Research Interests

Computational Mechanics, Machine learning, Computational Biology

Topics of Potential Projects

Pressure ulcer modeling: finite element models of skin, and how it deforms creating ischemia, and subsequent inflammation and wounding.

Embryo morphogenesis: finite element models of zebrafish embryo development, how the embryo gets its shape over time.

Student Requirements / Skills Needed

• Programming skills (good Matlab, or Python skills, alternatively Java or C++ experience would be good)
• Mechanics of materials (basic stress analysis)
• Finite element modeling (basic use of commercial software like Abaqus or Ansys)

Research Interests

Building a SMART Small Farm

Topics of Potential Projects

The project aims to improve farm productivity and well-being of small scale farms by experimenting with a suite of digital technologies for farm management. There are many digital agricultural technologies, including farm management software, automatic irrigation systems, autonomous robots, IoT systems, and more. Each technology has its own investment costs, implementation challenges, and benefits to the user. In this project we will be establishing a smart farm on the Purdue campus for on-farm data collection, farm monitoring, and automating tedious agricultural practices. The student will work with the team to evaluate and implement digital agricultural technologies as part of their research. They will conduct research using one or more of the technologies, with a focus on evaluating usability, interoperability, and security. The student will work with the project leads to identify a technology that matches their expertise and we will co-design a small research project to create additional functionality or engineer complementary digital agriculture tools.

Student Requirements / Skills Needed

Minimum Requirements

• Skill in one or more programming languages
• Understanding of data analysis tools e.g., excel, python packages
• Willingness to do hands-on work in our small farm
• Interest in designing digital technologies in resource-constrained environments

Preferable Requirements

• Experience with one or more of: web development, electronics, sensors, robotics, or IoT systems
• Some experiences working in operations e.g., farm, factory, retail store

Research Interests

Integrating LLMs with Knowledge Graphs

Topics of Potential Projects

This project explores the intersection of Large Language Models (LLMs) and knowledge graphs to address the inherent limitation of LLMs, which are often ungrounded in facts, people, and places. While LLMs excel in natural language understanding, their responses may lack context and factual accuracy. By integrating LLMs with knowledge graphs, which provide structured representations of information about facts, entities, and relationships, this research aims to bridge the gap between language models and grounded knowledge, enhancing the accuracy and relevance of natural language processing tasks. The key challenge of this project is the transfer of information between the positional word embeddings of LLMs and the permutation-equivariant representations of facts, people, and places obtained from knowledge graphs.

Student Requirements / Skills Needed

Familiarity with pytorch, pytorch Geometric (Graph Neural Networks) and open-source large language models such as Llama 2 7B.

Research Interests

Fabrication of Ceramic Glass Particles for High-Temperature Rotary Detonation Engines (RDE)

Topics of Potential Projects

A rotating detonation engine (RDE) is a high-efficiency engine where one or more high-pressure explosions or detonations continuously travel around a cylindrical channel. RDEs have the potential to be superior to gas turbines and rocket engines and provide propulsion to hypersonic speeds. The shock waves produced by detonation, which occur at a specific and predictable frequency, cause significant stresses and high temperatures in the channel. At these operational temperatures, there are advantages to fabricating this channel of a ceramic material. However, the operating conditions are challenging for brittle elastic materials. We propose the development of a new class of ceramics that intentionally has discrete viscous phases added to a purely elastic matrix. This approach will take advantage of the energy-absorbing relaxation mechanisms associated with glassy phases near their Tg, primarily via translational and rotational motions of the silica tetrahedron and atoms. The student involved in this project will work on fabricating ceramic glass particles with tailored Tg properties. These glassy particles will be incorporated into other high-temperature ceramics, such as silicon nitrate (Si3O4). The student will learn about particle fabrication and characterization, ceramic processing, and material property measurements. Students with a background in materials science and engineering, mechanical engineering, and aeronautical engineering are well-suited to participate in the project.

Student Requirements / Skills Needed

A background in materials or mechanical engineering is ideal for the project.

Research Interests

Fabrication of Temperature-sensitive Microcapsules for PFAS-free fire Fighting Foam Formulations

Topics of Potential Projects

Aqueous film-forming foams (AFFFs) containing perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acids (PFOS) (a.k.a PFAS) are used in fuel fire extinguishing operations. However, studies have shown that PFAS are detrimental to the environment and persist in the waterways and soil for significantly longer than silicone- and hydrocarbon-based surfactants. Despite many years of research in the military, academia, and industry, a replacement firefighting foam formulation has not been found. The objective of this project is to develop PFAS-free firefighting foam formulations, and this will be accomplished by combining 1) new custom-synthesized silicone surfactants that are formulated based on knowledge of their molecular properties to further lower surface tension with 2) encapsulated foam additives designed to release at specific moments to enhance foam stability while mitigating issues these additives cause. The student involved in this project will work on fabricating temperature-sensitive microcapsules and modifying their chemistry. Hence, they adhere firmly to the air/water interface, forming Pickering foams that are highly stable at high temperatures. The student will gain knowledge in the areas of particle characterization, emulsification, surface and interfacial tension measurements and optical microscopy.

Student Requirements / Skills Needed

Students pursuing BS on chemistry, materials science and engineering, chemical engineering, mechanical engineering should be able to work in the project.

Research Interests

Topical Elastase-Induced Murine AAA Severity Depends on Lysyl Oxidase Inhibition

Topics of Potential Projects

An abdominal aortic aneurysm (AAA) is a pathological dilation of the abdominal aorta defined by a 50% increase in diameter or a diameter greater than 3 cm in humans. While aneurysm severity is often defined based on measures of diameter and growth rate, a large variance in patient-to-patient outcomes suggests a complex disease pathophysiology. In this study, we will explore our ability to influence aneurysm growth in a topical elastase plus β-Aminopropionitrile (BAPN) mouse model by varying elastase concentration (0, 2.5, 5, and 10 mg/ml) and by altering the cross-linking capability of the tissue. To do so, we will assess both chronic and acute effects of elastase concentration using high frequency volumetric ultrasound. Additionally, we will assess the effects of BAPN by 1) removing it to restore the cross-linking capability of tissue after aneurysm formation and 2) adding it to animals with stable aneurysms to interrupt cross-linking.

Student Requirements / Skills Needed

Willingness to work with laboratory animals, interest in biomedical imaging

Research Interests

Urban Generative Modeling

Topics of Potential Projects

We are working on blending deep learning, procedural modeling, and computer vision in order to provide tools for helping to design better cities and neighborhood. Our recent tasks have been automatically modeling buildings in cities and all urban trees, from satellite data. After modeling, we then enable what-if generative tasks to tryout different altered urban scenarios. We also link the designs with weather, flooding, and air quality simulations. This is a very large collaborative project with many players.

Student Requirements / Skills Needed

Deep learning, computer graphics, and/or computer vision.

Research Interests

Benchmarking and understanding current quantum algorithms for optimization and chemistry

Topics of Potential Projects

Current quantum computers can implement limited yet potentially practical algorithms. In order to assess their performance, we can use empirical benchmarking techniques together with data analytics. This would help us realize the practical advantage these algorithms, executed in both quantum and classical hardware, might have against current state-of-the-art solution methods for combinatorial optimization and computational chemistry. Through open-source software intended for Machine Learning, we intend to verify the performance of this method. This project is in collaboration with Ph.D. students of SECQUOIA (https://secquoia.github.io/) and the Universities Space Research Association (USRA).

Student Requirements / Skills Needed

• Strong computational background in Python and/or Julia
• Knowledge of linear algebra, calculus, and optimization
• No requirements on Quantum Mechanics or Computing (yet preferable)
• Preferably knowledge in operations research or computational chemistry (not necessary)

Research Interests

Efficient and sustainable water technology

Topics of Potential Projects

Water and energy are tightly linked resources that must both become renewable for a successful future. However, today, water and energy resources are often in conflict with one another, especially related to impacts on electric grids. Further, advances in nanotechnology, material science and artificial intelligence allow for new avenues to improve the widespread implementation of desalination and water purification technology. This project aims to explore nanofabricated membranes, light-driven reactions, artificial intelligence control algorithms, and thermodynamic optimization of systems. Further projects include removing water vapor for atmospheric water harvesting or HVAC systems. The student will be responsible for fabricating membranes, building hydraulic systems, modeling thermal fluid phenomenon, analyzing data, or implementing control strategies in novel system configurations. More information here: www.warsinger.com

Student Requirements / Skills Needed

Applicants should have an interest in thermodynamics, water treatment, and sustainability. Applicants with experience in some (not all) of the following are preferred: experimental design and prototyping, manufacturing, Python, LabView, EES, MATLAB, 3D CAD Software, & Adobe Illustrator. Rising Juniors and Seniors are preferred.

Research Interests

The Healthcare Ergonomics and Analytics Lab (HEAL) focuses on linking the areas of musculoskeletal injuries, intervention design and assessment, and sensing-based exposure measurements with applications in improving the safety in healthcare environments for both patients and medical professionals. Approaches include sensor based physical and cognitive measurements to understand interactions between stakeholders in the healthcare industry, designing and assessing of interventions to reduce workload and improve human performance, developing objective and automated assessment metrics for simulation-based clinical training, as well as big data approaches to modeling human behaviors in healthcare delivery.

Topics of Potential Projects

Investigating teamwork through the use of Virtual Reality (VR) applications. VR gives researchers the opportunity to rapidly create scenarios while controlling all aspects of that scenario, which is difficult to do in real life simulation. It also allows for researchers to easily track performance metrics, giving us deeper insight into how various teams perform and what differences may be causing differing performance.

Student Requirements / Skills Needed

Human subject research experience is preferred. Prior experience with VR is helpful but not required. A strong interest in understanding how teams perform and how we can objectively model it is required.

Research Interests

Computational biology of infectious diseases, computational tools in education

Topics of Potential Projects

Development and analysis of computational models for a variety biomedical systems including viral and bacterial infections.

Student Requirements / Skills Needed

Prior coding experience and familiarity with ordinary differential equations

Research Interests

Catalysis, renewable fuels and chemicals

Topics of Potential Projects

A range of solid materials, including metals, oxides and zeolites, and carbons, are used as catalysts for upgrading shale gas and renewable biomass feedstocks into transportation fuels and chemicals. However, improved catalyst materials that are more active, selective and stable are needed to valorize shale gas and renewable biomass resources in commercially viable technologies. These aspects of catalytic performance are linked to their bulk and atomic-scale properties. This project will involve developing catalyst synthesis techniques, and applying state-of-the-art characterization methods for bulk and atomic structure (X-ray diffraction, spectroscopy, microscopy), and methods of catalyst evaluation. Please learn more about our projects and goals in the NSF Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR) at www.cistar.us.

Student Requirements / Skills Needed

General Chemistry Level Lab Experience

Research Interests

Early Detection of Pancreatic Cancer Through Deep Learning

Topics of Potential Projects

Pancreatic cancer remains one of the most fatal malignancies, at a 5-year overall survival rate of under 15%. The majority of patients receive a diagnosis at an advanced and incurable stage of the disease. Only a quarter of patients diagnosed with pancreatic cancer are eligible for curative-intent surgery. Importantly, some types of pancreatic cysts, often detected incidentally on imaging, are potential precursors of pancreatic cancer and thus offer a valuable window of opportunity for the early detection and prevention of pancreatic cancer. The risk of malignant progression varies widely depending on the type of pancreatic cyst, ranging from 0% for benign serous cystic neoplasm (SCN) to as high as 60% for intraductal papillary mucinous neoplasm (IPMN). Patients with pancreatic cysts undergo regular surveillance comprising imaging, physical examinations, and laboratory tests to identify high-risk lesions before they progress to malignancy. However, the accuracies of all existing diagnostic methods, including imaging, endoscopy, and cyst fluid analysis, remain limited. Given the substantial risks associated with pancreatic surgery, including life-threatening complications as well as potential development of pancreatogenic diabetes mellitus, recommendations for surgical resection are typically made by experts on a case-by-case basis, considering all available diagnostic modalities. The overall goal of this project is to leverage the potential of state-of-the-art deep learning methods to analyze medical image and clinical data, including blood parameters and demographic information, to improve risk assessment and enable early detection of malignant progression in patients with pancreatic cysts.

Based on previous knowledge and experience, the student will get the chance to work on an independent sub-project, investigating the utility of deep learning for screening and early cancer detection in specific patient populations at high and low relative risk of malignant progression of pancreatic cysts. These analyses have the potential to contribute to improved quality of care by defining which patients would profit from early surgical cyst removal while avoiding overtreatment of patients at very low risk of malignant progression.

Student Requirements / Skills Needed

We are searching for a highly motivated student with a background in computer science, electrical and computer engineering, (bio-)medicine, industrial engineering, statistics or related fields who will get the chance to contribute to various aspects of the project including data analysis, deep learning model development and evaluation, and summary and publication of results. An interest in interdisciplinary work with clinicians and engineers is critical for the success of this project. Experience in deep learning, computational medical image and/or data analysis as well as statistics (i.e. using Python and R) is a plus, but not a requirement.

Research Interests

Environment friendly design and life cycle engineering, applications of bio-based materials in manufacturing, fast and low-cost detection of pathogenic microorganisms, biomass thermo-chemical upgrading for liquid and gaseous fuel

Topics of Potential Projects

Project title: Sn-Bi Alloy: A More Environmentally Friendly Solder?
Research mentors: Carol A. Handwerker, Fu Zhao (Faculty), Tai-Yuan Huang (PhD student)

Solder plays an important role in electronics manufacturing. Traditionally, tin-lead (Sn-Pb) alloy was the most commonly used solder. Since lead is highly toxic, i.e., even a small amount can be detrimental to human health, Sn-Pb solder was largely phased out in the early 2000s. The dominant solders used globally are in the Sn-Ag-Cu alloy system, melting at approximately 217˚C. These solders are used to join components to circuit boards at temperatures as high as 250˚C. These high processing temperatures lead to high thermal stresses and large warpage of both components and boards, which combine to cause manufacturing defects. To eliminate these problems, researchers have been investigating lower melting temperature solders that can, therefore, be used at lower processing temperatures. The leading candidate is based on tin-bismuth (Sn-Bi) alloys which melt near 139˚C. It has been shown that adding small amounts of other metals (Ag, Cu, Sb, In, Ni) can improve the mechanical properties of these alloys to make them almost as reliability as Sn-Ag-Cu alloys.

This project will answer the question whether Sn-Bi solder has better environmental performance than Sn-Ag-Cu solder. The question is critical for the wide adoption of the new Sn-Bi solder as companies are facing ever increasing pressure to disclose the environmental footprint of their products. The widely used life cycle assessment methodology will be used and extended as very likely dynamic modeling is needed – current level of bismuth production may not meet the demand from wide adoption of Sn-Bi solder. Sn-Bi solder composition and performance data will be provided by an industrial partner. Currently there is no student working on the project, but we have a PhD student who has been working on life cycle assessment of rare earth elements and other minor metals. The REU student will be supervised by the two faculty members and the graduate student and focus on developing a life cycle inventory of bismuth production. Given the relatively low abundance of bismuth we expect that Sn-Bi recycling could become a key factor in determining its environmental performance. Therefore, the REU student will also conduct a literature survey to suggest possible recovery and recycling methods for Sn-Bi solder. Research findings will be communicated to our industrial partner and presented at a technical conference. The REU student has the opportunity to work in a dynamic interdisciplinary environment, and gain new perspective of system thinking.

Student Requirements / Skills Needed

Minimum qualifications

• introduction level thermodynamics
• general chemistry
• familiar with Excel
• good reading/writing skills

Desired qualifications

• basic understanding on life cycle thinking
• some exposure to mining and extractive metallurgy
• basic understanding on environmental toxicity

Research Interests

Innovating Turbines for Clean Aviation and Power Generation

Topics of Potential Projects

Are you ready to be at the forefront of a revolution? We are on the hunt for passionate, driven students eager to contribute to the future of clean energy. This is your chance to participate in a groundbreaking project focused on developing turbines for clean aviation and power generation.

In this endeavor, you will dive into the intricacies of designing state-of-the-art turbines. This is an opportunity to work hands-on in pioneering technologies that aim to redefine clean energy standards and sustainable aviation. Your role will not be confined to design alone. You will immerse yourself in advanced measurement techniques, testing, and rigorous analysis of these new turbines. Each day will be a new challenge, a new learning experience, and a step closer to making a tangible impact on the world. We are looking for visionaries who believe in a greener future. Whether your passion lies in engineering, environmental science, data analysis, or any field that intersects with our mission, your contribution will be vital.

By joining our team, you will: Work alongside leading experts in turbine technology and clean energy. Gain invaluable hands-on experience in cutting-edge design and testing methodologies. Contribute directly to projects that have the potential to shape the future of aviation and power generation.

Let's work together to create a cleaner, more sustainable world, one turbine at a time.

Student Requirements / Skills Needed

MatlabCAD

Research Interests

Soft Hydraulics

Topics of Potential Projects

Prof. Christov's Transport: Modeling, Numerics & Theory Laboratory (TMNT-Lab) at Purdue is developing a new theory of microscale fluid--structure interactions ("Soft Hydraulics", see https://arxiv.org/abs/2106.07164) to yield predictive models of the response of soft devices due to internal flow within. This involves understanding viscous flow, elastic deformation, and their coupling. The student will work with the Purdue professor and graduate student(s) to develop the theory of oscillatory fluid flows in deformable channels and tubes (such as microchannels in a lab-on-a-chip or blood vessels in the body). The work will combine mathematical derivations with numerical simulations.

Student Requirements / Skills Needed

1. Strong foundation in mathematics for engineering (partial differential equations, solution methods, numerical methods).
2. Strong background in mechanics (fluid, solid, or both).
3. Interest in fundamental mathematical and computational research in the engineering sciences. (We do not do experiments.)
4. Programming skills in MATLAB and/or Scientific Python.

Research Interests

Infectious diseases are a major cause of death and disability throughout the world. Research in the Linnes Lab focuses on using state of the art microfluidic and paperfluidic technologies to prevent, detect, and better understand the pathogenesis of these infectious diseases. The Linnes Laboratory at Purdue University has openings for Undergraduate Research Assistants to design and translate paper-based point-of-care diagnostic devices. These projects will enable the design and translation of paper-based diagnostic platforms for low-cost and robust device manufacturing at scale.

Topics of Potential Projects

1. Scale the manufacturing of paper-based point-of-care diagnostics devices using robotic automation tools such as 6-axis robots and Selective Compliance Assembly Robot Arm (SCARA) robots. The student will learn about robotic automation and develop strategies to reduce the number of manual interventions and errors during the fabrication process of paper-based diagnostic devices.
2. Optimize the power consumption and functionality of thin film heaters that are part of the point-of-care diagnostic devices fabricated in the lab. The student will optimize the heater design to lower the energy consumption, and develop a system capable of turning on the heaters using a smartphone as the power source. They will also have the opportunity to be involved in testing biological reactions and pathogen detection incubated using the heaters.

Student Requirements / Skills Needed

• Enrollment in engineering or technical field undergraduate degree
• Knowledge or interest on programming, electronics design, manufacturing and automation techniques
• The student should be highly motivated to work in a highly cooperative, interdisciplinary, and productive translational research environment
• The student should be resourceful and take initiative to succeed
• interest in health and diagnostic disease detection

Research Interests

Molecular modeling of surface and interfaces to understand and predict how solid catalysts promote desired reaction pathways.

Topics of Potential Projects

• use of first principles calculations to relate the atomic structure of metal alloy surfaces to the catalytic properties of the alloys for production of useful fuels from shale gas. Prediction of new catalysts for these reactions using kinetic theories and machine learning.
• first principles, molecular-level study of how solid oxide electrocatalysts convert ethane to ethylene. Formation of kinetic models of these reactions, and prediction of improved catalysts for the reaction.

Student Requirements / Skills Needed

• working knowledge of engineering thermodynamics
• interest in learning principles of surface kinetics and reactions
• interest in working with molecular simulation codes

Research Interests

Building an Infrastructure by Integrating Neighborhood Information across Data Sources

Topics of Potential Projects

This project aims to establish a robust and sustainable data infrastructure to integrate neighborhood-level data to assist and inform various local stakeholders. Drawing on local records, census data and other neighborhood-level data, the project will construct a unified database to capture crucial connections among the variety of neighborhood-level information sources. Project outcomes include integrated neighborhood-level data and software for querying and mining such datasets.

Student Requirements / Skills Needed

Knowledge about databases and data mining. Programming skills and experiences. Experiences with geo-spatial data are preferred but not required.

Research Interests

Data-driven insights into enzyme reaction catalysis for green chemistry

Topics of Potential Projects

Biocatalysis and metabolic engineering use enzymes to catalyze a series of transformations to yield a desired small molecule or natural product, e.g., commodity chemicals and pharmaceutical agents. Enzymatic processes are greener, more selective, more amenable to economic modeling compared to their chemocatalytic counterparts. Biochemical reactions are beginning to be cataloged into databases. As a result, this increasing availability of reaction corpora will enable the timely development of computational tools that exploit any underlying patterns within biochemical reactions for chemical manufacturing. By addressing methodological challenges at the interface between enzymology and applied machine learning, we will accelerate the development of biocatalytic processes to challenging synthetic targets. These computational tools will be experimentally tested through route scouting for complex natural product analog pharmaceutical drugs that are hard to synthesize chemically but could have facile biocatalytic alternatives.

Student Requirements / Skills Needed

Computer Science, Biochemistry

Research Interests

Reverse-engineering of new processor technologies for security

Topics of Potential Projects

This project focuses on new hardware features that Intel, AMD, Qualcomm, and Apple have introduced recently and examines their potential for security vulnerabilities.

Student Requirements / Skills Needed

C/C++ programming, understanding of x86 and arm assembly, familiarity with computer architecture

Research Interests

Topics in assessment and supporting students

Topics of Potential Projects

The project team has collected surveys from undergraduate engineering students at 14 U.S. universities. The purpose of the surveys is to look at how students are supported by their social networks and the opportunities they receive to develop professional skills.

Student Requirements / Skills Needed

Proficient with Excel. Able to create charts and graphs. Some data visualization skills would be helpful, not required.

Research Interests

This research project focuses on the critical need for rapid, deterministic, and reliable sense-communicate-compute-actuate loops in mission-critical autonomous systems. The core of the study involves an extensive measurement analysis of existing operational Wi-Fi 6 and 5G networks. The aim is to design and implement a reconfiguration solution tailored for various wireless network protocols. This solution will be underpinned by theoretically sound optimization techniques, with a special emphasis on ensuring performance determinism and high reliability in autonomous systems operations.

Topics of Potential Projects

The aim of the project is to develop an autonomous experimental platform that enables automated design of experiments (DoE) implementation for crystallization and integrated crystallization-filtration-drying systems, for data generation for digital twin development. Data received from an array of advanced process analytical technologies will be processes in real time and used in an iterative model-based experimental design for automated model development.

Student Requirements / Skills Needed

• Foundational knowledge acquired through coursework in digital communications and wireless networks; additional coursework in robot control is highly advantageous.
• Proficiency in programming languages such as C, C++, and Python, with an emphasis on their application in network communication and system control contexts.

Research Interests

Ground improvement, foundation engineering, retaining structures, foundation instrumentation, soil behavior

Topics of Potential Projects

Response of bridge foundations to loading, Use of digital image technique to study the behavior of foundations tested in a calibration chamber, instrumentation of retaining structures and foundations

Student Requirements / Skills Needed

Knowledge of geotechnical engineering

Research Interests

Weldon School of Biomedical Engineering Public health data science; public health systems engineering; systems optimization and control; compressive population health

Topics of Potential Projects

Latin America has been plagued by the mosquito species Aedes aegypti since the 1970s, introducing diseases such as Dengue (DENV), Chikungunya (CHIKV), and Zika (ZIKV). In this study, we will utilize data from the established surveillance system to analyze sociodemographic and environmental factors and their contribution to DENV, ZIKV, and CHIKV risk, with the purpose of informing epidemic prevention. In addition, we will study the community logistics and implementation issues regarding the environmental health surveillance and develop stochastic dynamic programming models and corresponding solution methods to cost-Effective profiling of prevalence for these diseases.

Student Requirements / Skills Needed

• already had courses statistical data modeling
• basic R/Python or Matlab coding.
• good experience on statistical and data mining toolboxes, e.g., Scikit-Learn in Python.
• preferable, some experience on analyzing spatial data for statistical correlation
• ideally, majored in mathematics, computer science, Industrial and systems engineering.

Research Interests

Machine Learning to Quantify Microstructural Patterns in Semiconductors

Topics of Potential Projects

This project will focus on using and developing machine learning-based algorithms to automatically identify microstructural patterns in Sn-Bi and other important alloys used interconnects in semiconductors.

Student Requirements / Skills Needed

Strong background in MSE and structure-property relationships . Experience with machine learning codes and programming is a plus.

Research Interests

Machine Learning for Analysis of Microstructures

Topics of Potential Projects

The goal of this project is to develop a methodology for automatically identifying and classifying various types of microstructures in metallic materials. The student will work on analyzing and classifying images of microstructures, from scanning electron microscopy and x-ray microtomography. Machine learning codes used in the Chawla Research Group will be used.

Student Requirements / Skills Needed

Background in Materials Science and Engineering. Familiarity with programming and Python is a plus. Should be independent and enthusiastic. O Professor Chawla nasceu no Brasil e fala portugues.

Research Interests

New materials for photonic integrated circuits

Topics of Potential Projects

Transmitting and processing information traditionally involves electronic circuits, which use electrons to do the job. The research in this project uses photons instead, which are individual units of light. These photons have some properties that make them ideal for handling information. They can move fast and carry a lot of data. However, there are still some challenges to overcome when using light for these circuits, like directing it where we want it to go, preventing it from interfering with other light, and switching it on and off when needed.

Student Requirements / Skills Needed

Majors: We're particularly interested in ECE, MSE, and ME majors; all College of Engineering majors can apply

Requirements: Experience with programming in Python, C/C++, and/or MATLAB

Desired experience: Enthusiasm for scientific programming. Understanding of electromagnetism (e.g., it's helpful to have previously taken ECE 30411).

Academic Years Eligible: Juniors and seniors with the desired experience will be preferred, but all undergraduates are also eligible to apply.

Research Interests

Ferroic Quantum Materials and Devices

Topics of Potential Projects

Electron-electron correlations in solid-state platforms are at the heart of stabilizing exotic many-body ground states ranging from superconductors to topological magnets. In this project, we will design novel quantum materials and devices exploiting correlated ferroic interactions, ranging from negative capacitance enabled superconductors with enhanced operating temperatures to topological magnet-based probabilistic bits/spintronic memory for accelerating applications in artificial intelligence and machine learning. Depending on student's interest, there will also be scope for performing experiments on probing above-mentioned materials and phenomena via Nitrogen Vacancy-based quantum sensors.

Student Requirements / Skills Needed

analytical and/or numerical experience with quantum mechanics and many-body quantum theory techniques

Research Interests

Catalysis, renewable fuels and chemicals

Topics of Potential Projects

A range of solid materials, including metals, oxides and zeolites, and carbons, are used as catalysts for upgrading shale gas and renewable biomass feedstocks into transportation fuels and chemicals. However, improved catalyst materials that are more active, selective and stable are needed to valorize shale gas and renewable biomass resources in commercially viable technologies. These aspects of catalytic performance are linked to their bulk and atomic-scale properties. This project will involve developing catalyst synthesis techniques, and applying state-of-the-art characterization methods for bulk and atomic structure (X-ray diffraction, spectroscopy, microscopy), and methods of catalyst evaluation. Please learn more about our projects and goals in the NSF Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR) at www.cistar.us.

Student Requirements / Skills Needed

General Chemistry Level Lab Experience

Research Interests

Development of a solution processed Cu(In,Ga)(S,Se)2 base layer for use in perovksite-CIGS tandem solar cells.

Topics of Potential Projects

Student would work with a graduate student on tuning the processing conditions of solution-processed CIGS thin films to control the morphology, bandgap, and device properties of the CIGS film. Student would collaborate with other research groups within the department to construct tandem devices and ensure compatibility of the CIGS layer with the perovskite top layer. This will include selecting different buffer layers and tuning their properties, working on band gap alignments, and working on physical adhesion of the layers.

Student Requirements / Skills Needed

This project requires manipulating multiple factors and measuring their effect on the materials. Successful students will employ effective experimental design, be thorough with their data collection, and collaborate well with others in the group.

Research Interests

Fabrication of Solution Processed Thin Films of Chalcogenide Perovskites

Topics of Potential Projects

Growing technological advancements necessitate the development of versatile semiconductor materials capable of addressing a myriad of challenges. These materials must exhibit robust stability, abundance in nature, environment friendly and tunable properties that can be tailored towards diverse applications such as transistor, photovoltaics, thermoelectrics, LEDs, and more. They should also facilitate efficient and high-throughput synthesis. One such emerging class of material that aligns with these requisites is chalcogenide perovskites, especially in the context of photovoltaics. Chalcogenide perovskites have shown to exhibit superior stability and abundance in nature. They offer interesting optoelectronic properties such as tunable bandgap, high absorption coefficients, defect tolerance and high dielectric constant. This project is focused on developing a versatile solution-processing approach for the fabrication of thin films of chalcogenide perovskites. Solution processing can enable roll to roll processing of semiconductors similar to current day newspaper printing at moderate temperature and pressure conditions, hence improving the capability and application of these materials. Students will be working with a diverse group of graduate students coming from various corners of the globe. This offers a unique opportunity to acquire hands-on experience in material synthesis and delve into advanced characterization techniques, including XRD, Raman, and XRF. This project aims to impart comprehensive knowledge of semiconductor functionalities and the working principles of photovoltaic systems to the students.

Student Requirements / Skills Needed

Experience with handling chemicals, glassware and general laboratory practices.

Research Interests

Planning and design of sustainable logistics systems

Topics of Potential Projects

This project aims at designing practical and efficient methods to solve modern supply chain challenges. This includes leveraging data to enhance decision-making in logistics systems while considering the human element in the loop and addressing environmental considerations for sustainability.

Student Requirements / Skills Needed

Required: Basics knowledge of linear and integer programming. Basic knowledge of a programming language such as Python, Julia, etc.

Preferred: experience with an optimization solver such as Gurobi or CPLEX.

Research Interests

Development and Analysis of Heat Pumps with Environmentally Friendly Working Fluids

Topics of Potential Projects

As buildings consume approximately 40% of US energy, increasing their efficiency while also ensuring they use working fluids that are environmentally friendly is a high priority. To support this effort, this position will focus on the design and characterization of heat pumps using environmentally friendly working fluids. Consisting of both experimental and numerical analysis, this position will entail the analysis of heat pump systems, their components (i.e., compressors and heat exchangers) and the working fluids they utilize (i.e., refrigerants and compressor lubricants). The heat pumps being investigated are for both residential and light commercial applications, and the specific tasks are as follows:

• Experimental characterization of compressor and heat exchanger performance, as well as thermo-physical properties of new working fluids.
• Numerical characterization of the experimental results and input into heat pump system models to predict their performance in a range of applications and operation conditions.

In addition to technical content, there will be opportunities to collaborate with other students and research groups in a range of thermal systems applications.

Student Requirements / Skills Needed

Thermal systems analysis Numerical (Python, EES, Fluid property characterization) simulation Experimental test stand development and operation, data acquisition, analysis, etc. Necessary coursework: Thermodynamics, Heat & Mass Transfer, Fluid Mechanics

Research Interests

• Geomechanics
• Computational geomechanics
• Offshore foundations
• Renewable energy infrastructure
• Material point method
• Digital image correlation

Topics of Potential Projects

• Geomechanics
• Computational geomechanics
• Offshore foundations
• Renewable energy infrastructure
• Material point method
• Digital image correlation

Student Requirements / Skills Needed

Some coding ability would be helpful. Some knowledge of instrumentation would also be helpful. Basic knowledge of soil mechanics is required.

Research Interests

Machine learning, control systems, power systems

Topics of Potential Projects

Learning, control, and optimization for power and energy systems

Student Requirements / Skills Needed

Familiarity with control systems/power systems and machine learning, MATLAB, Python.

Research Interests

Topics of Potential Projects

1. Investigations into the dynamics of protein signaling in neurons and cardiac cells
2. Development of point-of-care assays for detection of disease
3. Labeling new protein synthesis to investigate disease progression

Student Requirements / Skills Needed

Experience with microfluidic systems, molecular or synthetic biology, proteomics, or python programing or control systems.

Research Interests

Mechanics of Materials; Fracture Mechanics; Biomechanics

Topics of Potential Projects

• Topic 1: Fracture of assembled structures. Using LEGOs a building blocks investigate the fracture response of built-up structures and investigate effects of crack tip constraint on the effect of specimen size on fracture.
• Topic 2: 3D printing bone structures for visualization of microscale damage in bone. Transfer 3D medical images to 3D print files, manufacture specimens for visualization of bone damage.
• Topic 3: Create flat vault structures based on the Penrose tiling. Design and manufacture (3D print), and by experiments, determine the mechanical properties of such systems.

Student Requirements / Skills Needed

Students ideally should have taken courses in mechanics of materials, finite element analysis. Interest in working with materials, CAD is useful.

Research Interests

Computational nanotechnology, molecular chemistry, and machine learning

Topics of Potential Projects

The Kubis group is part of the Elmore Family School of Electrical and Computer Engineering at Purdue University. The group’s work centers on computational nanotechnology (support for semiconductor companies such as Intel, TSMC, Samsung, etc.), molecular and quantum chemistry (support for Corteva, Dow and Merck), and AI-supported quantum transport simulation tool development (support for Silvaco Inc.). Students with interest in computational quantum mechanics, semiconductor materials, molecular reactions, high performance computing or software development will find great overlap with the projects of the Kubis group.

Student Requirements / Skills Needed

Interested students should bring some experience in at least one of the following areas:

• Semiconductor material modeling (e.g. DFT or similar methods);
• Nanodevice modeling (e.g. quantum transport methods);
• Object oriented programming (e.g. C++ or Python);
• High performance computation (using 1000s of CPUs);
• Machine learning models (e.g. supervised learning models);

Research Interests

Towards Machine Learning for Control of Physical Systems

Topics of Potential Projects

Machine learning and AI techniques (such as reinforcement learning) have had some high profile successes in recent years, but applications of such techniques to control of real-world large-scale systems remains limited. Many reasons account for this, including data hunger of these techniques, lack of robustness or generalization guarantees, and the need for safety. The high level aim of this project is to explore integration of advances in machine learning (large language models, deep reinforcement learning, graph neural networks) with concepts from systems theory to address some of these reasons. Both experimental and theoretical projects are available depending on the background of the student.

Student Requirements / Skills Needed

An interest and some background in machine learning and control theory, python

Research Interests

Autonomous Uncrewed Aerial Vehicles

Topics of Potential Projects

This project will program an autonomous uncrewed aerial vehicle (UAV) to navigate in a maze. The UAV needs to use the onboard sensors to build a map of the maze, determine an appropriate route, and move from the entrance to the exit.

Student Requirements / Skills Needed

computer programming

Research Interests

Digital design of crystallization systems

Topics of Potential Projects

The aim of the project is to develop an autonomous experimental platform that enables automated design of experiments (DoE) implementation for crystallization and integrated crystallization-filtration-drying systems, for data generation for digital twin development. Data received from an array of advanced process analytical technologies will be processes in real time and used in an iterative model-based experimental design for automated model development.

Student Requirements / Skills Needed

Programing in matlab, python, labview is desirable