Find Academic Supervisors

Zongyi Li is a Research Fellow at Massachusetts Institute of Technology , hosted by Kaiming He. They are currently pursuing a Ph.D. in Computing and Mathematical Sciences at Caltech (2019-2025), mentored by Anima Anandkumar and Andrew Stuart. Ph.D. candidate: Computing and Mathematical Sciences, Caltech (2019-2025) B.Sc. in Computer Science and Mathematics with a Jazz minor from Washington University in St. Louis (2015-2019) They focus on Neural Operators for learning solution operators in Partial Differential Equations (PDEs) , particularly in fluid mechanics and earth science . Their work models physical simulations with chaotic behaviors and complex geometries, showing applications in weather forecasting , carbon storage , and aerodynamics simulation . Publications emphasize resolution-invariant models , chaotic systems , and zero-shot super-resolution capabilities. Their research combines Fourier analysis , graph networks , and physics-informed loss functions to achieve state-of-the-art performance in PDE solving with up to 1000x speedup over traditional solvers. Fellowships: Kortschak Scholarship PIMCO Fellowship Amazon AI4Science Fellowship Nvidia Fellowship MIT Novo Nordisk AI Fellowship Code & Open-Source: Co-developer of the NeuralOperator library Implementations for Fourier Neural Operators , Graph Neural Operators , and Tensorized Neural Operators Media Recognition: Quanta Magazine MIT Tech Review NVIDIA Features Towards Data Science

• Machine Learning
• Scientific Computing
• Partial Differential Equations
• +5 more

Benoit Forget is the Korea Electric Power Professor of Nuclear Engineering and the Department Head of Nuclear Science and Engineering at MIT. He joined MIT in 2008 and leads the MIT Computational Reactor Physics Group (CRPG), which focuses on advancing computational methods for reactor simulation. His research spans Monte Carlo and deterministic transport methods, multiphysics coupling, and uncertainty quantification. He co-developed OpenMC and OpenMOC, open-source tools for reactor analysis. Forget holds a PhD from Georgia Tech and has received awards including the 2013 Landis Young Member Engineering Achievement Award. He teaches courses such as 22.05 Neutron Science and Reactor Physics, and actively contributes to MIT’s computational science initiatives. Educations: PhD in Nuclear Engineering (Georgia Tech, 2006), MS and BS in Energy Engineering (École Polytechnique de Montréal, 2003). Research Interests: Computational reactor physics, radiative transport, high-performance computing, Monte Carlo and deterministic methods, multiphysics coupling, nuclear data uncertainty. Labs/Teams: MIT Computational Reactor Physics Group (CRPG), Consortium for Advanced Simulation of Light Water Reactors (CASL).

• Computational Transport Theory
• Reactor Physics
• Nuclear Fuel Cycle
• +4 more

Phillip J. Ansell is an Associate Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He directs the Center for Sustainable Aviation and the Center for High-Efficiency Electrical Technologies for Aircraft. His academic positions include Assistant Professor (2015–2021) and current role as Associate Professor since 2021. He teaches courses such as AE 416 (Applied Aerodynamics), AE 419 (Aircraft Flight Mechanics), and AE 515 (Wing Theory). Education: BS, The Pennsylvania State University, Aerospace Engineering, 2008 MS, UIUC, Aerospace Engineering, 2010 PhD, UIUC, Aerospace Engineering, 2013 Research Interests: Focuses on applied aerodynamics, sustainable aviation, distributed propulsion, flow control, and aircraft electrification. His work integrates experimental fluid mechanics and computational models to advance aviation sustainability. Key projects include hydrogen propulsion systems, cryogenics in aviation, and unsteady aerodynamics for rotorcraft. Research Contributions: Authored/co-authored books like Aircraft Cryogenics (Springer, 2024). His articles address sustainable aviation frameworks, hydrogen-electric propulsion, and high-lift aerodynamics. Recent trends emphasize decarbonization pathways and system-of-systems analysis. Awards & Honors: Dean's Award for Excellence in Research (2025) NASA Innovative Advanced Concepts Fellow (2025) AIAA Associate Fellow (2024) Forbes 30 Under 30 (2016) Advising & Grants: Advises graduate students on propulsion and aerodynamics. Secured grants from AFOSR, ARO, and NASA. Active in AIAA committees, including Electrified Aircraft Technology Technical Committee (Chair, 2020–2023). Labs & Teams: Leads the Aerodynamics and Unsteady Flows Research Group, using UIUC’s wind tunnel facilities. Collaborates on projects like the Five Circles of Sustainable Aviation framework and cryogenic propulsion systems.

• Applied aerodynamics
• Sustainable aviation
• Distributed propulsion
• +7 more

Prof. Dan Jiao is the Synopsys Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School. She leads the Rapid-Heterogeneous Integration (Rapid-HI) Design Institute and serves as Editor-in-Chief of the IEEE Journal on Multiscale and Multiphysics Computational Techniques. Her research focuses on computational electromagnetics, multiphysics modeling, and AI-driven design automation for advanced integrated circuits and quantum systems. She has held academic positions since 2005, progressing from Assistant to Full Professor, and has extensive industry experience at Intel Corporation (2001–2005). Education: PhD in Electrical Engineering, University of Illinois at Urbana-Champaign (2001) Senior Staff Engineer at Intel Corporation (2001–2005) Research Interests: Fast numerical methods for large-scale electromagnetic analysis AI/ML integration in design automation (EDA/MDA) Quantum circuits and spin qubit systems Heterogeneous integration and advanced packaging Multiphysics co-simulation for nano-scale devices Signal/power integrity in high-speed systems Key Projects: Leads the NSTC AIDRFIC program (first NSTC R&D Jump Start project), the DARPA NGMM Rapid-HI Design Institute, and the GENIE-RFIC generative design tool initiative. Also directs the Consortium for Electromagnetic Science and Technology. Awards & Honors: 2022 ACES Computational Electromagnetics Award IEEE Fellow (2016) Intel Outstanding Researcher Award (2019) MTT-S Distinguished Microwave Lecturer (2020–2023) 2013 Schelkunoff Prize Paper Award Advising & Grants: Advised over 30 PhD/master's students and led projects funded by NSF, DARPA, Intel, SRC, and industry partnerships. Key grants include NSF CAREER (2008), ONR Young Investigator (2006), and multiple industry-sponsored initiatives. Labs & Teams: Rapid-HI Design Institute (DARPA NGMM) Quantum device co-design group Multiphysics modeling team

• Computational Electromagnetics
• Computational Multiphysics
• Electronic Design Automation (EDA)
• +8 more

Yuri Bazilevs is the E. Paul Sorensen Professor of Engineering at Brown University's School of Engineering and Co-Director of the Mechanics of Undersea Science and Engineering Center. His research focuses on computational mechanics, isogeometric analysis, fluid-structure interaction, and high-performance computing. Prior to Brown, he held positions at UC San Diego, where he advanced to Full Professor in 2014 after a rapid tenure. He earned his PhD in 2006 and postdoc training in computational engineering at UT Austin's ICES. Research interests span computational fluid dynamics, solid mechanics, and advanced discretization methods like isogeometric analysis (IGA) and meshfree approaches. He has developed novel formulations for complex phenomena such as underwater explosions, composite material failure, and hypersonic flow dynamics. His work integrates cutting-edge numerical methods with practical engineering applications in aerospace, energy, and biomedical systems. Recent publications highlight advancements in IGA for architected materials, RKPM-based crack modeling, and stabilized formulations for compressible flows. His contributions bridge theoretical mechanics with computational innovation, addressing challenges in multiphysics coupling and large-scale simulations. Collaborations span academia and industry, emphasizing practical validation and real-world impact. Bazilevs' expertise includes variational multiscale methods, peridynamics for fracture mechanics, and immersive particle methods for fluid-structure interaction. His work has been applied to wind turbine aerodynamics, gas turbine optimization, and cardiovascular flow analysis. He actively contributes to computational infrastructure development, such as the tIGAr software framework for IGA automation.

• Computational Mechanics
• Isogeometric Analysis
• Fluid-Structure Interaction
• +5 more

David Warsinger is an Assistant Professor of Mechanical Engineering at Purdue University's College of Engineering, located in West Lafayette, IN. He holds a Ph.D. from MIT and degrees from Cornell University. His research focuses on thermofluids, nanotechnology, and membrane science applied to water treatment, energy systems, and sustainable technologies. Key areas include desalination innovation, the water-food-energy nexus, and HVAC efficiency. He leads the Warsinger Lab, which develops advanced membrane materials, dehumidification systems, and renewable energy integration for desalination. Education: Ph.D., Mechanical Engineering (MIT), M.Eng. and B.S. (Cornell University). Awards include the MIT Outstanding UROP Mentor (2015), UCOWR Dissertation Award (2016), and Purdue's Early Career Teaching Award (2025). His lab collaborates on grants from DOE, NSF, and industry, with recent focus on batch reverse osmosis, solar desalination, and membrane-based HVAC systems. Research emphasizes high-impact applications like atmospheric water harvesting, photocatalytic air purification, and CO₂ removal for space exploration. The lab's capabilities include membrane testing, multiphysics modeling, and partnerships with ARUP for sustainable building design. Current projects include NSF-funded ReNEW initiatives and innovations in wave-powered desalination. Awards include over $4M in grants, including a 2025 $75k Showalter Grant and a 2022 DOE $2.4M award. His lab publishes in top journals and presents at ASME, NAMS, and international conferences. Undergraduate and graduate training emphasizes diversity and entrepreneurship, with alumni securing roles at top universities and companies like SpaceX.

• Desalination & Water Treatment
• Water-Food-Energy Nexus
• Thermofluids
• +5 more

Christopher Bailey is a Professor of Advanced Semiconductor Packaging and Director of the Centre for Advanced Semiconductor Packaging at Arizona State University (ASU). He previously served as Professor of Computational Mechanics & Reliability and Associate Dean for Research at the University of Greenwich, UK. At ASU, he leads research on advanced semiconductor packaging, including roles as Principal Investigator (PI) and Co-Investigator (Co-I) on major projects such as the SRC-funded Thermo-Mechanical Modelling and US Chips Act initiatives (e.g., SWAP-Hub, SHIELD, ITSI). His research focuses on semiconductor packaging reliability, thermal management, co-design methodologies, and multiphysics modeling. Education: MBA (Technology Management), Open University, UK PhD, Thames Polytechnic, UK Research Interests: Advanced Semiconductor Packaging Thermal Management Solutions Co-Design and Multiphysics Modeling Reliability of Electronic Components His work integrates computational mechanics, materials science, and engineering to address challenges in high-reliability electronics. Recent projects emphasize predictive modeling for semiconductor packaging failures under thermal-mechanical stress. Awards: IEEE Region 8 Europe Award (2024) IEEE David Feldman Award (2022) Visiting Professorships at IIT Kharagpur (2018/2022) and Hong Kong (2018) Service & Leadership: Former President of IEEE Electronics Packaging Society (2020–2021) Associate Editor for IEEE Transactions on Components, Packaging, and Manufacturing Technology Conference Leadership (e.g., Program Chair for IEEE PAINE 2024) He has secured over $40M in research funding and authored 400+ archival papers, with expertise spanning industry collaborations (e.g., BAe Systems, Rolls Royce) and government advisory roles (EPSRC Peer Review College, UK Research Excellence Framework).

• Advanced Semiconductor Packaging
• Thermal Management
• Co-Design and Multiphysics Modelling
• +3 more

Dr. Raj M. Manglik is a Professor of Mechanical & Materials Engineering and Director of the Thermal-Fluids & Thermal Processing Laboratory at the University of Cincinnati. His research focuses on interfacial phenomena, molecular dynamics, heat transfer enhancement, and thermal systems design. He holds a Ph.D. from Rensselaer Polytechnic Institute, an M.S. from Iowa State University, and a B.Tech. from Indian Institute of Technology Madras. Dr. Manglik has secured over $9.5M in grants, including recent projects on advanced dry-cooling systems, 3D printed ceramic heat exchangers, and thermal energy storage. His work spans experimental and computational studies of heat exchangers, non-Newtonian fluids, and phase-change materials. He has authored numerous peer-reviewed publications and co-edited books such as Principles of Heat Transfer . Awards include the ASME Heat Transfer Memorial Award (2016), ASME James Harry Potter Gold Medal (2018), and multiple university teaching and research accolades. His lab explores topics like boiling heat transfer, drop impact dynamics, and energy-water nexus solutions in power plants.

• Heat Transfer
• Thermal Engineering
• Fluid Dynamics
• +7 more

Jonathan Freund is Professor of Mechanical Science and Engineering and Aerospace Engineering at the University of Illinois at Urbana-Champaign, holding the Donald Biggar Willett Professorship since 2016. He serves as Head of Aerospace Engineering (2020-present) and is Co-Director of the Center for Exascale-enabled Scramjet Design (CEESD). His academic journey began with all three degrees in Mechanical Engineering from Stanford University (B.S. 1991, M.S. 1992, Ph.D. 1998), followed by faculty positions at UCLA (1997-2001) before joining UIUC. Freund's research spans fluid mechanics with applications in biomedical systems, aeroacoustics, and materials science. His work focuses on computational modeling of cellular blood flow, jet noise control, plasma-coupled combustion, uncertainty quantification, and nanoscale material processing. He develops advanced simulation tools to investigate phenomena ranging from atomically thin liquid films to spacecraft propulsion systems. His laboratory leverages high-performance computing to solve complex multiphysics problems requiring exascale capabilities. Analysis of his recent publications reveals a strong emphasis on computational fluid dynamics applied to biological systems (35%), aeroacoustics and jet noise (25%), materials processing at nanoscale (20%), and uncertainty quantification methods (20%). His work consistently bridges fundamental fluid mechanics with practical engineering applications, particularly in medical technologies and advanced propulsion systems. Donald Biggar Willett Professor (2016-present) Kritzer Faculty Scholar (2011-2016) Fellow of the American Physical Society (2011) Campus Excellence in Faculty Mentoring Award (2017) APS DFD Gallery of Fluid Motion Winner (2000) Associate Fellow of AIAA (2012) Freund has advised numerous graduate students and received multiple teaching honors including the Engineering Council Award for Excellence in Advising (2008, 2012) and repeated recognition on the List of Excellent Teachers. His research has been supported by agencies including the Department of Energy's National Nuclear Security Administration. He leads the CEESD center which develops physics-faithful predictive simulations for scramjet design using advanced high-temperature composite materials.

• Fluid Mechanics
• Biomedical Fluid Dynamics
• Aerodynamic Sound
• +4 more

Dorin Boldor holds the Charles P. Siess Jr. Professorship at Louisiana State University's Department of Biological and Agricultural Engineering. His research specializes in microwave heating, bioprocessing, and bioenergy systems. He teaches BE 4303: Engineering Properties of Biological Materials and holds a Ph.D. from North Carolina State University. Research encompasses microwave-assisted biomass conversion, pyrolysis kinetics, and sustainable fuel production, with emphasis on reactor design and catalytic processes. Recent publications (2022-2025) explore lignin pyrolysis, biodiesel co-formulants, and oil containment technologies, reflecting applied engineering solutions for energy and environmental challenges.

• Microwave heating
• Bioprocessing
• Bioenergy

Professor Wang Shiren is a faculty member in the Department of Industrial & Systems Engineering at Texas A&M University, holding the Jill & Charles F. Milstead '60 Faculty Fellowship. He is affiliated with Biomedical Engineering and Materials Science & Engineering. His research focuses on additive manufacturing, bio/nano-manufacturing, brain-inspired AI, and decarbonization. He leads the Manufacturing Intelligence and Nanotechnology Innovation (MINI) Lab, emphasizing sustainable manufacturing and commercialization. Education: Ph.D. in Industrial & Manufacturing Engineering from Florida State University (2006) Research interests span advanced materials, energy-efficient manufacturing, and AI integration. Recent work includes low-carbon ceramics, thermoelectric materials, and nanozyme-based therapies. Over 100 peer-reviewed publications demonstrate expertise in additive manufacturing, nanocomposites, and energy harvesting. Awards include NSF CAREER Award (2010-15) and multiple faculty fellowships. Awards: NSF CAREER Award, AFOSR Fellowship, Texas A&M TEES Fellowship, and 3M Non-tenured Award. Grants and collaborations focus on AI-driven manufacturing, eco-friendly processes, and medical device innovation. The MINI Lab develops smart materials and sustainable solutions for industrial and biomedical applications. Labs/Teams: MINI Lab at Texas A&M, specializing in nanotechnology and manufacturing intelligence.

• Additive Manufacturing
• Bio/nano-manufacturing
• Brain-inspired Artificial Intelligence
• +6 more

Ben Lindley is an Assistant Professor of Nuclear Engineering and Engineering Physics at the University of Wisconsin-Madison since 2020. He leads research in advanced reactor design, reactor physics, and integrated energy systems with a focus on cost reduction, nuclear-solar co-generation, and multiphysics modeling. His work spans computational methods development, safety analysis, and fuel cycle optimization, supported by DOE grants and collaborations with Argonne National Laboratory. Education: PhD in Nuclear Engineering (Cambridge, 2014), MEng & BA in Mechanical Engineering (Cambridge, 2011) Affiliations: Joint faculty appointment at Argonne National Laboratory His research explores nuclear reactor design , flexible operation (load-following, thermal storage), and economic viability of advanced reactors. Recent publications highlight innovations in microreactors, molten salt systems, and fusion-fission hybrids, with methodological advances in reinforcement learning for reactor control and open architecture design . Key article trends include: Advanced reactor cost reduction Nuclear-solar synergy Accident-tolerant fuel analysis Fusion energy commercialization Uncertainty quantification High-fidelity computational modeling Scientific Awards : 2021 ICONE21 Best Paper Award 2011 Babcock Award Runner-Up IET Bill Kerss Scholarship ANS 40 Under 40 Cambridge Rex Moir Prize Ben leads the RETI Lab (reti.ep.wisc.edu), mentoring graduate students through courses like Nuclear Reactor Theory (NE405) and advising on advanced reactor projects with national laboratories.

• Nuclear Reactor Design
• Advanced Reactors
• Integrated Energy Systems
• +4 more

Xiaozhe Hu is a full-time Professor in the Department of Mathematics at Tufts University since July 2024. Previously held positions include Associate Professor (2019-2024) and Assistant Professor (2014-2019) at Tufts, and Adjunct Associate Professor (2020-2022) at the University of Bergen, Norway. Education : PhD in Computational Mathematics (Zhejiang University, 2009); BS in Information and Computer Science (Zhejiang University, 2004) His research focuses on scientific computing and numerical analysis , particularly: Development of adaptive and parallel numerical methods for PDEs and graph problems Multigrid/multilevel solvers for large-scale coupled systems Quantum algorithms and spectral graph theory Applications in poromechanics , reservoir simulation , and bioinformatics Recent publications demonstrate expertise in preconditioning techniques for Biot’s model, meshless methods for fluid-structure interaction, and data-driven discretization approaches . Awards include the Reimann-Louville Award (2016) and outstanding PhD graduate recognition (Zhejiang Province, 2009). PhD Students : Junyuan Lin (Loyola Marymount), Peter Ohm (RIKEN), Casey Cavanaugh (LSU), Kaiyi Wu, Eoghan O'Keefe Master Students : Charles Colley (Purdue PhD), Yue Shen (Florida State PhD), Samuel Rabinowitz, Phong Huang, Samuel Hocking Co-organizer of the Computational and Applied Mathematics Seminar and contributor to open-source HAZmath finite element library.

• Scientific Computing
• Numerical Analysis
• Multigrid Methods
• +7 more

Dr. Jason Hicken is an Associate Professor in the Mechanical, Aerospace, and Nuclear Engineering Department at Rensselaer Polytechnic Institute (RPI), and co-director of the Rensselaer Augmented and Virtual Environment. His research focuses on computational fluid dynamics, aerodynamic shape optimization, and simulation-based design. He holds a Ph.D. in Aerospace Engineering from the University of Toronto Institute for Aerospace Studies (2009), with postdoctoral training at Stanford University. Notable awards include the AFOSR Young Investigator Award (2015) and NSF CAREER Award (2016). His research interests span high-order numerical methods, entropy-stable discretizations, and optimization techniques for complex systems. He has contributed to advancing finite-difference operators, summation-by-parts schemes, and multi-disciplinary design optimization. His work bridges computational engineering and applied mathematics, addressing challenges in fluid dynamics, thermal systems, and aerospace applications. His lab, the Optimal Design Lab (http://www.optimaldesignlab.com/), develops innovative tools for engineering design optimization. Key achievements include developing entropy-stable numerical frameworks and integrating machine learning techniques for preconditioning in advection-dominated flows. His research has been applied to electric motor design, thermal management systems, and additive manufacturing. Awards recognize his contributions to foundational methods in computational engineering and aerospace optimization.

• Computational Fluid Dynamics
• Aerodynamic Shape Optimization
• Simulation-Based Design
• +3 more

Tuhin Das is a Professor of Mechanical and Aerospace Engineering at the University of Central Florida (UCF), where he has been since 2011. He holds a B.Tech from IIT Kharagpur (1997), and M.S. and Ph.D. from Michigan State University (2000, 2002). His research focuses on dynamics and controls applied to energy systems (fuel cells, wind energy), robotics (mobile/biomimetic systems), and sensing (compressive sensing). His work is funded by NSF, ONR, Siemens Energy, and ARPA-E. He is an ASME Fellow and co-founder of the Energy Systems Technical Committee. Education: Bachelor of Technology in Mechanical Engineering, Indian Institute of Technology, Kharagpur (1997) M.S. and Ph.D. in Mechanical Engineering, Michigan State University (2000, 2002) Research Interests: Energy systems (wind turbines, hybrid fuel cells) Nonlinear dynamics and control Robotics and mobile systems Advanced modeling/simulation techniques Phase-space kinematics and Hamiltonian systems Recent Work Trends: Recent publications emphasize offshore wind energy systems, floating platform dynamics, and advanced control strategies for energy systems. Experimental validation of models (e.g., tuned mass dampers for semisubmersible platforms) and theoretical advancements in system dynamics (Hamiltonian approaches) are prominent themes. Awards: UCF College of Engineering Excellence in Graduate Teaching Award (2016) ASME Fellow Inductee into Pi Tau Sigma (2009) Grants & Advising: Leading a $3.3M project for floating offshore wind turbine simulators Received $771K grant for offshore wind turbine simulation tools Active in mentoring graduate students in mechanical systems research Labs/Teams: Directs the Hybrid Sustainable Energy Systems Lab at UCF, focusing on interdisciplinary energy solutions and advanced control system development.

• Dynamics and Controls
• Energy Systems
• Robotics
• +4 more