جست‌وجوی استاد و پژوهشگر

Sheng Shenمشاهده پروفایل

استاد

• Nanophotonics
• Nanoscale Energy Transport and Conversion
• Advanced Manufacturing
• +۷ مورد دیگر

Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.

Andrew Stuartمشاهده پروفایل

استاد

• Applied and Computational Mathematics
• Bayesian Inverse Problems
• Data Assimilation
• +۶ مورد دیگر

Andrew Stuart is the Bren Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech), joining in 2016. He previously held faculty positions at the University of Warwick (1999–2016), Stanford University (1992–1999), and Bath University (1989–1992). He earned his PhD from the University of Oxford's Computing Laboratory in 1986. Professor Stuart's research focuses on applied and computational mathematics , particularly Bayesian inverse problems , data assimilation for dynamical systems , and stochastic modeling . His work bridges mathematical theory, algorithm development, and applications in geophysics, materials science, and biological systems. His recent publications emphasize operator learning , machine learning for PDEs , and uncertainty quantification . Key areas include ensemble Kalman methods , Gaussian processes , and neural operators for solving and learning from complex systems. Scientific awards include the Vannevar Bush Faculty Fellowship and election to the Royal Society of Great Britain . He advises graduate students in applied mathematics, computational science, and geophysics, including Edoardo Calvello , Hojjat Kaveh , and Florian Wolf .

Maria Gouskovaمشاهده پروفایل

استاد

• Phonology
• Morphology
• Lexical Phonology
• +۳ مورد دیگر

Maria Gouskova is a Professor of Linguistics at the Department of Linguistics, New York University (NYU). She is affiliated with the College of Arts and Science and holds editorial roles as an Associate Editor of Language and board member of NLLT and Phonology . Her research focuses on phonology, morphology, and lexicon, with a particular emphasis on morphophonological interactions, sublexicons, and phonotactic constraints. She earned her Ph.D. in Linguistics from the University of Massachusetts, Amherst (2003) and a B.A. in English Linguistics and German Language/Literature from Eastern Michigan University (1998). Her work bridges theoretical phonology and experimental methods, addressing questions such as how phonological patterns interact with morphology, the role of sublexical phonotactics in grammatical processes, and the learnability of complex segmental inventories. Recent research includes studies on Russian diminutive affixes, gradient phonological constraints, and the phonological properties of compounds. Her publications span topics like allomorphy, lexical phonology, and the typology of morpheme structure constraints. She frequently collaborates on projects investigating the interplay between syntax, phonology, and morphology, as seen in studies of Russian prepositions and compound stress patterns. Her contributions to phonological theory include advancing models of sublexicon theory and nonlocal constraint induction.

Andrea Coladangeloمشاهده پروفایل

استادیار

• Quantum Computation
• Quantum Cryptography
• Quantum Learning Theory
• +۳ مورد دیگر

Andrea Coladangelo is an Assistant Professor at the Allen School of Computer Science & Engineering , University of Washington , co-leading the Quantum group and contributing to the Theory and Crypto groups. He coordinates the NSF-funded Quantum@UW REU program , fostering undergraduate research in quantum information. Previously, he was a postdoctoral researcher at UC Berkeley and the Simons Institute , advised by Umesh Vazirani , following a PhD in Computer Science at Caltech under Thomas Vidick . His academic journey began with a B.A. in Mathematics from Oxford and a Master in Mathematics from Cambridge . He co-founded qBraid , a platform for quantum computing education. Research Interests : Andrea explores the intersection of quantum computation and cryptography , focusing on foundational questions in entanglement , quantum correlations , and quantum learning theory . His work investigates quantum pseudorandomness , device-independent security , quantum algorithms , and quantum copy-protection , often leveraging computational assumptions to bridge quantum information theory with cryptographic applications. Scientific Awards : 2025 Google Research Scholar Program Award in Quantum Computing 2023 CSE Undergraduate Teaching Award for his course on quantum computation 2019 Best Student Paper Award at QIP Teaching & Outreach : Andrea designed and taught CSE 434: Intro to Quantum Computation (Spring 2023, 2024, 2025), CSE 534: Quantum Information and Computation (Autumn 2023), and CSE 599C: Quantum Learning Theory (Winter 2025). He also delivered lectures at the 22nd Bellairs Crypto Workshop (2024) and led a quantum programming tutorial using qBraid . Labs & Teams : As co-leader of the Quantum group at the Allen School, he collaborates with researchers in Theory and Crypto , advancing quantum computing through interdisciplinary projects and educational initiatives.

Andrew Childsمشاهده پروفایل

استاد

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +۲ مورد دیگر

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

Zongyi Liمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Scientific Computing
• Partial Differential Equations
• +۵ مورد دیگر

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

Ali Mostafazadehمشاهده پروفایل

استاد

• Mathematical Physics
• Quantum Mechanics
• Scattering Theory
• +۳ مورد دیگر

Ali Mostafazadeh is a Professor at the Department of Mathematics, College of Sciences, Koç University. His research spans Mathematical Physics, focusing on Quantum Mechanics, Scattering Theory, and PT-Symmetry. He has made significant contributions to understanding non-Hermitian Hamiltonians, electromagnetic wave propagation, and geometric scattering phenomena. Education: PhD in Physics (1994) from The University of Texas, BA in Physics and Mathematics (1989) from Boğaziçi University His work explores the intersection of mathematics and physics, particularly through spectral singularities, transfer matrix methods, and nonlinear optical systems. Recent publications highlight advancements in broadband directional invisibility, exact Born approximations, and time-dependent Hilbert spaces in quantum systems. 2011 Outstanding Success Award 2007 TÜBİTAK Science Award 2006 Werner-von-Siemens Excellence Award 2001 TÜBA Outstanding Young Scientists Award 2001 Parlar Foundation Research Incentive Award

• Inverse Problems
• Partial Differential Equations
• Mathematical Physics
• +۳ مورد دیگر

Ali Feizmohammadi is an Assistant Professor, Teaching Stream (LTA) in the Department of Mathematics at the University of Toronto Mississauga, affiliated with the Mathematical and Computational Sciences division. His research focuses on inverse problems, partial differential equations, and geometric analysis. He holds a position emphasizing teaching excellence within the university's framework. His work addresses advanced mathematical challenges such as coefficient identification in subdiffusion equations, fractional Laplacian problems on Riemannian manifolds, and nonlinear elliptic equations on manifolds. Recent articles highlight contributions to the Calderón problem in various contexts, wave equation control, and spacetime finite element methods. No scientific awards or grants are explicitly listed in the provided information. He has not yet listed advisees in the available data. His research trends emphasize rigorous mathematical analysis of inverse problems in both classical and fractional PDE frameworks, with applications to geometric and control-theoretic questions. Dr. Feizmohammadi's work spans theoretical advancements in inverse problems, numerical methods for control systems, and the interplay between differential geometry and PDEs. His contributions address both fundamental theory and applied methodologies in mathematical physics and engineering.

John Evansمشاهده پروفایل

دانشیار

• Computational Mechanics
• Fluid Dynamics
• Fluid-Structure Interaction
• +۳ مورد دیگر

John Evans is an Associate Professor and Jack Rominger Faculty Fellow in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, affiliated with the Applied Mathematics program. He serves as Associate Chair for Undergraduate Curriculum and is part of the Aerospace Mechanics Research Center (AMREC). His research focuses on computational mechanics, particularly fluid dynamics, fluid-structure interaction, and turbulence modeling using high-order and structure-preserving methods. Evans holds a PhD (2011) and MS (2008) in Computational and Applied Mathematics from the University of Texas at Austin, and dual BS/MS degrees in Mathematics and Applied Mathematics from Rensselaer Polytechnic Institute (2006). Before joining CU Boulder, he was a postdoctoral fellow at the Institute for Computational Engineering and Sciences (ICES). His research interests include isogeometric analysis, immersed methods, and data-driven turbulence modeling. Notable contributions include development of divergence-conforming discretizations for incompressible flows, stabilized collocation methods, and invariant subgrid stress models. He leads the AMREC lab and collaborates on plasma-fueled propulsion systems and geometrically sensitive simulations. Key Awards: 2021: Rocky Mountain AIAA Educator of the Year 2021: Gallagher Young Investigator Medal 2019-2021: Clarivate Highly Cited Researcher Professional Activities: Editor of Engineering Computations, Senior AIAA Member, Simons Visiting Professor (2019) Evans' work bridges advanced numerical methods with real-world engineering challenges. His lab develops open-source tools like XIGA for multi-material problems and focuses on immersive simulation environments. Current projects explore turbulence closure models, plasma propulsion, and topology optimization with B-spline-based approaches.

• Nonlinear partial differential equations
• Singularity formation
• Mathematical analysis
• +۲ مورد دیگر

Manuel Del Pino is Professor at the University of Bath's Department of Mathematical Sciences and Royal Society Professor specializing in nonlinear partial differential equations. His research focuses on singularity formation, geometric evolution equations, and asymptotic analysis in fluid dynamics and mathematical physics. His investigations encompass blow-up phenomena in heat equations, vortex dynamics in Euler flows, and minimal surface theory. Current projects examine infinite-time singularity formation in parabolic equations and asymptotic properties of vortex configurations. Del Pino has received the Royal Society Professorship and leads multiple grants including 'Asymptotic patterns in nonlinear evolution problems' (EPSRC). He maintains collaborations with researchers globally through projects on singularity formation in PDEs.

Jean-Claude Besseمشاهده پروفایل

مدرس

• Quantum Computing
• Superconducting Circuits
• Microwave Photonics
• +۵ مورد دیگر

Jean-Claude Besse is a Lecturer in the Department of Physics at ETH Zürich, specializing in superconducting circuits and quantum optics. His research focuses on quantum computing, microwave photonics, and artificial atoms. Research Interests: Besse works on the fabrication of superconducting circuits, modular quantum computing processors, and microwave quantum optics using artificial atoms. His work includes single-photon detection, parity measurements, entanglement stabilization, and quantum networking. He has developed technologies like high-fidelity multiplexed readout and tunable ZZ gates. Key Contributions: Besse led breakthroughs in non-destructive single-photon detection, deterministic remote entanglement, and loophole-free Bell inequality violations. His research enables error-corrected quantum communication protocols and scalable microwave quantum systems. Publications Trends: Recent articles emphasize modular quantum architectures, entanglement stabilization, and microwave photon engineering. Topics include cluster state generation, defect mode mitigation, and reinforcement learning for quantum feedback systems. Labs & Teams: Affiliated with the Laboratorium für Festkörperphysik at ETH Zürich, Besse contributes to advancing superconducting quantum technologies and microwave quantum optics.

Maarten de Hoopمشاهده پروفایل

استاد

• Seismic Wave Analysis
• Inverse Problems
• Deep Learning
• +۵ مورد دیگر

Maarten de Hoop is the Simons Chair and Professor of Computational and Applied Mathematics at Rice University, part of the George R. Brown School of Engineering. He holds visiting roles at MIT and the Chinese Academy of Sciences. His research spans seismic wave analysis, inverse problems, deep learning, and planetary seismology. He earned his Ph.D. in Technical Sciences from Delft University of Technology (1992), and earlier degrees from Utrecht University. Notable awards include the 1996 J. Clarence Karcher Award and 2001 Fellowship from the Institute of Physics. His work integrates computational mathematics with geophysics, focusing on extracting signal information from large datasets, developing novel inverse scattering methods, and applying deep learning to geoscience challenges. Recent studies include transformer models for in-context learning, semialgebraic neural networks, and seismic waveform foundation models like SeisLM. He leads the Geo-Mathematical Imaging Group, fostering interdisciplinary projects in planetary missions and data-driven discovery.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +۵ مورد دیگر

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

• Fracture Mechanics
• Materials Science
• Solid Mechanics
• +۵ مورد دیگر

Professor Chunsheng Lu is a faculty member at Curtin University's School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He currently holds the position of Professor and serves as Editor-in-Chief of Mechanical Engineering Advances . His research focuses on fracture mechanics, multi-scale modeling, energy materials, nonlinear dynamics, and natural disaster risk analysis. Lu is actively involved in HDR (Masters/PhD) supervision, offering projects on advanced materials modeling and simulations. His research interests include mechanics of energy materials, multi-scale modeling, and fracture statistics. He has contributed to over 200 publications, with recent work emphasizing piezoelectric semiconductors, nanomaterials, and energy storage systems. Lu's teaching spans materials engineering, solid mechanics, and numerical methods.

Henry Yuenمشاهده پروفایل

دانشیار

• Quantum Computing
• Complexity Theory
• Cryptography
• +۲ مورد دیگر

Henry Yuen is the Srivani Family Associate Professor of Computer Science at Columbia University, with affiliations in the CS Theory group, Data Science Institute, and Columbia Quantum Initiative. His work bridges theoretical computer science and quantum information, focusing on the computational foundations of quantum systems. Yuen received his BA in Mathematics from the University of Southern California (2010) and PhD in Computer Science from MIT (2016). His research explores quantum complexity theory, quantum cryptography, and quantum information through both theoretical frameworks and practical applications. His recent publications reveal a strong focus on quantum pseudorandomness, quantum circuit complexity, and quantum cryptographic primitives. The research trajectory demonstrates increasing sophistication in connecting quantum computational models with fundamental questions in complexity theory, particularly through the lens of quantum interactive proofs and quantum state complexity. His work frequently intersects with operator algebras and quantum information theory, reflecting the interdisciplinary nature of modern quantum computing research. NSF CAREER award Sloan Fellowship Yuen actively mentors graduate students, with several PhD students having graduated to postdoctoral positions or faculty roles. His service includes co-organizing the Columbia CS Theory Seminar and serving on program committees for major conferences including QIP, STOC, and ITCS. He has organized multiple workshops on quantum computing challenges and cryptography. As a member of the Columbia Quantum Initiative, Yuen contributes to Columbia's growing quantum ecosystem, collaborating across departments to advance both theoretical foundations and potential applications of quantum information processing.