Find Academic Supervisors

Sean GallenView profile

Associate Professor

• Landscape Evolution
• Tectonics
• Natural Hazards
• +5 more

Prof. Sean Gallen is an Associate Professor in the Department of Geosciences at Colorado State University (CSU), USA. He holds a Senior Humboldt Research Fellowship at the GFZ German Research Centre for Geosciences, where he collaborates with Prof. Jean Braun's team in the Earth Surface Process Modeling section. His research integrates fieldwork, numerical modeling, geochronology, and GIS to study landscape evolution, tectonics, and natural hazards. Gallen earned his Master's (2008) from Western Washington University and PhD (2013) from North Carolina State University, followed by a Turner Postdoctoral Fellowship at the University of Michigan. Research Focus: His work examines climate-landscape interactions, subduction zone dynamics, and extreme event impacts on erosion. Notable projects include studying Colorado Front Range topography using cosmogenic nuclides and modeling climate effects on volcanic island landscapes. His interdisciplinary approach addresses topics like tectonic uplift quantification, silicate weathering feedbacks, and landscape-fish coevolution. Awards: Recipient of the NSF CAREER Award (2021) and Senior Humboldt Fellowship (2024). His research has been supported by NSF grants focusing on critical zone dynamics and subduction zone hazards. Current Projects: Investigating climatic controls on river incision in hotspot volcanoes and quantifying glacial erosion impacts on fault slip in the Sangre de Cristo Mountains. Collaborates internationally, including with Tribhuvan University (Nepal) on coseismic landslide studies.

Giorgio C. ButtazzoView profile

Professor

• Real-Time Systems
• Heterogeneous Computing
• Robotics
• +4 more

Giorgio C. Buttazzo is a Full Professor of Computer Engineering at the Scuola Superiore Sant'Anna in Pisa, Italy, and founder/director of the RETIS Lab. His career includes roles at the University of Pavia and co-founding Evidence s.r.l. (a real-time embedded systems company). He holds an IEEE Fellowship (2012) and the IEEE TC RTS Outstanding Technical Contributions Award (2013). Education: Electronic Engineering (University of Pisa, 1985), Master in Computer Science (University of Pennsylvania, 1987), PhD in Computer Engineering (Scuola Superiore Sant'Anna, 1991). Affiliations: TeCIP Institute, RETIS Lab, and leadership roles in IEEE Technical Committees. Research focuses on real-time systems, robotics, and AI integration. He has authored 10 books, over 300 papers, and pioneered frameworks like the ERIKA/SHARK kernels. Current projects include RETICULATE, OPERAND, and NANCY (5G networks). Teaching includes Real-Time Systems, Neural Networks, and Jazz Guitar Improvisation. Advised over 150 master and PhD students. Active in conferences like ECRTS, RTSS, and RTAS.

Weronika GorczykView profile

Adjunct Professor

• Geodynamics
• Tectonics
• Carbon Cycle
• +3 more

Weronika Gorczyk is an Adjunct Professor at the School of Earth and Oceans at The University of Western Australia. She holds a PhD from ETH Zurich (2008) and has extensive experience in geodynamic modeling, mineral systems research, and tectonic studies. Her research focuses on lithospheric-scale processes, including rifting, basin evolution, and the deep carbon cycle, with applications to mineral exploration. She currently leads MRIWA-funded projects investigating Proterozoic basin dynamics and their links to mineralization in the Paterson Orogen. Education: PhD in Geology, ETH Zurich (2008) Numerical Modeling experience from CSIRO (2008–2010) Research Interests: Geodynamics, tectonic evolution of cratons, carbon cycle dynamics, and the interplay between lithospheric deformation and mineralizing processes. Her work integrates numerical modeling, geophysical data, and field observations to address unresolved questions in Earth's evolution. Key Projects: MRIWA 521: Multi-stage basin evolution and mineralization in the Paterson Orogen ARC Linkage LP190100146: Integrated exploration framework for frontier basins ARC DP190100216: Fluid dynamics in deep Earth processes Grants & Leadership: Principal Investigator on MRIWA and ARC grants totaling over 18 funded projects. Active in collaborative networks with Geological Surveys, Macquarie University, and international experts. Labs/Teams: Core member of the Centre for Exploration Targeting and ARC Centre of Excellence for Core to Crust Fluid Systems. Leads multidisciplinary teams integrating geodynamic modeling, geochemistry, and geophysics.

Amir Hamed MajediView profile

Professor

• Quantum photonics
• Superconducting optoelectronics
• Microwave-photonics
• +5 more

Amir Hamed Majedi is a Professor at the University of Waterloo , cross-appointed to the Departments of Physics and Astronomy and Applied Mathematics . He leads the Integrated Quantum Optoelectronics Lab (IQOL) under the Waterloo Institute for Nanotechnology. Research Interests : Quantum photonics Superconducting optoelectronics Graphene photonics THz photonic devices Nano-electrophotonics Quantum information technology Article Trends : His publications focus on quantum electrodynamics in superconducting and graphene structures, covering single-photon detectors, nonlinear optical effects, THz amplification, and microwave-photonics integration. Keywords include Quantum Physics , Nanotechnology , Photonics , and Superconductivity . Teaching : Courses taught in recent years include ECE 106 - Electricity and Magnetism , ECE 375 - Electromagnetic Fields and Waves , and advanced topics in Quantum Electronics and Photonics (ECE 677, QIC 885). Education : Doctorate in Electrical and Computer Engineering (2001, University of Waterloo) Master's in Electromagnetic Waves and Photonic (1996, Amirkabir University of Technology) Bachelor's in Telecommunications (1994, Khaje-Nasir Toosi University of Technology)

Avery E. BroderickView profile

Associate Professor

• Theoretical Astrophysics
• Black Hole Physics
• General Relativity
• +3 more

Avery E. Broderick is an Associate Professor in the Department of Physics & Astronomy at the University of Waterloo and an Associate Faculty Member at the Perimeter Institute for Theoretical Physics. His research focuses on theoretical astrophysics, particularly studying compact objects like black holes and testing general relativity through astronomical observations. He is a key member of the Event Horizon Telescope (EHT) collaboration, which produced the first direct images of black hole horizons in M87* and Sagittarius A*. Broderick’s work emphasizes relativistic astrophysical phenomena such as accretion flows, jet formation, and polarization signatures. He collaborates extensively with observational astronomers and computational physicists to model black hole environments using general relativistic magnetohydrodynamic simulations. His recent research includes analyzing EHT data to constrain black hole spin, test spacetime metrics, and study photon ring dynamics. He also explores next-generation EHT (ngEHT) capabilities for higher-resolution imaging and multi-wavelength studies. Broderick has delivered invited lectures globally, including at Harvard-Smithsonian CfA, MIT, and the Aspen Center for Physics, reflecting his leadership in the field. Broderick’s contributions span over 135 refereed publications and conference proceedings, with a focus on black hole astrophysics, VLBI techniques, and relativistic plasma physics. His work bridges theoretical predictions with observational data, advancing our understanding of extreme gravitational regimes in the universe.

Ayusman SenView profile

Professor

• Nanotechnology
• Materials Science
• Chemical Biology
• +7 more

Ayusman Sen is the Verne M. Willaman Professor of Chemistry and Distinguished Professor of Chemistry at Pennsylvania State University. He holds a joint appointment in the Department of Chemical Engineering. His research focuses on self-powered nano/micromotors, dynamic materials, and enzyme-driven systems, with applications in smart materials and active matter. Sen’s work integrates chemical synthesis, catalytic energy harvesting, and emergent phenomena to create adaptive systems capable of performing complex tasks. Education: B.Sc. (Honours), University of Calcutta, India (1970) M.Sc., Indian Institute of Technology, Kanpur, India (1973) Ph.D., University of Chicago, USA (1978) Research Interests: Design of self-powered nanomotors and micropumps Chemically controlled assembly and motion of colloidal systems Enzyme cascade systems for programmable behavior Active matter and collective dynamics Key Contributions: Pioneered enzyme-powered micromotors for biomedical and environmental applications Developed theoretical frameworks for chemotactic assembly and non-equilibrium systems Engineered autonomous fluid-pumping systems using multi-enzyme networks Awards and Honors: Langmuir Lecture Award (American Chemical Society) Humboldt Prize (Alexander von Humboldt Foundation) Fellow of the Royal Society of Chemistry Paul J. Flory Award (IBM) Labs and Teams: His research group, the Sen Research Group, focuses on interdisciplinary projects at the interface of chemistry, materials science, and engineering. Current efforts explore light-driven systems, programmable fluidics, and bioinspired materials.

Alain TrouvéView profile

Professor

• Shape Spaces and Applications
• Imaging Processing and Computational Vision
• Computational Biology
• +3 more

Alain Trouvé is a Professor at the Center for Mathematics and Their Applications (CMLA) within the Ecole Normale Supérieure de Cachan , France. His research focuses on Shape Spaces , Computational Anatomy , Imaging Processing , and Biological Imaging , with applications in medical and computational fields. He directs the Mathematics Department at ENS Cachan and contributes to neuroanatomical studies through diffeomorphometry techniques. Key roles include membership in the Conseil National des Universités (Section 26) and teaching responsibilities such as courses on Geometry and Shape Spaces and Probability Theory . His work spans from theoretical frameworks (e.g., Hamiltonian modeling of shape evolution) to practical applications like 3D cell imaging and white matter fiber analysis. Publications emphasize interdisciplinary methods, including diffeomorphic registration, varifold-based image analysis, and stochastic shape evolutions. Current projects explore multi-scale modeling of biological systems and AI-driven medical diagnostics. Key Research Themes: Diffeomorphic mappings, computational vision, and functional shape analysis. Teaching: Courses on geometric modeling and probability at undergraduate and graduate levels. Tools Developed: xIV-LDDMM Toolkit for multi-modal biomedical data analysis.

Jiajia YuView profile

Assistant Professor

• Applied Mathematics
• Computational Mathematics
• Numerical Methods
• +3 more

Jiajia Yu is a Phillip Griffiths Assistant Research Professor in the Department of Mathematics at Duke University, affiliated with the Trinity College of Arts & Sciences. She holds a Ph.D. in Mathematics from Rensselaer Polytechnic Institute (2023) and a B.S. in Mathematics and Applied Mathematics from Beijing Normal University (2017). Her research focuses on applied and computational mathematics, with a particular emphasis on numerical methods for mean-field games, optimal transport, and inverse problems. She collaborates with prominent researchers such as Professors Hongkai Zhao, Xiuyuan Cheng, and Jian-Guo Liu. Recent work includes convergence analysis of fictitious play in mean-field games, zeroth-order optimization methods, and bilevel optimization frameworks for inverse mean-field games. Her contributions span computational methods on manifolds and trajectory regularization in machine learning contexts. Upcoming engagements include presentations at the IPAM Workshop on Scientific Machine Learning (2025) and Duke Math+ Program leadership on optimal transport topics. Her GitHub repositories showcase MATLAB implementations of FISTA algorithms and computational tools for mean-field games on manifolds.

James V. BurkeView profile

Professor

• Convex Optimization
• Non-smooth Optimization
• Variational Analysis
• +7 more

James V. Burke is a Professor of Mathematics at the University of Washington with extensive contributions to optimization theory and its applications. His academic career spans several decades, during which he has developed fundamental theories in nonsmooth and convex optimization, variational analysis, and computational methods for complex optimization problems. Research Focus Burke's primary research centers on convex-composite optimization , where he has established critical theoretical foundations and practical algorithms. His work on weak sharp minima has become foundational in optimization theory, providing essential insights into solution stability and error bounds. He has made significant advances in gradient sampling algorithms for nonsmooth, nonconvex optimization problems, which have broad applications in engineering and data science. More recently, Burke has applied optimization techniques to state estimation problems , particularly developing robust Kalman smoothing methods using Student's t-distributions and other non-Gaussian models. His research bridges pure mathematical theory with practical computational methods, demonstrating consistent innovation across multiple subfields of optimization. Academic Contributions Burke has taught numerous graduate-level courses including Math 509 (Optimal Control), Math 554 (Linear Analysis), and specialized courses on convex analysis and optimization. His research collaborations span multiple institutions, with frequent co-authorship with leading optimization researchers such as Tim Hoheisel, Adrian Lewis, and Michael Overton. He regularly presents his work at major conferences including SIAM Optimization and ICCOPT, with his most recent presentation at the SIAM Conference on Optimization in Seattle (June 2023).

Laurence Perreault-LevasseurView profile

Associate Professor

• Cosmology
• Machine Learning
• Gravitational Lensing
• +5 more

Laurence Perreault-Levasseur is an Associate Professor at Université de Montréal and an Associate Member of Mila. She specializes in applying machine learning methods to cosmology, with affiliations at the Flatiron Institute and Perimeter Institute. Her research focuses on gravitational lensing, dark matter, and precision cosmology. She holds a Canada Research Chair in Computational Cosmology and Artificial Intelligence. Education: PhD (University of Cambridge, 2015), M.Sc. and B.Sc. (McGill University). Research Interests: Machine learning for cosmological inference, strong gravitational lensing, galaxy cluster characterization, and dark matter studies. Affiliations: CRAQ (Québec Astrophysics Research Centre), Mila (Quebec AI Institute). Her work includes developing Bayesian methods for inverse problems and neural networks for astrophysical data analysis. Key projects involve precision cosmology via machine learning and reconstructing early-universe conditions using generative models.

Sherilyn Williams-StroudView profile

Professor

• Induced Seismicity
• Subsurface Storage
• Fracture Analysis and Modeling
• +4 more

Sherilyn Williams-Stroud is the Director of the Berg-Hughes Center and holds the Dan A. Hughes '51 Chair in Geosciences at Texas A&M University. She is a Professor in the Department of Geosciences, with over 30 years of expertise in structural geology, subsurface storage, and induced seismicity. Her research focuses on fracture analysis, geomechanics, and the societal impacts of energy resource utilization, particularly in carbon capture and storage (CCUS) and renewable energy transition. Education: BA in Geology from Oberlin College (198?), MA and PhD in Structural Geology from Johns Hopkins University (199?). Research interests include induced seismicity from fluid injection, subsurface tomographic imaging, and the integration of machine learning for improved subsurface modeling. Her work addresses critical challenges in energy resource management and environmental sustainability, with a focus on CO2 sequestration and geothermal energy. Publications highlight advancements in microseismic monitoring, fracture network modeling, and geomechanical analysis of CO2 injection sites. Her contributions span academic, industrial, and governmental sectors, including roles at the USGS, Chevron, and MicroSeismic Inc. Awards: AAPG Distinguished Lecturer (2023–2024), AAPG Honorary Member (2022), USGS Star Award (1997). Professional Leadership: Member of the National Petroleum Council’s Natural Gas GHG Study Committee, National Academy of Sciences’ Geodynamics Committee, and American Rock Mechanics Association’s Discrete Fracture Network Technical Committee. Her advisory and collaborative work bridges academia and industry, with a focus on mitigating risks in subsurface energy projects while advancing sustainable practices.

Shlomo Ta'asanView profile

Professor

• Materials Science
• Computational Biology
• Grain Growth Modeling
• +6 more

Shlomo Ta'asan is a Professor Emeritus in the Department of Mathematical Sciences at Carnegie Mellon University, affiliated with the Mellon College of Science. He holds a Ph.D. from The Weizmann Institute of Science. His research spans computational materials science and systems biology, with a focus on grain growth dynamics and immune response modeling. Collaborations include work with David Kinderlehrer, R. Suter Lab, and materials science faculty at CMU. Key research areas include bridging microscopic dynamics to macroscopic equations, grain boundary evolution, and immune system modeling. His work on inverse problems using HEDM data and entropy-based theories of grain boundary character distribution has advanced materials science. In biology, he develops models for circulatory system instabilities and shock mechanisms. Notable contributions include mesoscale simulations of grain growth and multigrid optimization methods for aerodynamics. His interdisciplinary approach integrates computational mathematics with experimental data from materials and biological systems.

Harold ParkView profile

Professor

• Computational Nanomechanics
• Mechanics of two-dimensional nanostructures
• Mechanics of soft, active materials
• +5 more

Harold S. Park is a Professor of Mechanical Engineering and Materials Science & Engineering at Boston University. He leads research in computational nanomechanics, focusing on nanowire mechanics, soft materials, and coupled electromechanical phenomena. Park earned his PhD from Northwestern University in 2004 and has held faculty positions since 2007. His work bridges atomistic simulations and continuum mechanics, addressing challenges in nanoscale material behavior and energy conversion. Education: PhD, Northwestern University (2004) MS, Northwestern University (2001) BS, Northwestern University (1999) Research Interests: Park’s lab explores topological mechanics, phononic metamaterials, and machine learning-driven materials design. Key areas include surface-dominated plasticity in nanomaterials, flexoelectricity in 2D materials, and energy harvesting via crumpling mechanics. His team develops multiscale models to predict mechanical behavior across length scales. Publications: Over 150 peer-reviewed articles span topics like nanowire deformation mechanisms, nanoresonator dynamics, and topology-optimized metamaterials. Recent work highlights include enhancing nanowire Q-factors via strain tuning and designing non-reciprocal elastic systems. Awards: NSF CAREER Award (2007) DARPA Young Faculty Award (2008) ASME Fellow (2016) John Argyris Award (2016) Advising & Teams: Park mentors graduate students and postdocs in experimental and computational mechanics. Notable advisees include Dr. Penghui Cao (UC-Irvine faculty) and Dr. Saman Seifi. His lab collaborates with industry partners on nanomaterials for sensors and energy systems. Labs: Affiliated with the Materials by Design Center at BU, focusing on computational and experimental nanomechanics. Active in editorial roles for journals like Journal of Applied Mechanics and Nano Letters .

Sachin ShanbhagView profile

Associate Professor

• Polymer Rheology
• Complex Fluids
• Molecular Simulations
• +6 more

Sachin Shanbhag is an Associate Professor in the Department of Scientific Computing and Department of Chemical & Biomedical Engineering at Florida State University (FSU), affiliated with the FAMU-FSU College of Engineering. His research focuses on polymer rheology, complex fluids, and multiscale modeling with applications in biomedical materials and nanotechnology. He holds a PhD in Chemical Engineering from the University of Michigan and a B.Tech from IIT Bombay. Research interests include polymer dynamics, constitutive modeling, and inverse problems. Notable awards include the NSF Early Career Award (2010) and the Petroleum Research Fund New Faculty Award (2006–2008). His work bridges computational methods with experimental data, advancing understanding of polymer networks and viscoelastic behavior. Education: B.Tech, IIT Bombay (1999); PhD, University of Michigan (2004) Affiliations: FSU-FAMU College of Engineering, Department of Scientific Computing Key Projects: Multiscale modeling for tissue engineering, nanotechnology applications, and polymer dynamics His publications emphasize analytical and numerical approaches to rheological challenges, with contributions to software tools like pyReSpect for relaxation spectrum analysis. Current research trends include nonlinear rheology, surrogate modeling, and data assimilation in polymer systems.

Douglas W. CarterView profile

Assistant Professor

• Experimental turbulent flows
• Particle-turbulence interaction
• Noise generation of separated flows
• +7 more

Douglas W. Carter is an Assistant Professor in the Department of Mechanical, Materials, and Aerospace Engineering at the Armour College of Engineering, Illinois Institute of Technology. He leads the Experimental Turbulent Flows Lab, focusing on advanced experimental techniques for fluid dynamics research. Education: Ph.D., University of Minnesota, 2019 M.S., University of Minnesota, 2017 B.S., University of New Hampshire, 2014 Research Interests: Dr. Carter investigates experimental turbulent flows, particle-turbulence interactions, and noise generation in separated flows. His expertise spans particle tracking velocimetry, hypersonics, compressible flows, and data-driven methods for fluid systems. Research emphasizes experimental validation of turbulence models and development of novel diagnostic tools like FLEET velocimetry. Publications: Recent work explores hypersonic flow diagnostics, pressure reconstruction in stalled airfoils, and turbulence cascade dynamics. Publications demonstrate consistent focus on experimental fluid mechanics, high-speed flow measurements, and low-order modeling for aerodynamic prediction. Laboratory: The Experimental Turbulent Flows Lab (Rettaliata Engineering Center) develops cutting-edge techniques for turbulent flow analysis, including multi-scale imaging and optical diagnostics for high-speed applications.