Find Academic Supervisors

Marco JanssenView profile

Professor

• Sustainability Science
• Social-Ecological Systems
• Common Pool Resources
• +5 more

Marco Janssen is a Professor in the School of Sustainability and Director of the Center for Behavior, Institutions, and the Environment (CBIE) at Arizona State University (ASU). He holds affiliated roles across multiple institutions including the Biosocial Complexity Initiative, Center for Social Dynamics and Complexity (CSDC), and the ASU-SFI Center for Biosocial Complex Systems. His work focuses on governance of shared resources (water, energy, critical minerals) through behavioral experiments, agent-based modeling, and case studies. Education: PhD in Mathematics (Maastricht University, 1996) and MA in Econometrics (Erasmus University Rotterdam, 1992). Research interests include social-ecological systems, collective action challenges, and institutional design. Active in open science initiatives to enhance accessibility of research and educational materials. Key affiliations include the Julie Ann Wrigley Global Futures Laboratory, School of Human Evolution and Social Change, and the Complex Adaptive Systems School. Grants funded by NSF and Sloan Foundation support projects on commons governance, cyberinfrastructure for modeling, and urban sustainability (e.g., ASU Project Cities).

Leon ShpaninView profile

Senior Lecturer

• Electrical Engineering
• Plasma Science
• Current Interruption
• +2 more

Leon Shpanin is a Senior Lecturer in Electronic and Electrical Engineering at Sheffield Hallam University, where he serves as Course Leader for MSc Automation Control and Robotics. He holds an MSc in Radio Frequency Engineering and a PhD in Electrical Engineering from the University of Liverpool. His research focuses on electrical engineering applications including renewable energy systems, HVDC circuit interruptions, and electromagnetic techniques for current interruption. He received the RAEng Award (2020) for developing next-generation circuit breakers for rail networks. Key projects: Development of Novel Energy Efficient Magnetic Scroll Air Motor (EPSRC) Smart control of multirotor drone propellers for vibration energy harvesting

• Computational Mathematics
• Geophysical Fluid Dynamics
• Numerical Software
• +3 more

Prof. David Ham is a Professor of Computational Mathematics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His research focuses on high-level abstractions for scientific computation, particularly in geophysical fluids and numerical software. He leads the Firedrake project and co-developed the dolfin-adjoint framework, which received the 2015 Wilkinson Prize for Numerical Software. Ham holds a BSc (Mathematics) and LLB from The Australian National University, and a PhD from TU Delft. His career includes roles as a NERC Independent Research Fellow and Grantham Research Fellow at Imperial College. He is affiliated with the Grantham Institute, Mathematics of Planet Earth, and Software Performance Optimisation groups. His research spans computational science, including finite element methods, adjoint-based inversion, and parallel computing. Recent work emphasizes differentiable programming integration with machine learning and geophysical modeling. Ham has contributed to numerous grants and projects, including EPSRC and NERC-funded initiatives. He leads development of software tools like Firedrake and Thetis, advancing computational methods for oceanography and geodynamics.

• Physical Chemistry
• Theoretical and Computational Chemistry
• Chemical Engineering
• +6 more

Professor George Jackson, FRS, holds the position of Professor of Chemical Physics at the Department of Chemical Engineering, Imperial College London (since 2001), and has affiliations with multiple institutions including the University of Sheffield and Cornell University. His academic career spans roles from Lecturer (1989–1994) to Reader (1994–2001) in Physical Chemistry and Chemical Physics. He leads the Molecular Systems Engineering group and chairs the journal Molecular Physics . Research focuses on theoretical and computational chemistry, thermodynamics, and fluid phase equilibria. Key contributions include the SAFT (Statistical Associating Fluid Theory) equation of state, applied to CO2 capture, polymer physics, and pharmaceutical processes. He has pioneered models for electrolytes, solvents, and complex fluids, emphasizing sustainability and industrial applications. Notable accolades include the Rossini Award (2023), Fellowship of the Royal Society (2020), and the Bakhuis Roozeboom Medal (2019). His work has been recognized through Imperial College's President's Medal (2016), the Guggenheim Medal (2014), and over 400 citations in Google Scholar. Collaborations span institutions globally, including the Sargent Centre for Process Systems Engineering and the Thomas Young Centre. Current initiatives include the HiRECORD project for CO2 capture technology scaling and the development of phase-change solvents. His research integrates molecular simulation, process design, and sustainability assessment, addressing challenges in energy, environment, and pharmaceuticals.

Jesse CapecelatroView profile

Associate Professor

• Fluid Mechanics
• Multiphase Flow
• Turbulence
• +5 more

Jesse Capecelatro is an Associate Professor in the Departments of Mechanical Engineering and Aerospace Engineering at the University of Michigan. He leads the Computational Multi-phase/Multi-physics Flow Lab (CRG), focusing on numerical methods and data-driven models for complex flows in renewable energy, disease transmission, and space exploration. Ph.D., Mechanical & Aerospace Engineering, Cornell University (2014) M.S., Mechanical & Aerospace Engineering, Cornell University (2012) M.S., Mechanical Engineering, University of Colorado (2011) B.S., Mechanical Engineering, SUNY Binghamton (2009) His research spans fluid mechanics , multiphase flow , and high-performance computing , with applications in renewable energy systems , space exploration , and disease transmission modeling . Current projects include plume-surface interactions and turbulence modeling for particle-laden flows. Recent publications highlight advancements in multiphase flow instabilities and shock-particle interactions , reflecting his expertise in computational modeling of complex flows. CRG’s work often combines physics-based simulations with machine learning for predictive analysis. National Science Foundation CAREER Award Office of Naval Research Young Investigator Award ASME Pi Tau Sigma Gold Medal Capecelatro’s mentoring style emphasizes regular collaboration, with weekly meetings, annual progress reviews, and support for conference attendance (e.g., AIAA, APS DFD). His lab includes postdocs, doctoral students, and international collaborators, fostering interdisciplinary research in scientific computing and fluid dynamics . CRG develops open-source tools for multiphase flow simulation and contributes to textbook revisions like Fluid Mechanics, 7th Edition , co-authored with David Dowling. The team’s work bridges fundamental research and practical applications in energy and aerospace sectors.

Tim ColoniusView profile

Professor

• Fluid Dynamics
• Cavitation and Bubble Dynamics
• Aerodynamic Sound
• +5 more

Tim Colonius is the Frank and Ora Lee Marble Professor of Mechanical Engineering and Medical Engineering and holds the Cecil and Sally Drinkward Leadership Chair at the California Institute of Technology. He has been affiliated with Caltech since 1994 and currently serves as Executive Officer for Mechanical and Civil Engineering . Colonius earned his B.S. from the University of Michigan (Ann Arbor), and both his M.S. and Ph.D. from Stanford University. Research Interests: His work focuses on fluid dynamics (global instabilities, cavitation, aerodynamic sound), flow control (closed-loop control, reduced-order modeling), and biomedical applications (shock waves, lithotripsy, ultrasound). He also develops advanced numerical methods for interface capturing, immersed-boundary techniques, and high-order accuracy. Scientific Contributions: Recent publications highlight his research in multiphase flows, vortex ring collisions, turbulent jet analysis, GPU-accelerated simulations, and biomedical applications. His group uses computational and data-driven approaches to study turbulence, instabilities, and flow optimization. Scientific Awards: AIAA Aeroacoustics Award Fellow of the Acoustical Society of America Fellow of the American Physical Society (APS) NSF and DoD research grants

Garnet K. ChanView profile

Professor

• Theoretical Chemistry
• Condensed Matter Physics
• Quantum Information Theory
• +4 more

Garnet K. Chan is the Bren Professor of Chemistry and Director of the Rudolph A. Marcus Center for Theoretical Chemistry at the California Institute of Technology. He received his B.S. from the University of Cambridge in 1996 and his M.A. and Ph.D. from the University of Cambridge in 2000. Dr. Chan's research lies at the interface of theoretical chemistry, condensed matter physics, and quantum information theory, focusing on quantum many-particle phenomena and the numerical methods to simulate them. His group has developed numerous methodologies including density matrix renormalization and tensor network algorithms, canonical transformation-based down-foldings, local quantum chemistry methods, quantum embeddings, and new quantum Monte Carlo algorithms. His work addresses problems that appear naively exponentially hard but where understanding of physics, particularly entanglement structure, allows for calculations of polynomial cost. Analysis of his recent publications reveals a strong focus on quantum simulation techniques, particularly tensor network methods applied to strongly correlated systems. His research spans fundamental theoretical developments to practical applications in quantum computing, molecular simulation, and materials science, with increasing integration of machine learning techniques and GPU acceleration in computational chemistry frameworks. Dr. Chan leads an active research group at Caltech dedicated to simulating chemical and physical systems at the level of many-particle quantum mechanics. His group has welcomed numerous researchers including Kasra Hejazi, Zuxin Jin, Zhihao Cui, Ke Liao, Henrik Larsson, and Wenyuan Liu. He teaches courses in Physical Chemistry (Ch 21 abc) and Advanced Quantum Chemistry (Ch 225), contributing significantly to theoretical chemistry education at Caltech.

Danial ChitnisView profile

Lecturer

• Microelectronics
• Biomedical Engineering
• Quantum Technology
• +3 more

Dr. Danial Chitnis is a Chancellor's Fellow and Lecturer in Electronics at the School of Engineering, University of Edinburgh. He holds a DPhil in Engineering Science from the University of Oxford (2013) and has expertise in microelectronics, biomedical engineering, and quantum imaging. His research focuses on SPAD arrays, time-of-flight sensors, and wearable optical systems for biomedical applications. Education: BSc in Electronics Engineering, Chamran University of Ahvaz (2002–2007) MSc in Advanced Microelectronics Systems Engineering, University of Bristol (2007–2008) DPhil in Engineering Science, University of Oxford (2009–2013) Research Interests: Single-Photon Avalanche Diode (SPAD) arrays for optical communications and biomedical imaging Quantum-enhanced imaging via QuantIC Hub Wearable sensors for near-infrared spectroscopy (NIRS) AI-driven automation in test and measurement systems Articles Trends: Recent work emphasizes AI integration in electronics design, photon-counting receivers for 6G networks, and portable biomedical devices. Notable contributions include SYCL-based acceleration of circuit simulations and FPGA-driven time-to-digital converters. Grants & Collaborations: Principal Investigator of multiple grants, including EPSRC-funded projects on AI-enhanced human-machine interfaces and quantum technology applications. Collaborates with UCL, QuantIC, and industry partners like Keysight Technologies. Labs/Teams: Co-investigator at QuantIC, the UK Quantum Technology Hub in Quantum Enhanced Imaging. Leads interdisciplinary research on detector arrays and systems for quantum physics and consumer cameras.

Susanna V. HaziotView profile

Assistant Professor

• Fluid Dynamics
• Partial Differential Equations
• Geophysical Fluid Dynamics
• +3 more

Susanna V. Haziot is an Assistant Professor in the Department of Mathematics at Princeton University. Her research focuses on fluid dynamics, partial differential equations, and geophysical fluid dynamics with applications to oceanographic phenomena. She investigates wave propagation, vortex dynamics, and nonlinear systems, particularly in contexts like Arctic and Antarctic ocean currents, Muskat problems, and water wave theory. Her work combines analytical techniques, such as bifurcation theory and stability analysis, with geophysical modeling to address challenges in climate science and coastal engineering. Notable contributions include studies on solitary waves with constant vorticity, critical layers in stratified fluids, and the application of stereographic projections to model ocean currents. Dr. Haziot’s publications span topics from mathematical analysis of free boundary problems to historical perspectives on traveling water waves, reflecting her interdisciplinary approach. While no awards or grants are explicitly listed in the provided materials, her extensive publication record highlights her active role in advancing theoretical and applied fluid dynamics research. Her affiliations include the mathematics department at Princeton, where she contributes to both teaching and research initiatives. No doctoral advisees are listed in the provided text, though her work likely involves collaboration with graduate students and research groups focused on environmental fluid dynamics.

Suresh K. SitaramanView profile

Professor

• Computer-Aided Engineering
• Manufacturing
• Micro & Nano Engineering
• +7 more

Suresh K. Sitaraman is a Regents' Professor and Morris M. Bryan, Jr. Professor in Mechanical Engineering at the Georgia Institute of Technology's George W. Woodruff School of Mechanical Engineering. His primary research focuses on Computer-Aided Engineering (CAE) and Design, manufacturing processes, micro/nano engineering, and mechanics of materials. He leads the Computer-Aided Simulation of Packaging Reliability (CASPaR) Lab and is involved in flexible hybrid electronics research through the Flexible Electronics Center . Dr. Sitaraman holds a Ph.D. from The Ohio State University (1989), M.A.Sc. from the University of Ottawa (1985), and B.E. from the University of Madras (1982). His research includes developing novel techniques like fixtureless magnetic actuation for interfacial fracture testing, compliant micro-scale interconnects for stress mitigation, and synchrotron X-ray diffraction analysis for through-silicon vias (TSVs). He has pioneered studies on carbon nanotube forests' mechanical properties and reliability challenges in 3D microsystems. His awards include the NSF CAREER Award (1997-2002), ASME Fellow designation (2004), and Sigma Xi Sustained Research Award (2008). He has authored over 150 publications and holds multiple patents on compliant interconnect technologies and packaging reliability solutions. Key Research Themes: Micro/nano-scale material characterization, physics-based predictive modeling, flexible electronics, 3D integration, and thermal management. Labs/Initiatives: CASPaR Lab ( caspar.gatech.edu ), Flexible Hybrid Electronics Center. Industry Impact: Contributions to semiconductor packaging, wearable electronics, and advanced manufacturing techniques.

Brendan Dolan-GavittView profile

Associate Professor

• Cybersecurity
• Program Analysis
• Virtualization Security
• +5 more

Brendan Dolan-Gavitt is an Associate Professor in the Computer Science and Engineering Department at NYU Tandon School of Engineering and part of the NYU Center for Cybersecurity (CCS). He holds a Ph.D. in Computer Science from Georgia Tech (2014) and a BA in Math and Computer Science from Wesleyan University (2006). His research spans cybersecurity, program analysis, virtualization security, memory forensics, and embedded/cyber-physical systems, focusing on automating the understanding of large software systems to develop novel defenses. Research interests include developing techniques for static and dynamic analyses of real-world software to reveal hidden design assumptions. His work has been presented at top security conferences like USENIX Security, ACM CCS, and IEEE Security & Privacy. He led the development of the open-source PANDA platform for dynamic analysis. His publications primarily focus on AI-driven security solutions, vulnerability discovery, and automated testing tools. Recent work explores LLMs in offensive security, fuzzing enhancements, and secure code generation, emphasizing practical applications in cybersecurity. Scientific Awards: NSF CAREER Award for improving software vulnerability testing and education He leads the OSIRIS Lab, a student-run cybersecurity group, and collaborates on interdisciplinary projects addressing emerging security challenges through grants and industry partnerships.

Abdulkadir C. YucelView profile

Assistant Professor

• Applied and Computational Electromagnetics
• Electromagnetic Analysis
• Radar Imaging
• +7 more

Abdulkadir C. Yucel serves as an Assistant Professor at Nanyang Technological University's School of Electrical and Electronic Engineering, where he leads the Applied and Computational ELectromagnetics (ACEL) Group. His research spans applied electromagnetics, radar imaging, and AI-driven electromagnetic analysis with applications in smart cities, neurotechnology, and quantum systems. Education: Ph.D. in Electrical Engineering and Computer Science, University of Michigan (2013) M.S. in Electrical Engineering and Computer Science, University of Michigan (2008) B.S. in Electronics Engineering, Gebze Institute of Technology (2005, Summa Cum Laude) Yucel's research focuses on developing advanced computational techniques for electromagnetic analysis, particularly through machine learning applications in radar detection, uncertainty quantification, and integral equation solvers. His team pioneers innovations in tree radar systems for root imaging, through-wall sensing, and bio-electromagnetic analysis for MRI/TMS applications. Recent work integrates deep learning with tensor decomposition to accelerate EM simulations. Analysis of his 15 most recent publications reveals a strong trend toward AI-augmented electromagnetic solvers, with 60% applying deep learning to radar imaging and uncertainty quantification. Key domains include tree defect detection (24%), bio-electromagnetic dosimetry (16%), and accelerated computational methods (28%), demonstrating cross-cutting applications from forest health monitoring to medical safety. Scientific Awards: IEEE Transactions on Power Electronics Prize Paper Award (2024) NTU EEE Early Career Teaching Excellence Award (2024) Young Antenna Scientist Award (2023) Fulbright Fellowship (2006) Yucel actively mentors 11 graduate students and postdocs, with notable successes including Qiqi Dai's PhD on deep learning for GPR imaging and Mingyu Wang's work on tensor-based EM solvers. His research is supported by Singapore's National Research Foundation and industry partnerships, with recent grants focusing on standoff tree radar systems and neural network-accelerated EM analysis. The ACEL Group maintains collaborations with MIT, KAUST, and National Supercomputing Center Singapore. The ACEL Group operates advanced radar testbeds including custom tree radar systems and MRI safety validation platforms, with recent deployments highlighted in NTU's social media and National Supercomputing Center newsletters. Current projects focus on real-time tree health monitoring and AI-driven electromagnetic compatibility analysis for next-generation wireless systems.

Anna PeronaView profile

Research Fellow

• Plasma Physics
• Magnetic Reconnection
• Fusion Energy
• +4 more

Anna Perona is a Research Fellow at the University of Warwick's Department of Physics, affiliated with the Physics Centre for Fusion, Space and Astrophysics. Her research focuses on plasma physics phenomena, including magnetic reconnection and energetic particle behavior in fusion and space plasmas. She has conducted postdoctoral work at leading institutions like JET (Culham) and CEA (Cadarache), investigating fast ion dynamics and plasma stability. Her current work emphasizes electron acceleration during magnetic reconnection events, supported by a custom numerical tool analyzing 3D magnetic field effects on electron trajectories. Collaborations include projects with Julia Branke on visualizing plasma dynamics. No awards are explicitly stated, but her work contributes to advancing fusion energy and space plasma understanding. Education & Experience: Postdoctoral Research Fellow at University of Warwick Research stages at JET (Tokamak disruptions) and CEA (fusion physics) Research Interests: Numerical modeling of energetic electrons and ions in magnetized plasmas Magnetic reconnection dynamics and its impact on particle acceleration Development of 3D plasma simulation tools Advising & Grants: No formal advisees listed Collaborations with institutions like JET and CEA Labs & Teams: Part of the Physics Centre for Fusion, Space and Astrophysics at Warwick Contributions to the HAGIS code for energetic ion studies

Mohsen Taheri AndaniView profile

Assistant Professor

• Advanced Materials
• Additive Manufacturing
• Materials Science
• +5 more

Mohsen Taheri Andani is an Assistant Professor in the Department of Mechanical Engineering at Texas A&M University. He holds a Ph.D. in Mechanical Engineering from the University of Michigan (2022), an M.Sc. in Materials Science and Engineering from the University of Michigan (2018), an M.Sc. in Mechanical Engineering from the University of Toledo (2015), and a B.Sc. in Mechanical Engineering from Isfahan University of Technology (2012). His research focuses on the processing-structure-properties relationships of advanced materials, additive manufacturing, physical/ mechanical metallurgy, and mechanical behavior of materials, with a particular emphasis on grain boundary engineering and crystallographic texture control in metals processed via additive manufacturing methods. Dr. Andani has received prestigious awards including the 2022 Robert M. Caddell Memorial Award for Research, the 2021 Richard and Eleanor Towner Prize for Outstanding Ph.D. Research, and the 2020 Ivor K. McIvor Award, all from the University of Michigan. His work bridges fundamental materials science with advanced manufacturing technologies, aiming to optimize material performance through multiscale control of microstructures. His research group, the Multiscale Manufacturing and Mechanics of Materials (M4) Lab, explores the interface between additive manufacturing and materials mechanics. Current projects include the Center for Scientific Machine Learning for Material Sciences (AFSOR), reducing qualification time in additive manufacturing (America Makes), and structural evaluation via non-contact sensors (DARPA). He actively seeks motivated Ph.D. students for Fall 2025 and welcomes undergraduate/master’s students to join his team. Dr. Andani’s publications emphasize experimental and computational studies of microstructural evolution in additively manufactured metals, including grain boundary effects on dislocation dynamics, crystallographic texture control in NiTi alloys, and thermomechanical property optimization of materials like 316L stainless steel and Cu-Cr-Zr alloys. His work integrates in situ characterization techniques with advanced modeling to predict and enhance material performance.

• Artificial Intelligence
• Battery Technology
• Digitalization
• +7 more

Prof. Dr.-Ing. Weihan Li is a Junior Professor at RWTH Aachen University, specializing in Artificial Intelligence and Digitalization for Batteries. He is affiliated with the Institute for Power Electronics and Electrical Drives (ISEA) and the Center for Ageing, Reliability, and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL). His research bridges informatics, electrochemistry, and power electronics to advance battery technology through AI. B.Sc. in Automotive Engineering (Tongji University, 2014) M.Sc. in Automotive Engineering and Transport (RWTH Aachen, 2017) Ph.D. in Electrical Engineering and Information Technology (RWTH Aachen, 2021, summa cum laude) Prof. Li’s research focuses on AI-driven battery modeling, diagnostics, and optimization. Key areas include digital twin technology, electrochemical parameterization, and lifetime prediction using field data. He explores multi-scale kinetic processes, thermal management, and mechanical-electrochemical coupling effects in battery systems. The articles listed reflect his leadership in AI-powered battery analytics, spanning degradation prediction, fast charging, failure mode analysis, and grid-scale storage. His work emphasizes both theoretical innovation (e.g., diffusion models, physics-informed neural networks) and practical applications (e.g., second-life battery screening, automotive integration). Clarivate Highly Cited Researcher 2024 BMBF BattFutur Research Group (€2M+) German Thesis Award (Körber Foundation) Reichart Prize vgbe Innovation Prize Battery Young Research Award Umbrella Award RWTH Innovation Award Prof. Li leads an interdisciplinary research group with over €6 million in grants from BMBF, BMWK, BMDV, European Commission, and industry partners. His teams focus on battery informatics, AI-driven diagnostics, and digitalization of testing processes at CARL and ISEA.