جستجوی استاد راهنمای دانشگاهی

Kaiming He is an Associate Professor with tenure in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), holding the Douglas Ross (1954) Career Development Professor of Software Technology chair. He also works part-time as a Distinguished Scientist at Google DeepMind. Prior to joining MIT in 2024, he was a research scientist at Facebook AI Research (FAIR) from 2016 to 2024, and a researcher at Microsoft Research Asia (MSRA) from 2011 to 2016. Dr. He received his PhD from the Chinese University of Hong Kong in 2011 and his Bachelor of Science from Tsinghua University in 2007. His academic journey reflects a strong foundation in computer science and engineering that has led to transformative contributions in artificial intelligence. His research primarily focuses on computer vision and deep learning, with pioneering work on deep residual networks (ResNets), visual object detection and segmentation, and self-supervised learning. He is best known for his work on Deep Residual Networks (ResNets), recognized as the most-cited paper of the twenty-first century. The residual connections he pioneered are now fundamental components in modern deep learning architectures including Transformers, AlphaGo Zero, AlphaFold, and various generative AI models. His recent publications demonstrate continued innovation across generative models, transformer architectures, and cross-disciplinary AI applications. His work bridges theoretical advances in neural network design with practical implementations that address real-world challenges in physics, biology, and other scientific domains. PAMI Young Researcher Award (2018) Best Paper Award, CVPR (2009, 2016) Best Paper Award, ICCV (2017) Best Student Paper Award, ICCV (2017) Everingham Prize, ICCV (2021) Most-cited paper of the twenty-first century Dr. He advises graduate students including Jake Austin, Xingjian Bai, and Mingyang Deng, and teaches advanced courses such as "6.S978: Deep Generative Models" (Fall 2024) and "6.8300/6.8301: Advances in Computer Vision" (Spring 2024). His research group actively explores how AI can serve as a unifying framework across scientific disciplines, breaking down traditional barriers between fields through shared methodologies and tools.

• Computer Vision
• Deep Learning
• Machine Learning
• +۶ مورد دیگر

Stanislav Smirnov is a Professor of Mathematics at the University of Geneva, where he has been a faculty member since 2003. He also holds a part-time position at the Chebyshev Laboratory of St. Petersburg State University. As Director of the National Centre of Competence in Research SwissMAP since 2014, he leads a major research initiative funded by the Swiss National Science Foundation. His education includes a mathematics degree from St. Petersburg State University (1992) and a PhD from the California Institute of Technology (1996). Prior to joining Geneva, he held positions at Yale University, the Institute for Advanced Study in Princeton, the Max Planck Institute in Bonn, and the Royal Institute of Technology in Stockholm. Professor Smirnov's research focuses on the mathematical foundations of statistical physics, with particular emphasis on conformal invariance in two-dimensional lattice models. His work has revolutionized our understanding of critical phenomena through rigorous mathematical approaches, establishing deep connections between probability theory, complex analysis, and statistical mechanics. He develops novel discrete complex analysis techniques to prove continuum limits of lattice models at criticality. His publication record shows consistent advancement in understanding random planar geometry, percolation theory, and the Ising model, with increasing attention to Liouville quantum gravity in recent years. His work bridges deep mathematical analysis with physical insights, often providing rigorous proofs for phenomena previously understood only through physical intuition. Fields Medal (2010) for the proof of conformal invariance of percolation and the planar Ising model in statistical physics As an advisor, Professor Smirnov has mentored doctoral students including Ekin Arikök and Nikolai Bobenko. He leads the ANALYSE, PHYSIQUE MATHÉMATIQUE ET PROBABILITÉS research group at the University of Geneva. His research is supported by major grants including the NCCR SwissMAP, European Research Council's AG COMPASP, and Swiss National Science Foundation grants 200020_143434 and 200020_141329. Professor Smirnov has organized numerous influential conferences, including the "Conformal maps from probability to physics" workshop at Monte Verità (2010) and multiple "Random Planar Geometry" meetings in Les Diablerets, fostering collaboration between mathematicians and physicists working on critical phenomena and random geometry.

• Mathematical Physics
• Statistical Physics
• Probability Theory
• +۴ مورد دیگر

Ali Yazdani is an Adjunct Professor at the University of Illinois Urbana-Champaign's Grainger College of Engineering, Department of Physics, and Director of the Princeton Center for Complex Materials at Princeton University. His research focuses on quantum condensed matter physics, leveraging scanning tunneling microscopy (STM) and spectroscopy to explore novel quantum phases in materials such as graphene, twisted bilayer graphene, and topological insulators. Key achievements include the first direct observation of Hofstadter's fractal energy spectrum in quantum materials (2025), studies on Majorana fermions in atomic chains, and investigations into strongly correlated Chern insulators. His work bridges theoretical predictions with experimental validation, emphasizing quantum materials' topological and correlated properties. Affiliations: Princeton University, Department of Physics; University of Illinois Urbana-Champaign, Grainger College of Engineering. Research Themes: Quantum fractals, topological insulators, superconductivity, Majorana fermions, moiré materials. Research Summary: Dr. Yazdani’s lab employs advanced STM techniques to visualize electronic wavefunctions and study correlated phases. Notable projects include: - Visualization of Hofstadter’s butterfly in twisted bilayer graphene. - Discovery of valley skyrmions in graphene quantum Hall ferromagnets. - Unconventional superconductivity in magic-angle graphene. - Development of methods to detect Majorana zero modes. Labs/Teams: Yazdani Lab at Princeton University focuses on quantum materials and topological phases, collaborating with theorists and experimentalists globally.

• Condensed Matter Physics
• Quantum Fractals
• Topological Insulators
• +۵ مورد دیگر

Ewain Gwynne is a Professor of Mathematics at the University of Chicago, affiliated with the Committee on Computational and Applied Mathematics (CCAM) and the Statistics Department. He previously held postdoctoral positions at the University of Cambridge and earned his Ph.D. from MIT in 2018 under Scott Sheffield. His research focuses on probability theory, particularly random geometric structures in statistical mechanics, including Schramm-Loewner evolution (SLE), Liouville quantum gravity (LQG), and random planar maps. Education: Ph.D. in Mathematics, MIT (2018); M.Sc., MIT (2015); B.Sc., Northwestern University (2013). Research Interests: Random geometric objects in statistical mechanics Liouville quantum gravity and its metric properties Random planar maps and their scaling limits SLE and its relationship with LQG Random walks on random planar maps Percolation and permutons His recent articles explore topics such as supercritical LQG, Gaussian curvature on random maps, and harmonic balls in LQG. He has advised multiple Ph.D. students and serves as an associate editor for Probability and Mathematical Physics . His work bridges probability theory, geometry, and mathematical physics, with applications to understanding critical phenomena in random systems.

• Probability Theory
• Liouville Quantum Gravity
• Random Planar Maps
• +۷ مورد دیگر

Johnny Golding is a Professor at the Royal College of Art (RCA), School of Arts & Humanities. His career spans roles such as Director of the Centre for Fine Art Research at Birmingham City University, Professor of Philosophy in the Visual Arts & Communication Technologies (2000–2012), and honorary Professorship in Philosophy and Imaging at Dundee School of Art (2009). Born in New York, he holds a PhD from the Universities of Toronto and Cambridge. Education : - PhD in Philosophy from the Universities of Toronto and Cambridge. - Earlier studies in Toronto and New York. Research Interests : Golding’s work explores post-Newtonian analytics, new materialisms, and the erotics of sense as 'radical matter.' His interdisciplinary approach bridges art, philosophy, and 'wild sciences' like AI, robotics, and quantum theory. Key themes include data proliferation's societal impact, emergent systems, and the interplay between art and technology. Recent Articles & Projects : Focus on Data Loam (2020), exploring future knowledge systems through art and science collaborations. Recent works address radical empathy, distributed intelligence, and the ethics of AI. His 2018 opera Entanglement: The Opera and installations like Of The Thick and the Raw exemplify his practice-led philosophy. Grants & Leadership : - Led the Data Loam project (FWF-PEEK funded), involving over 20 artists and scholars. - PI for AiDesign Labs on generative AI at RCA. Labs & Collaborations : - Radical Matter Lab (2017–2018), a pedagogical experiment at RCA. - Collaborations with institutions like the University of Applied Arts Vienna and the British Library.

• Contemporary Philosophy
• Art Theory
• New Materialisms
• +۳ مورد دیگر

Dr. Arpit Dua is an Assistant Professor in the Department of Physics at Virginia Tech. Previously, he held positions including a joint Simons-IQIM postdoc at Caltech under Xie Chen and a PhD at Yale University under Meng Cheng and Liang Jiang. His research focuses on theoretical quantum information systems, with emphasis on quantum error correction, topological order, and integrating machine learning principles into physics frameworks. Education: PhD in Physics from Yale University, Postdoctoral research at Caltech. Research Interests: Quantum error correction (developing novel codes using conventional and machine learning methods), thermalization in topological systems, self-correcting models, and applying physics-based insights to AI architecture design. His current projects explore fault-tolerant protocols, fracton orders, and Floquet codes. Publications reflect contributions to topological codes, subsystem symmetries, and fracton physics. His work bridges quantum information theory with condensed matter physics.

• Theoretical Quantum Information Systems
• Quantum Error Correction
• Topological Order
• +۴ مورد دیگر

Shirshendu Ganguly is an Associate Professor in the Department of Statistics at the University of California, Berkeley. His research focuses on probability theory, statistical physics, and their applications, including percolation models, phase transitions, Markov chains, and random graphs. He holds a PhD in Mathematics from the University of Washington and has held postdoctoral positions at UC Berkeley. Ganguly has been recognized with the 2019 Sloan Research Fellowship. Education: PhD in Mathematics, University of Washington, 2011–2016 Miller Postdoctoral Fellow, UC Berkeley, 2016–2018 Research Interests: Probability Theory, Statistical Mechanics, Markov Chains, Random Graphs, Percolation Theory, Sparse Combinatorial Structures His work explores geometric and probabilistic phenomena in disordered systems, including polymer models, self-organized criticality, and random matrix theory. He has advised multiple PhD students and contributes to teaching advanced probability courses at Berkeley. Awards: 2019 Sloan Research Fellowship

• Probability Theory
• Statistical Mechanics
• Markov Chains
• +۳ مورد دیگر

Allan Greenleaf is Professor of Mathematics and Co-director of Graduate Studies at the University of Rochester's Department of Mathematics, School of Arts & Sciences. He received his AB/SM from the University of Chicago (1977) and PhD from Princeton University (1981), followed by an NSF Postdoctoral Fellowship at MIT. His research specializes in harmonic analysis and microlocal analysis applied to integral geometry and inverse problems. Recent work focuses on degenerate Fourier integral operators, X-ray transforms underlying CAT scanning, and transformation optics for invisibility/cloaking. Publications demonstrate consistent exploration of configuration sets, microlocal techniques in tomography/seismology, and quantum integrable systems. Awards: Sloan Research Fellowship (1990-91)

• Harmonic Analysis
• Microlocal Analysis
• Integral Geometry
• +۱ مورد دیگر

Hsueh-Chia Chang is the Bayer Professor of Chemical Engineering in the Department of Chemical and Biomolecular Engineering at the University of Notre Dame's College of Engineering. He also holds a concurrent faculty position in the Department of Aerospace and Mechanical Engineering. As Principal Investigator of the Chang Lab, he leads cutting-edge research in microfluidic and nanofluidic technologies for biomedical applications. Prof. Chang received his B.S. in Chemical Engineering from Caltech in 1976, followed by M.S. and Ph.D. degrees in Chemical Engineering from Princeton University in 1977 and 1980, respectively. His academic journey has established him as a leader in the field of microfluidics and biosensing technologies. Chang's research focuses on developing low-cost liquid biopsy nanotechnologies for cancer screening and therapy management. His lab specializes in microfluidic and nanofluidic research coupled with electrokinetics, optics, plasmonics and acoustics for biosensing applications. Key research areas include Electrokinetics & Biosensing, Optics & Plasmonics, Nanoelectrokinetics, and Droplet Microfluidics. The Chang Lab has developed innovative platforms that can isolate and sort tumor cells, exosomes, microvesicles, lipoproteins, and stress granules from blood samples, then lyse these structures to release RNA/protein biomarkers for detection and quantification. His recent publications reveal a strong focus on extracellular vesicle diagnostics, cancer biomarker detection, and point-of-care diagnostic technologies. The research spans multiple disciplines including oncology, cardiology, and neurology, with applications for pancreatic, liver, breast, ovarian, and lung cancers as well as myocardial infarction diagnosis. Fellow of American Institute of Medical and Biological Engineering (2025) Provost Research Achievement Award, Notre Dame (2024) Fellow of the National Academy of Inventors (2020) Lifetime Achievement Award, American Electrophoresis Society (2019) Fellow of the American Physical Society (1997) Presidential Young Investigator Award, NSF (1985) Prof. Chang has advised over 50 PhD students and postdocs who have gone on to prominent positions in academia and industry. His lab has secured significant funding and has commercialized several technologies through startups like Aopia Biosciences, which launched NanoEx at ISEV 2024. The Chang Lab maintains active collaborations with medical researchers for validating their diagnostic platforms against various cancers and cardiac conditions.

• Microfluidics
• Nanofluidics
• Electrokinetics
• +۵ مورد دیگر

Sean Carroll serves as the Homewood Professor of Natural Philosophy at Johns Hopkins University and holds External Faculty status at the Santa Fe Institute. His research bridges cosmology, quantum mechanics, and philosophy, focusing on foundational questions about spacetime emergence, quantum interpretation, and complexity across cosmic scales. Carroll earned his Ph.D. from Harvard University in 1993. His academic trajectory reflects deep engagement with theoretical physics and philosophical inquiry, culminating in his current named professorship at Johns Hopkins. Carroll's research centers on the intersection of physics and philosophy, with significant contributions to quantum foundations, cosmology, and the nature of emergence. He is a leading proponent of the many-worlds interpretation of quantum mechanics and has pioneered work on the thermodynamic arrow of time, quantum decoherence, and the fine-tuning of initial cosmic conditions. His recent investigations explore discretized quantum systems, holographic principles in gravity, and the philosophical implications of quantum gravity. Analysis of his 2022-2025 publications reveals a pronounced shift toward computational approaches in quantum gravity, with increasing emphasis on finite-dimensional Hilbert spaces and GPU-accelerated modeling. His work consistently integrates quantum information theory with cosmological questions, particularly examining how spacetime geometry emerges from quantum entanglement and how complexity evolves in closed systems. Carroll's scientific recognition includes: National Science Foundation Fellowship NASA Fellowship Sloan Research Fellowship Packard Fellowship Fellow of the American Physical Society American Institute of Physics Award Fellow of the Royal Society Guggenheim Fellowship Fellow of the American Association for the Advancement of Science His research has been sustained through major fellowships from NSF, NASA, Sloan, and Packard foundations, enabling interdisciplinary collaborations across physics and philosophy. Carroll actively mentors graduate students at Johns Hopkins and contributes to public discourse through his popular science books (including the Biggest Ideas in the Universe series) and the weekly Mindscape podcast. As Fractal Faculty at the Santa Fe Institute, Carroll participates in cross-disciplinary research on complex systems, exploring how emergent phenomena arise from fundamental physical laws. His work bridges theoretical physics with broader questions about complexity in biological, cognitive, and social systems.

• Cosmology
• Quantum Mechanics
• General Relativity
• +۴ مورد دیگر

Manfred Einsiedler is a Professor in the Department of Mathematics at ETH Zurich, Switzerland, with office HG G 64.2 at Rämistrasse 101, 8092 Zurich. He teaches undergraduate and graduate courses including Linear Algebra (HS 2019), Analysis I/II, and Functional Analysis I/II, using his co-authored textbook Functional Analysis, Spectral Theory, and Applications . His research centers on dynamical and equidistribution problems in homogeneous spaces, with focus on closed horocycle orbits, geodesic orbits on the modular surface, and measure rigidity. Key contributions include work on effective equidistribution, entropy methods, and connections between ergodic theory and number theory. He has co-authored foundational texts: Ergodic Theory with a view towards Number Theory and Functional Analysis, Spectral Theory, and Applications in Springer's Graduate Texts in Mathematics series, alongside multiple in-progress volumes on entropy, homogeneous dynamics, and unitary representations. Recent publications explore integer points on spheres, rigidity of invariant measures, and Diophantine approximation on fractals, emphasizing collaborations with Lindenstrauss, Ward, Margulis, and Venkatesh. His work demonstrates consistent focus on homogeneous dynamics with applications to arithmetic problems, particularly through effective methods and measure classification theorems. While no specific awards or student lists are documented in the source, his extensive publication record and textbook authorship establish significant scholarly impact.

• Dynamical systems
• Ergodic theory
• Homogeneous spaces
• +۴ مورد دیگر

Professor Victor Beresnevich of the University of York, Department of Pure Mathematics, is a leading researcher in Metric Number Theory and Diophantine Approximation . He leads the Number Theory Research Group and collaborates on problems involving algebraic numbers , manifold approximation , and ergodic theory . PhD and DSc from Minsk EPSRC-funded projects on Duffin-Schaeffer conjecture and rational points near manifolds Organiser of conferences on Diophantine approximation, dynamical systems, and quantum chaos His work connects Diophantine approximation with dynamical systems , fractal geometry , and p-adic analysis . Recent projects focus on inhomogeneous approximation and shrink targets problems . He supervises PhD students and mentors collaborations in analytic number theory and measure theory . Scientific Awards : Advanced Research Fellow Current PhD Student : Dorsa Vakilzadeh Hatefi

• Metric Number Theory
• Diophantine Approximation
• Geometry of Numbers
• +۷ مورد دیگر

Pavel Etingof is Professor of Mathematics at the Massachusetts Institute of Technology (MIT), Department of Mathematics, where he has been a distinguished faculty member for many years. He serves as the Chief Research Adviser of MIT-PRIMES, an all-year high school math research program that provides exceptional research opportunities for talented high school students. Additionally, he holds the prestigious position of Editor-in-Chief of Selecta Mathematica. Professor Etingof's research spans multiple advanced areas of pure mathematics with a particular focus on representation theory, tensor categories, Lie algebras, Hecke algebras, and algebraic structures. His work consistently bridges algebra, geometry, and mathematical physics, revealing deep connections between abstract algebraic structures and physical phenomena. His research has evolved to increasingly explore tensor categories in positive characteristic, connections between representation theory and fractal structures, and applications to quantum field theory. His recent publications (2021-2025) demonstrate continued productivity and innovation, with numerous papers on tensor categories in various characteristics, representation theory of Lie groups, and connections to mathematical physics. These works show sophisticated exploration of representation theory in prime characteristic, novel applications to quantum field theory, and deep investigations into the structure of tensor categories. Editor-in-Chief of Selecta Mathematica Chief Research Adviser of MIT-PRIMES Professor Etingof has mentored numerous Ph.D. students at MIT and other institutions, establishing a significant mathematical genealogy in representation theory. His teaching includes advanced courses on algebraic groups, Lie theory, representation theory, and specialized topics. He has also co-organized many student seminars on cutting-edge mathematical topics including Deligne categories, symplectic reflection algebras, quantum cohomology, and double affine Hecke algebras, fostering collaborative research environments for students and colleagues.

• Representation Theory
• Tensor Categories
• Lie Algebras
• +۴ مورد دیگر

David Simmons-Duffin is a Professor of Theoretical Physics at the California Institute of Technology (Caltech), where he has held positions since 2016. He is part of the Division of Physics, Mathematics and Astronomy, contributing to the Physics Department. His career progression includes roles as Visiting Associate (2016–17), Assistant Professor (2017–20), and Associate Professor (2020–21) before becoming full Professor in 2021. Education: A.B. and A.M. from Harvard University (2006), CASM from the University of Cambridge (2007), and Ph.D. from Harvard University (2012). His research focuses on conformal field theory (CFT), bootstrap methods, quantum field theory, and AdS/CFT correspondence. Key areas include precision computations in strongly coupled systems, critical phenomena, and applications to holography and quantum gravity. Research highlights include advancing the conformal bootstrap program, analyzing CFT data in 3D Ising models, and exploring connections between CFTs and gravitational theories. His work often bridges theoretical frameworks with numerical methods, yielding insights into operator product expansions (OPE), spectral gaps, and causality constraints. Affiliations include the Institute for Quantum Information and Matter (IQIM) and other Caltech research centers. His contributions have shaped modern approaches to understanding universality in critical systems and the geometric aspects of quantum field theories. Notable collaborations involve high-precision calculations, bootstrap island techniques, and studies of thermal QFT and light-ray operators. His work emphasizes interdisciplinary methods, combining analytic tools with computational advancements to tackle complex theoretical problems.

• Theoretical Physics
• Conformal Field Theory
• Bootstrap Methods
• +۵ مورد دیگر

William Sulis is an Associate Clinical Professor in the Department of Psychiatry and an Associate Member of the Department of Psychology at McMaster University, where he also directs the Collective Intelligence Lab (CILab). With a unique interdisciplinary background spanning mathematics, physics, and psychiatry, Dr. Sulis bridges the gap between theoretical science and clinical practice. His educational journey is exceptionally diverse: B.Sc. (Hon) in Mathematics with minor in Theoretical Physics, Carleton University (1976) M.D., University of Western Ontario (1980) M.A. in Mathematics, University of Western Ontario (1984) Ph.D. in Mathematics, University of Western Ontario (1989) FRCPC in Psychiatry (1984) Ph.D. in Theoretical Physics, University of Waterloo (2014) CRCPC in Geriatric Psychiatry (2015) Dr. Sulis's research explores the intersection of complex systems theory with psychological and psychiatric phenomena. His work on Collective Intelligence investigates how group dynamics emerge from individual interactions, while his research on Temperament and Psychobiology examines the continuum between normal personality variations and mental illness. He has made significant contributions to understanding Synchronization in Complex Systems and developed the concept of Transient Induced Global Response Synchronization (TIGoRS) , which has implications for neural coding and information processing. His theoretical work extends to Quantum Foundations and Process Algebra Theory , where he proposes novel approaches to quantum mechanics. Analysis of his recent publications reveals a consistent thread connecting complex systems theory with psychological and psychiatric applications. His work increasingly focuses on bridging the gap between temperament theory and clinical psychiatry, using mathematical and computational approaches to understand mental illness. Simultaneously, he continues to develop theoretical frameworks in quantum physics through process algebra models, demonstrating remarkable interdisciplinary range. Dr. Sulis has received several prestigious awards including The Governor General's Medal for having the highest overall grade point average in his graduating class, the Henry Marshall Tory Scholarship, and multiple Harry Stevenson Southam Scholarships. Throughout his career, Dr. Sulis has mentored numerous students across disciplines, supervising research projects spanning collective intelligence, semantic space modeling, network dynamics, and temperament studies. His Collective Intelligence Lab has served as a hub for interdisciplinary research connecting computer science, psychology, and psychiatry. Dr. Sulis has also been actively involved in professional organizations, serving as President of The Society for Chaos Theory in Psychology and the Life Sciences (1996-1998) and holding editorial positions for several journals including "Dynamical Psychology" and "Nonlinear Dynamics in Psychology and the Life Sciences." As Director of the Collective Intelligence Lab at McMaster University, Dr. Sulis fosters research exploring how complex adaptive systems can model cognitive and social phenomena. The lab serves as an intellectual nexus where mathematics, computer science, psychology, and psychiatry converge to address fundamental questions about intelligence, both individual and collective.

• Collective Intelligence
• Temperament and psychobiology of mental illness
• Collective Dynamics
• +۷ مورد دیگر