project description: The interdisciplinary research has a focus on developing data-driven models to enhance grid stability and optimize EV integration in renewable-powered microgrids. The project will contribute to sustainable energy transformation while addressing critical challenges in cybersecurity and real-time energy management. Students will: Explore ML techniques to analyze EV charging patterns, forecast renewable energy generation, and detect cyber threats targeting grid infrastructure. By leveraging advanced data science and security algorithms, the research aims to improve the resilience and efficiency of energy systems. Prerequisite skills/knowledge: BS in Engineering.
Project description: Explore and investigate the physics of GenAI models, analyze them and conduct semantic agumentation for safety-critical tasks. Students will: Code, read papers, implement modules, and help curating the data. Prerequisite skills/knowledge: Computer Science majors are preferrd, but not a requirement.
Project description: Heterogeneous catalysis is a key technology in the production of chemicals, fuels, polymers, and pharmaceuticals. Though well-established for petrochemical processes, the extension of heterogeneous catalysis to sustainable chemical production (e.g., upgrading biomass), is still underdeveloped. A key challenge is that traditional heterogeneous catalysts show poor stability and selectivity in the presence of water, deactivating rapidly in processes involving water- and oxygen-rich biomass-derived molecules. This project will systematically explore reactivity and deactivation of conventional and tailored nanoporous zeolite-based catalysts toward prototypical oxygen-containing organic molecules. The objective is to obtain a molecular-level understanding of catalyst deactivation pathways and develop design criteria for catalysts that enact selective molecular transformations of biomass-derived molecules. Students will: Develop protocols for measuring the catalytic reaction properties (selectivity, conversion, kinetics) of a series of zeolite-based catalysts for the conversion of small molecules typical of biomass derivatives. The student will analyze the reaction data with respect to established kinetic models and optimize reaction conditions. Depending on their initial progress, the student will also be involved in in-situ and post-reaction spectroscopic analysis of the catalysts to track activation/deactivation processes. Prerequisite skills/knowledge: Experience/interest in chemical reaction kinetics, analytical chemistry, and/or inorganic chemistry.
Project description: This project seeks to understand the fundamental role of different dopant atoms and surface sites in determining the optoelectronic properties of doped nanocrystalline semiconductors. Nanocrystalline semiconductors are promising for high-performance optical devices, photovoltaics, and solid-state lighting because their electronic properties can be tuned across a wide range by controlling crystallite size and composition. Determining the influences of different dopant atoms and surface sites on bulk optoelectronic properties is crucial for engineering devices based on such materials. To that end, this project will systematically investigate the incorporation and influence on optoelectronic properties of different dopant atoms in tin oxide nanoparticles, with the goal of benchmarking new spectroscopic methods for extracting atomic-level information on electronic structure. Students will: Synthesize tin oxide nanoparticles using established solvothermal colloidal synthesis methods and investigate the incorporation of different dopant atoms (e.g., N, Al, P). The student will also characterize the nanomaterials using X-ray diffraction and UV-vis and FTIR spectroscopy to establish structure and optical properties. Prerequisite skills/knowledge: Experience/interest in semiconductor synthesis and physics, spectroscopy, inorganic chemistry.
Project description: The objective of the research is to develop digital twin for predicting and contorling multiphysics behaviors in laser power bed fusion process. Students will: Conduct simulations using COMSOL or OpenFoam to simluate laser-powder interaction during laser powder bed fusion and use experimental dataset to validate the developed models. Prerequisite skills/knowledge: Modeling and simulations

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Project description: Understand the physical scale-dependent mechanical & dynamic properties of meteoritic materials and gain insight into their deformation mechanisms and fracture & impact dynamics.. Students will: Assist in conducting ballistic impact and quasi-static compressive tests on meteorite samples coupled with digital image correlation techniques, and performing microscopy on the fragments from impact. Prerequisite skills/knowledge: Students from mechanical or aerospace engineering; some experience in hands-on experiments is a plus. Junior status would be preferable, but motivated sophomores who meet the requirements will also be considered.
Project description: The objective of this project is to explore the potential of large language models in generating 3D designs using text-based prompts. Students will: Explore the challenges in generating complex designs, best practices when providing text prompts, and incorporating different type of constraints. Furthremore, we will explore the potential of LLM in generating designs from a family, e.g., making changes to an existing design. Prerequisite skills/knowledge: The work will require knowledge of basic python (or any other) programming language, basic knowledge of large language models and how to use them.
Project description: This project is inspired by EPIXC with an aim to develop highly conductive electric conductors using carbon nanotubes (CNT) and copper, that contribute to the expansion of electrified processes with reduced carbon emission. In this project, a student aims to understand how the composite structure of carbon nanotube (CNT)-metal fibers affects their electrical and thermal conductivities. CNT-metal fiber is expected to offer extraordinary ratio of conductivity to mass, which, however, requires theoretical understanding of its structural (or morphology) effects. Students will: Learn a computational simulation model for electrical and thermal conductivity of CNT-metal fiber. After running simulations for several possible structures of this fiber, the student should discuss the effects of structure on electrical and thermal transport in the fiber, and propose an optimal structure. Prerequisite skills/knowledge: Knowledge of electrical and thermal conductivities in materials, numerical methods (finite element model).
Project description: This project utilizes a longitudinal epidemiological health dataset to advance understanding of cardiovascular health in a diverse U.S. population. By integrating demographic, behavioral, and clinical data, the project aims to provide actionable insights to improve cardiovascular health outcomes and inform public health strategies. Students will: Collaborate to (a) build a comprehensive data inventory, (b) develop predictive models to monitor health trajectories, and (c) explore graphical models to uncover relationships among multi-dimensional health risk factors. Prerequisite skills/knowledge: Programming languages such as R, Python, or MATLAB; Basic Probability, Statistics, and Data Mining.
Project description: The objective of the research is to develop a versatile technique that is capable of printing metallic structures at micrometer- scale resolution feasible for photonics and electrochemical sensing applications. Here we will explore a new solutionbased photochemically induced polymer-assisted deposition (PIPAD) process to produce metallic composite microstructures. Students will: Work with a postdoc on addititive manufacturing by engineering optical system and chemical precursors. Prerequisite skills/knowledge: Photonics; chemistry, electrochemistry, and fabrication skills are desired but not required.
Project description: The objective of the research is to design nanoparticle-based, portable biomolecular sensors and their electronic readout systems that will be suitable for accessible healthcare use. The goal is to make the system suitable for detection of both infectious diseases and chronical diseases for those inexperienced users, which will have significant impact on broadening healthcare in resource-limited areas. Students will: Work with graduate students on assay design process and validation. Prerequisite skills/knowledge: Biochemistry, circuits, and programming skills are desired but not required.
Project description: This research project focuses on designing and fabricating bioinspired structures to mitigate the Leidenfrost effect, a phenomenon where a vapor layer forms between a hot surface and a liquid, inhibiting efficient heat transfer. Drawing inspiration from natural textures and patterns, the project aims to create advanced surface designs that disrupt vapor layer formation and enhance sustained thermal cooling. These structures will be fabricated using state-of-the-art additive manufacturing techniques, enabling precise control of surface geometry and material properties. By overcoming the limitations of conventional cooling methods, this work seeks to improve energy efficiency and thermal management in various applications, including industrial heat exchangers, electronics cooling, and sustainable energy systems. The outcomes of this study have the potential to significantly advance our understanding of thermofluidic interactions while contributing to environmentally friendly cooling solutions. Students will: Be involved in designing micro- and nanoscale surface structures using CAD software, fabricating these structures through advanced 3D printing techniques, and conducting experiments to evaluate their effectiveness in mitigating the Leidenfrost effect. Additional responsibilities may include analyzing heat transfer performance, optimizing surface geometries based on experimental data, and contributing to the development of sustainable cooling solutions. Prerequisite skills/knowledge: CAD, simulation
Project description: This project aims to (i) investigate the potential of utilizing native fungal strains for heavy metal bioremediation and (ii) explore the characteristics of fungi-metal-organic framework (F-MOF) composite materials for tailored applications. Students will: Design and conduct bench-scale laboratory experiments, including culturing fungi in growth media supplemented with metals. They will perform a comprehensive range of characterization tests and analyses, including data collection, compilation, analysis, and reduction, as well as writing up their findings and report. Prerequisite skills/knowledge: Previous experience in a BSL-2 level environmental microbiology lab and a strong interest in fungi mycelium culture will be advantageous. A working knowledge of bioremediation and microbe-metal interactions would also be beneficial.
Project description: This project focuses on the evaluation and assessment of various binary decompilation tools, such as Hex-Rays Decompiler (IDA Pro), Ghidra, Binary Ninja, Reko Decompiler, and angr decompiler. Researchers on this project will investigate potential metrics that measure the quality of binary decompilation output. The project will result in the creation of a data set as well as an online platform that evaluates decompilers on multiple metrics. Students will: Work on one of the following tasks: (a) proposing new metrics and studying existing metrics for evaluaitng the quality of decompilation output; (b) building an online service for evaluating output of existing decompilers. Prerequisite skills/knowledge: Some skills in low-level computing (e.g., assembly, memory errors, etc) are required. Also Python 3 programming experience is a must. Strong interest in compiler theory (or decompiler theory) and/or programming languages.
Project description: This project focuses on building a correct and verifiable binary decompilation technique for a small set of binary programs. By fixing issues and adding new analysis passes into angr decompiler, we will create sound and recompilable decompilation for executables and libraries in old PC games or Windows software (especially healthcare software). Students will: Work on one of the following tasks: (a) evaluating angr decompiler on executables of old PC games and other Windows software (especially healthcare software); (b) curating a data set of old PC games and other Windows software for evaluating angr decompiler. Prerequisite skills/knowledge: Some skills in low-level computing (e.g., assembly, memory errors, etc) are required. Also Python 3 programming experience is a must. Strong interest in compiler theory (or decompiler theory) and/or programming languages.
Project description: The projects aim to develop efficient Machine learning models to fine tune and prompt large language models to understand the root causes of different accident report to understand the major root causes of aviation accidents Students will: Work on ML algorithms implementation and development. Prerequisite skills/knowledge: Python, Pytorch
Project description: Detecting and Remediating Online Study Fraud: Since the bot crisis of 2018, crowdâ€‘sourced studies have been critically hindered by fraudulent responses. Amazon Mechanical Turk surveys, once representative of the USâ€‘census, are now not generalizable; $50,000 surveys have fraud rates as high as 96%; and filtering fraudulent data can take multiple months and still only result in a a single authentic response among 1000. To protect studies, researchers in various fields have independently created adâ€‘hoc mechanisms to distinguish real responses from fraud; however, these mechanisms are often not principled, not adversarially robust, nor address emerging concerns. This project will investigate how to make principled defenses against study fraud. This project will investigate how online study fraud occurs, whether it can be effectively detected, and whether it can be prevented. Students will: Investigate the blackmarket of the fraud ecosystem, systematically evaluating proposed detection methods, or creating a novel detection method, depending on the interests and skills of the applicant. Prerequisite skills/knowledge: Javascript, computer networking, computer security & privacy, basic programming.
Project description: Investigating the Security and Privacy effect of Human-Artificial Intelligence Interaction: Currently, there is a lack of principled methods to construct safe and secure human-ML interaction paradigms. Thus, to prevent harm in ML-based systems, it is paramount that we understand vulnerabilities and apply safeguards now. This set of projects will investigate how human interaction impacts ML security in two ways: How human factors can be 1) exploited to reduce security or 2) harnessed to improve security. Projects topics may include detecting and mitigating the effect of deepfakes (topic 1), or developing ways to prevent vulnerabilities and prevent exploitation in developed machine learning systems (topic 2). The specific topic can be dependent upon the interests and proposals of the applicant. Students will: Develop UI to convey provenance information for media and indicators to reduce the effect of deepfakes, understand how to develop machine learning coursework to include modules on adversarial machine learning topics, or discovering ways that adversarial machine learning exploits occur in practice, and developing methods to mitigate them. Prerequisite skills/knowledge: Machine learning, human factors methodologies (e.g., experimental design, interviews, qualitative coding), computer security & privacy.
Project description: This project aims to build high-performance and reconfigurable computer architectures for deep learning applications. Students will: Work on architectural simulation, hardware design, ML development. Prerequisite skills/knowledge: C/C++, Verilog, Pytorch.
Project description: This project aims to build high-performance GPU programming for scientific computing. Students will: Work on Cuda development. Prerequisite skills/knowledge: CUDA programming, C/C++.
Project description: Learn how to fabricate microfluidics and ancillary components for diagnostic cartridges. Investigate mechanisms for actuating the release of reagents and record data from experiments. Complete a technical report including data analysis for presentation of results. Students will: Investigate the use of methods to remove the need for cold storage of reagents used in point of care diagnostics. The microfluidic environment complicates the mixing and flow of the reagents and samples added to the cartridges. Prerequisite skills/knowledge: Excellent fine motor skills, data analysis, basic wet lab skills, laboratory safety
Project description: Learn how to fabricate test devices using precision fabrication and polymers, complete testing of delicate components, electrical measurements and data analysis, prepare a technical report. Students will: The student will investigate the use and degradation of devices place in brain using a simulated brain environment. The student will use wireless methods of interogating the devices operation and gain information about the patient's health and device degredation. Prerequisite skills/knowledge: Basic electronics including frequency dependent analysis, excellent fine motor skills, data analysis, basic wet lab skills, laboratory safety
Project description: The Weaver lab designs macroencapsulation devices with complex geometries and engineers high-throughput biomanufacturing techniques to encapsulate cells in these devices. This project will entail optimization of hydrogel injection mold design and encapsulation device fabrication, and downstream assessment of cell viability and engraftment. Students will: Assist with a tissue engineering project incorporating cells into hydrogels and assessing cell viability and differentiation. Prerequisite skills/knowledge: Not required, but previous experience in CAD design, 3D printing, cell culture, hydrogel fabrication, or histology techniques are a plus.
Project description: The aim of the project is to simulate a continuum robotic arm with physics-informed data-driven methods (Koopman operator). The student will study how to improve the accuracy of the model and reduce the requirement of the training data. The arm will be controlled to conduct a series of tasks such as maneuvering through tree branches to pick fruits. Students will: Study physics-based and data-driven simulation methods, derive models, and implement the simulation with python/C++. Prerequisite skills/knowledge: Knowledge of solid mechanics, dynamic systems, and numerical methods (ODE/PDE solvers). Proficient in one programming language: Python/C++.
Project description: The aim of this project is to develop an underwater robotic arm. The robotic arm will be remotely controlled to repair nets, monitor fish, or take samples. The desired applicants have a strong interest in research and have hands-on experience in mechanical engineering, electrical engineering, and computer science. Students will: Modify the current mechanical design, especially waterproof the robotics arm hardware, derive dynamics models, and implement the simulation and control algorithm with python/C++. Prerequisite skills/knowledge: Basic mechanical design, mechatronics design, and Arduino programing. Know about robotic operating systems. Students in computer science and electrical engineering are encouraged to apply.
Project description: Faculty leads also include Vikram Kodibagkar. The project involves analysis of simultaneous MRI oximetry / ECoG data. Students will: Analyze previously acquired multi modality data (MRI, ECoG) from rodents with the overall goal of artifact reduction in ECoG data and assessing correlaltions with MR oximetry data. Additionally, the student will gain exposure to data acquisition and analysis using a benchtop MRI scanner as well as hands on techniques for design of multimodal brain implants. Prerequisite skills/knowledge: Previous experience with Python, MATLAB for data analysis is a plus.
Project description: This project aims to explore the potential of combining knowledge-based and learning-based methods to enhance the generation of traffic scenarios for testing and evaluating AV safety. Students will: Leverage both hardware and software tools in the BELIV lab to conduct scenario-based testing of automated vehicles. Prerequisite skills/knowledge: ROS, Linux, Python, Generative AI, Reinforcement learning.
Project description: This project will focus on developing Universal BMS (U-BMS) with Digital Twin technology and AI-powered solutions for Battery Energy Storage Systems (BESS). Students will: Develop digital twin for battery systems and train AI models to enhance BMS accuracy and functionality. Prerequisite skills/knowledge: Matlab/Simulink, Battery Managment System, Digital Twin, Machine Learning.
Project description: This project aims to evaluate the mechanism of action of a biomimetic nanodrug developed in our laboratory using high-throughput transcriptomics and bioinformatic analysis. Students will: Gain hands-on experience with fundamental cellular and molecular biology assays and develop skills in bioinformatics for analyzing RNA-seq data. Prerequisite skills/knowledge: Cell biology, molecular biology, biomaterials.
Project description: This project will focus on finetuning of generative models. Diffusion based generative models are the key components of industrial genAI. However, these models are slow to sample and provide no assurances of fairness in sampling from the input support. Our lab focuses on enhancing the speed of sampling diffusion models and also evaluating their fairness guarantees. Prerequisite skills/knowledge: Student must have a strong background in statistics, probability, and Python programming.
Project description: Compared to traditional rigid structures and robots, soft robots, such as a bio-inspired snake robots, are more adaptable in complex environment. In this project, we will use physics-informed machine learning techniques to design and control the bioinspired soft robots. Students will: Develop graph-based machine-learning methods to model soft robotics and mechanical metamaterials. The student will fabricate the robot using laser cutting and conduct experiments to verify the design. Prerequisite skills/knowledge: Machine learning, Structural mechanics, Python-based programming.
Project description: Fish and birds oftentimes form a collective group to save energy during locomotion. Such phenomena are known as "schooling". In this project, we will understand the benefit of the schooling phenomena involving multiple fish and birds in fluid flows through numerical simulation and dynamical modeling. We will develop model-based control to teach the optimal schooling strategy. Students will: Develop multiple robot to mimick fish schooling in computational fluid dynamics simulation environment. The student will also develop model-based controls to control the robot to accomplish certain tasks, such as search and rescue. Prerequisite skills/knowledge: Machine learning, Fluid mechanics, Python-based programming, and willing to learn new programming language.
Project description: This project aims to develop machine-learning enhancements to incorporate semiconductor packaging analysis to electronic design automation. ML models and design metrics of the multi-physics performance in packaging design will be used to advance co-design algorithm in early stage physical design of electronics. Students will: Work on fine-tuning ML model, CAD simulations to generate datasets, embed ML model into one of the EDA algorithms. Prerequisite skills/knowledge: Knowledgeable in machine learning, project experience on electronic design automation, hands-on experience in programming (C/C++ and/or Python).
Project description: This research will investigate the photomechanical behaviors of flexible photovoltaic materials and devices using multiscale material modeling and experimentation. It will analyze the impact of environmental and mechanical stresses on material defect evolution and overall performance of thin-film solar cells, particularly under cyclic loading and light exposure. The study aims to optimize material properties and structural designs to enhance durability and efficiency, aligning with sustainability goals and contributing to advancements in semiconductor manufacturing. Students will: Gain knowledge of photovoltaic materials and devices, receive training in finite element modeling and atomic-scale material modeling, and develop expertise in micromechanical testing techniques. Prerequisite skills/knowledge: Junior or senior in materials science or mechanical engineering.
Project description: We are developing improved cell culture models of human brain to improve accuracy and work toward effective study and treatment of neurological disease. This project will use microscopy and RNA analysis strategies to assess how changes in cell culture conditions/environment, focused on oxygen and glucose accessibility, impact homeostasis and disease states. Students will: Learn how to process samples for RNA and protein analyses and compare differences across conditions. The analysis of this data will then be implemented to improve the accuracy of our cell culture conditions. Prerequisite skills/knowledge: Working understanding of basic molecular biology and some wet lab experience, would be helpful.
Project description: The research project is to develop a solar drievn hydrogen production system. It involves both hardware and software development. Depending on the academic discipline, the student will be assigned to a task in the project. Some of the sample topics include water treatment for hydrogen production, current and voltage sensors for the system, control algorithm development, safe hydrogen handling, voltage and power matching between electrolyzer and solar array, system operation and maintennance, etc. Students with various engineering backgrounds are encouraged to apply including electrical, chemical, environmental, mechanical, industrial, materials, etc. Students will: Be assigned specifiic tasks that will be determined after an interview with professor and PhD students. Prerequisite skills/knowledge: STEM major.
Project description: Magnetic components (inductors and transformers) bottleneck the size, weight, and loss of many power electronic converters. A critical avenue towards mitigating this bottleneck is to better understand the parasitic characteristics of these materials, especially their inherent self-resonance. In this project, the student will be part of a team developing models of self-resonance and producing high performance magnetic components for power converters. Students will: Assist or take the lead on: designing an experimental testbed to evaluate power magnetic components, developing new printed circuit boards for this effort, soldering these prototypes, testing new magnetic components using the developed hardware, and comparing predicted performance to experimental performance. Prerequisite skills/knowledge: The student must have a strong background in circuit analysis. Ideally, the student will have already completed a course in power electronics and have experience with PCB layout software such as Altium.
Project description: Hydrogen derived from renewable energy sources, called â€œgreen hydrogenâ€�, is a compelling path towards decarbonization. There are many important challenges to be solved. Our group works on power electronic converters and systems which are required to interface large scale renewable energy production (e.g., from wind) to large scale hydrogen electrolyzers. These systems should be as low cost and efficient as possible. Students will: Assist with the development of an electrolysis demonstration unit that illustrates the utility of power electronics in these systems. This includes the creation of custom power electronics hardware. Students will assist or take the lead on: specifying the hydrogen electrolysis demonstration system, devising power electronics demonstrations for this system, and assisting with the advancement of emerging concepts being developed in our research group for these systems. Prerequisite skills/knowledge: Students must have a strong background in circuit analysis. Ideally, the student will have already completed a course in power electronics and have experience with PCB layout software such as Altium.
Project description: In this project, students will engineer an automated test setup for a custom in-house high frequency core loss tester in our laboratory. Students will: Be directly mentored by the faculty and a senior doctoral student with 8 years of software engineering experience. Specific tasks include: requirements engineering, feature implementation for our novel in-house test equipment. Prerequisite skills/knowledge: Working understanding of Python, C, version control
Project description: The research project focuses on developing secure computation techniques tailored for biomedical data, ensuring privacy while enabling meaningful analysis. Biomedical datasets, such as DNA sequences and medical records, are highly sensitive and require robust privacy protections. This project leverages advanced cryptographic methods, including secure multi-party computation (MPC), homomorphic encryption (HE), and private information retrieval (PIR), to facilitate computations on these datasets without exposing raw data. The goal is to address critical challenges such as efficient genomic data alignment, privacy-preserving data sharing, and secure collaborative research. Students will: Focus on designing, implementing, and optimizing secure computation protocols, where feasible. They will work closely with our senior Ph.D. students, gaining hands-on experience in addressing challenges specific to biomedical data. Prerequisite skills/knowledge: C++, Python, BS in Engineering
Project description: A compelling opportunity for higher energy density batteries is solid-state electrolytes (SSEs), which offer a host of advantages over the liquid electrolytes that dominate the market today: they are leak-proof, energy-dense, flame-resistant, contain no toxic organic solvents, and can charge faster. A challenge to the commercialization of solid-state batteries is the development of a stable SSE that can support the film stresses that develop from significant expansion during cycling and can be processed with low-cost manufacturing processes. The objective of this work is to two-fold: to improve the thermomechanical reliability of SSEs and to subsequently produce safe, durable, and high-specific energy solid state batteries with a robust thin film SSE. The overarching questions that will be investigated are the material (ionic and electronic conductivity) from thin-film processing of ceramic-based SSEs and mechanical properties that develop in SSEs for understanding of chemomechanical degradation modes. Students will: Learn how to make battery materials and devices from solution using printing processes and characterize them with electronic and ionic conductivity measurements. There is also funding for additional proejcts to work on perovskite-based photovoltaics materials and devices. Prerequisite skills/knowledge: Knowledge of electrochemistry, materials science, and mechanical properties is a plus (although not required).
Project description: Ultra wide band gap semiconductors (UWBG) such as Ga2O3, AlN and diamond are highly promising for high power applications such as power switching and high frequency power amplification. This project will study the design space of UWBG semiconductor transistors for optimial device performance such as on-resistance, breakdown voltage etc. This project focuses on TCAD modeling of ultra-wide band gap semiconductor devices. Students will: Get exposure to industry relevant experience in TCAD modeling of power semiconductor devices based on emerging ultra wide band gap semiconductors such as Ga2O3, diamond and AlN. Prerequisite skills/knowledge: Knowledge of semiconductor device physics.
Project description: This project will provide exciting opportunities to learn and apply system and web security concepts. The student will work on building a browser extension to monitor data flows from a device to remote servers and analyze these flows to investigate security and privacy issues. Students will: Learn to develop browswer plugin with javascript, use it to collect data from browser activities, and analyze the data to identify private data transmission. Prerequisite skills/knowledge: Knowledge of network traffic analysis tools, browser technology, programming in Javascript and python.
Project description: The project aims to understand and model human decision making process in the context of privacy and security behaviors. Toward this goal, we will collect both qualitative and quantitative data to learn about relevant variables and how they collectively influence decision making. Students will: Learn, apply, and develop theoretical models of human decision making process in the context of data privacy. We will collect data through user studies and analyze that data to build a theory of decision making processes. Prerequisite skills/knowledge: User study methods: interview/surveys, analysis of experimental data.
Project description: This research aims at synthesizing new biobased hydrogels to mitigate shrinkage in 3D printed concrete structures. Students will: Work with a graduate student helping her with the synthesis and characterization of biobased hydrogels and quantify their potential in mitigating the shrinkage in 3D printed concrete. Prerequisite skills/knowledge: Lab safety, previous experience with concrete and biobased materials is advantageous but not necessary.
Project description: The aim of this research is to understand the influence of stress concentrations on metal additive manufactured components. Students will: Be trained to perform mechanical testing on metal AM specimens and FE modeling. The student will be exposed to state-of-the-art mechanical testing and data-driven fracture modeling. Prerequisite skills/knowledge: Previous experience in mechanical testing is a plus, but not necessary.
Project description: The project aims to deliver virtual field trips for student spatial communication. Particularly, automatic scaffolds will be derived from human data to support learning of spatial abilities and communication skills within virtual reality experiences. Students will: Focus on developing machine learning models that can help classify in real-time multimodal data from multiuser converstions (text and audio), spatial information from user interactions in VR, and face expressions from videos. This will include all stages of development from data labeling, model architeture design, and model testing and validation. Prerequisite skills/knowledge: Machine Learning (Python-based), Game Development (e.g., Unity, Unreal), WebGL (not required but willing to learn).
Project description: This project will investigate the tradeoff and cobenefits of floating solar power generation on lake and reservoir surfaces in the arid and semi-arid southwest US. Students will: Work with a graduate student to compile publicly accessible information on energy and water infrastructure, develop analytics to evaluate various standard of infrastructure readiness for floating solar power and hydrogen production. Prerequisite skills/knowledge: Geographic Information system, use of machine learning package.
Project description: Electrification of some industrial processes are already economical in the state of Arizona (e.g., electrifying forklifts) while others need further analysis and development. This SURI project will use techno-economic models to assess the feasibility of current electrification strategies for industrial clients. Students will: Work on the evaluation of multiple electrification strategies that are applicable in industry and assessment of the current capital costs and energy savings to evaluate the return on investment. Prerequisite skills/knowledge: Basic concepts from thermodynamics and energy conversion are beneficial.
Project description: The development of low-power microelectronic devices, quantum computers, and data storage is driven by how the atoms are bonded to one another and their corresponding atomic scale electronic interactions. Transmission electron microscopy and spectroscopy is the most commonly used metrology to image and probe electronic and magnetic interactions. However, the primary challenge for this characterization is sample preparation. During this summer internship, the students will primarily learn to prepare electron transparent sample via mechanical polishing and stamping techniques. Successful optimization of the transfer techniques will result in unique electron microscopy experiments to image spin textures, polarization domains, atomic vibrations, defects, and strain at the buried interfaces in the future. Students will: Learn how to fabricate TEM samples, simulate images and understand diffraction patterns. Prerequisite skills/knowledge: Knowledge about materials science, condensed matter physics and inorganic chemistry (although not required)
Project description: Label-free optical imaging and detection of molecular biomarkers. Develop a point of care. Students will: Work with a grad student or postdoc to develop/test new biosensors. Prerequisite skills/knowledge: BS in biomedical engineer, chemistry or related field.
Project description: Nanophotonics intercrosses nanotechnology and photonics. This research project will study the phenomena of light interacting with matters at the nanoscale. Leveraging the optical design and nanochemical synthesis or 3D printing-assembly that you will learn, we aim to create engineered nanostructures/nanoparticles that can manipulate light in ways not possible with naturally existed materials, prospecting innovations in applications for light (solar) energy harvesting, imaging/sensing, data storage, computing and communication through photons. Students will: Be responsible for the optical design and the desired nanostructure/nanoparticle implementation. Interests and motivation for the described research are required while learning the interdisciplinary knowledge of nanotechnology and photonics. Prerequisite skills/knowledge: STEM major (interests first).
Project description: This research will explore algorithm development for human-robot interactions, with applications in manufacturing, autonomous driving, and assistive devices. Students will: Implement robot learning algorithms into various robot hardware and simulators, and help conduct human experiments to evaluate the performance of the algorithms as well as perform data analysis. Prerequisite skills/knowledge: Experience in robot learning, control systems, and robotics hardware (especially manipulators).
Project description: The Xu Lab at ASU focuses on advancing next-generation solid-state energy storage systems across multiple scales for a variety of applications. At the micro-scale, we develop microbatteries designed to power small devices such as sensors, medical implants, and brain chips. At larger scales, we work on batteries capable of powering electric vehicles, enabling advancements in electric aviation, and supporting grid energy storage. Students in the lab engage in the design and modeling of battery systems tailored for diverse applications, ranging from neural implants, RFID tags to power banks, vehicles and beyond. Through this work, they gain knowledge in electrochemistry and battery systems while utilizing advanced simulation tools such as COMSOL to enhance battery performance and optimize designs. Students will: Work on design and modelling, fabricating cells, and testing. Prerequisite skills/knowledge: Electrochemistry, energy storage, battery, COMSOL.
Project description: This project will explore techniques in the analysis of programs for correctness and the triaging and repair of detected flaws. Students will: Develop new analyses, run experiments on software, analyze the results, and write technical reports, depending on specific abilities and interests. Prerequisite skills/knowledge: Some skills in low-level computing (e.g., assembly, memory errors, etc) are required.
Project description: The interdisciplinary research has a focus on developing data-driven models to enhance grid stability and optimize EV integration in renewable-powered microgrids. The project will contribute to sustainable energy transformation while addressing critical challenges in cybersecurity and real-time energy management. Students will: Explore ML techniques to analyze EV charging patterns, forecast renewable energy generation, and detect cyber threats targeting grid infrastructure. By leveraging advanced data science and security algorithms, the research aims to improve the resilience and efficiency of energy systems. Prerequisite skills/knowledge: BS in Engineering.
Project description: Explore and investigate the physics of GenAI models, analyze them and conduct semantic agumentation for safety-critical tasks. Students will: Code, read papers, implement modules, and help curating the data. Prerequisite skills/knowledge: Computer Science majors are preferrd, but not a requirement.
Project description: Heterogeneous catalysis is a key technology in the production of chemicals, fuels, polymers, and pharmaceuticals. Though well-established for petrochemical processes, the extension of heterogeneous catalysis to sustainable chemical production (e.g., upgrading biomass), is still underdeveloped. A key challenge is that traditional heterogeneous catalysts show poor stability and selectivity in the presence of water, deactivating rapidly in processes involving water- and oxygen-rich biomass-derived molecules. This project will systematically explore reactivity and deactivation of conventional and tailored nanoporous zeolite-based catalysts toward prototypical oxygen-containing organic molecules. The objective is to obtain a molecular-level understanding of catalyst deactivation pathways and develop design criteria for catalysts that enact selective molecular transformations of biomass-derived molecules. Students will: Develop protocols for measuring the catalytic reaction properties (selectivity, conversion, kinetics) of a series of zeolite-based catalysts for the conversion of small molecules typical of biomass derivatives. The student will analyze the reaction data with respect to established kinetic models and optimize reaction conditions. Depending on their initial progress, the student will also be involved in in-situ and post-reaction spectroscopic analysis of the catalysts to track activation/deactivation processes. Prerequisite skills/knowledge: Experience/interest in chemical reaction kinetics, analytical chemistry, and/or inorganic chemistry.
Project description: This project seeks to understand the fundamental role of different dopant atoms and surface sites in determining the optoelectronic properties of doped nanocrystalline semiconductors. Nanocrystalline semiconductors are promising for high-performance optical devices, photovoltaics, and solid-state lighting because their electronic properties can be tuned across a wide range by controlling crystallite size and composition. Determining the influences of different dopant atoms and surface sites on bulk optoelectronic properties is crucial for engineering devices based on such materials. To that end, this project will systematically investigate the incorporation and influence on optoelectronic properties of different dopant atoms in tin oxide nanoparticles, with the goal of benchmarking new spectroscopic methods for extracting atomic-level information on electronic structure. Students will: Synthesize tin oxide nanoparticles using established solvothermal colloidal synthesis methods and investigate the incorporation of different dopant atoms (e.g., N, Al, P). The student will also characterize the nanomaterials using X-ray diffraction and UV-vis and FTIR spectroscopy to establish structure and optical properties. Prerequisite skills/knowledge: Experience/interest in semiconductor synthesis and physics, spectroscopy, inorganic chemistry.
Project description: The objective of the research is to develop digital twin for predicting and contorling multiphysics behaviors in laser power bed fusion process. Students will: Conduct simulations using COMSOL or OpenFoam to simluate laser-powder interaction during laser powder bed fusion and use experimental dataset to validate the developed models. Prerequisite skills/knowledge: Modeling and simulations

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How did you hear about the SURI Summer Research Initiative?

Please attach the following documents:

Your brief statement of interest in SURI and supporting documents (research interest statement, resume, unofficial or official transcript, English Proficiency) in one file (i.e. .pdf, .doc, .docx. No .zip files please). You can use Braintrade.net or other resources to merge your PDFs.

Research Interest Statement - a brief statement describing your interest in participating in SURI which may include your research interests, any relevant research, academic, or work experience, your goals and how SURI will help you achieve them (up to 500 words)
Resume
Transcripts - a copy of your transcripts (official or unofficial)
English Proficiency - for applicants who are non-U.S. citizens studying at universities OUTSIDE the U. S., please upload documentation of English-language proficiency (e.g., TOEFL, IELTS, etc.):
https://admission.asu.edu/international/undergrad/english-proficiency

Save your files as last name, first name (i.e. Smith, John) or your application will be considered incomplete.

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My proposal has the following items
(all items must be included with your application submittal in order to be considered complete):

Brief statement describing your interest in participating in SURI which may include your research interests, any relevant research, academic, or work experience, your goals and how SURI will help you achieve them (up to 500 words).

Resume

Unofficial Transcript

For applicants who are non-U.S. citizens studying at universities OUTSIDE the U. S., please upload documentation of English-language proficiency (e.g., TOEFL, IELTS, etc.)

By selecting "Submit", I certify that the information throughout this application is accurate and that misrepresentation of any facts or details could result in ineligibility for the SURI program.

A summary of your responses along with a link to edit your application will be send to the email address you provided above.

Summer 2025