جستجوی استاد راهنمای دانشگاهی

Andrea Young is a Professor in the Department of Physics at the University of California Santa Barbara (UCSB), where they lead the Young Lab. The lab investigates quantum materials through nanofabrication and electronic measurement techniques. Affiliation: University of California Santa Barbara (Department of Physics) Research Interests: Andrea Young's work focuses on the interplay of symmetry, topology, and correlations in low-dimensional systems, particularly exploring superconductivity, magnetism, and fractionalization in graphene and van der Waals heterostructures . They utilize cryogenic measurements and heterostructure engineering to probe thermodynamic properties of these materials. Publication Trends: Recent articles emphasize twisted bilayer/trilayer graphene , moiré superlattices , and fractional quantum Hall effects , with keywords spanning condensed matter physics, quantum materials, and nanofabrication. Scientific Awards: Moore Foundation grant (2020) NSF fellowship (2020) CAREER award (2017) Advising: Andrea Young has advised PhD students such as Dr. Haoxin Zhou (2021) and Dr. Marec Serlin (2021). Their lab also supports research fellows like James Ehrets, who received an NSF fellowship in 2020. Labs & Teams: The Young Lab at UCSB specializes in creating van der Waals heterostructures and developing techniques like picosecond transport and nanoscale interferometry to study fragile electronic states.

• Quantum Materials
• Two-dimensional Systems
• Graphene
• +۷ مورد دیگر

Stefano Ermon is an Associate Professor in the Department of Computer Science at Stanford University, affiliated with the Artificial Intelligence Laboratory and a Senior Fellow at the Woods Institute for the Environment. His research focuses on advancing machine learning and generative AI techniques to address societal and environmental challenges, including computational sustainability, geospatial analysis, and climate science. He holds a Ph.D. from Cornell University (2015). Education: Ph.D. in Computer Science, Cornell University (2015). Research Interests: Ermon’s work bridges foundational machine learning (e.g., diffusion models, generative AI, and optimization) with applications in sustainability, geospatial analysis (via satellite imagery), and earth observation systems. Notable contributions include predicting poverty using satellite data and developing scalable methods for molecule generation. Articles Trends: His recent work emphasizes diffusion models for generative tasks (e.g., text-to-image, molecule design), geospatial AI (e.g., environmental monitoring), and ethical AI (e.g., bias mitigation in LLMs). He also explores applications in robotics and scientific computing. Awards: He has received prestigious awards, including the ICML 2024 Best Paper Award, Sloan Research Fellowship, Microsoft Research Faculty Fellowship, and the IJCAI Computers and Thought Award. Advising and Grants: Ermon teaches courses like Probabilistic Graphical Models (CS228) and has secured grants from NSF, ONR, AFOSR, and private foundations. His lab develops tools for climate science and sustainable development. Labs/Teams: Leads the Stanford AI Lab group focused on computational sustainability and generative AI, collaborating with institutions like the Woods Institute for environmental applications.

• Machine Learning
• Generative AI
• Computational Sustainability
• +۷ مورد دیگر

Zhi-Xun Shen is the Paul Pigott Professor in Physical Sciences at Stanford University, holding dual appointments in the Physics and Applied Physics Departments. He is a senior fellow at the Precourt Institute for Energy and serves on advisory boards for the Knight-Hennessy Scholars and Stanford Science Fellows programs. His research focuses on condensed matter and materials physics, particularly the electronic structures of superconductors, topological insulators, and novel materials. Dr. Shen pioneered advanced spectroscopic techniques, including photon-based imaging and scattering methods, and has authored over 600 publications with significant citation impact. His honors include the Kamerlingh Onnes Prize (2000), E.O. Lawrence Award (2010), and Oliver E. Buckley Prize (2011). He co-founded PrimeNano Inc., commercializing technologies from his lab, such as microwave impedance microscopy. His work bridges fundamental physics with energy-related applications, emphasizing the interplay between electronic structure and material properties. Dr. Shen’s research group explores cutting-edge topics like topological surface states, electron-phonon interactions, and superconductivity mechanisms. His inventions, such as non-resonance microwave imaging, have found applications in materials characterization. He remains active in advancing instrumentation and fostering interdisciplinary collaborations through his academic and industry roles.

• Condensed Matter Physics
• Materials Science
• Superconductivity
• +۴ مورد دیگر

Ravindra N. Bhatt is currently a Professor of Electrical and Computer Engineering at Princeton University and an associated faculty member in Physics. His academic career spans leadership roles at prestigious institutions, including Director of the Princeton Center for Complex Materials (1999-2005) and Acting Associate Director of the Princeton Center for Theoretical Science (2005-2012). He previously headed Theoretical Physics Research at Bell Laboratories. Ph.D., University of Illinois, Urbana, 1976 M.S., Physics, University of Illinois, Urbana, 1974 B.Sc. Hons., Physics, University of Delhi, India, 1971 Bhatt specializes in theoretical condensed matter physics, focusing on topological materials, quantum Hall effects, and spin-based quantum computation. His work explores disordered systems, many-body localization, and quantum dynamics in low-dimensional structures like graphene and semiconductor heterostructures. His recent publications emphasize topological phases, composite fermions, and critical ground state dynamics, employing methods such as Density Matrix Renormalization Group (DMRG) and Monte Carlo simulations. Key themes include disorder-driven quantum phase transitions and applications in quantum information science. Scientific honors include: Fellow, American Physical Society (1986) Guggenheim Fellowship (1995) Fellow, American Association for the Advancement of Science (2004) Bhatt has led major research centers at Princeton and contributed to quantum science initiatives. His group utilizes computational techniques like Transfer Matrix Methods and Sparse Matrix Diagonalization to study complex materials.

• Theoretical Condensed Matter Physics
• Quantum Materials Science
• Topological Materials
• +۴ 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

Shiyu Su is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on high-speed data converters, wireless transceivers, digital phase-locked loops (PLL), and AI-assisted analog/mixed-signal design automation. He holds a Ph.D. from the University of Southern California (2019) and teaches courses such as ECE 340 (Electronic Circuits 2) and ECE 432 (Radio Frequency Integrated Devices and Circuits). Education: B.S. from Beijing University of Post and Telecommunication (China) and Queen Mary, University of London (UK), 2011; M.S. and Ph.D. from USC, 2013 and 2019, all in electrical engineering. Research Interests: High-speed ADCs/DACs RF/mm-wave transceivers Time-approximation filters (TAF) Analog/mixed-signal design automation Memristor-based computing Biomedical interfaces Key Awards: IEEE SSCS Predoctoral Achievement Award (2017–2018) Best Student Paper Award at IEEE RFIC (2022) Ming Hsieh Institute Scholar (2019–2020) Lab Focus: The Shiyu Su Lab develops integrated circuits for communications, sensing, and computing, with a focus on AI-driven methodologies and digital-analog co-design. Collaborations include work with Prof. Wei Wu (USC) on memristor-based systems.

• High-speed data converters
• Wireless transceivers
• Digital phase-locked loops
• +۷ مورد دیگر

Alexei Kitaev is the Ronald and Maxine Linde Professor of Theoretical Physics and Mathematics at the California Institute of Technology (Caltech). His research focuses on quantum computation, topological quantum phases, anyons, topological insulators and superconductors, and the black hole information paradox. He has pioneered the concept of topological quantum computation, where quantum information is protected through topological properties of many-body systems. His recent publications explore quantum error correction, scrambling dynamics, and holographic principles in SYK-like models, reflecting his interdisciplinary impact on quantum physics, computer science, and condensed matter. His work on the Sachdev-Ye-Kitaev model has advanced understanding of quantum chaos and gravitational phenomena. Kitaev has received numerous accolades, including the MacArthur Award (2008), Breakthrough Prize in Fundamental Physics (2012), Dirac Medal (2015), and Oliver Buckley Condensed Matter Prize (2017). He has taught advanced courses such as 'Quantum Computation' and 'Advanced Condensed-Matter Physics' at Caltech. Scientific Awards: MacArthur Award (2008) Breakthrough Prize in Fundamental Physics (2012) Dirac Medal (2015) Oliver Buckley Condensed Matter Prize (2017)

• Quantum Computation
• Topological Quantum Phases
• Anyons
• +۴ مورد دیگر

Prof. Dr. Frank Pollmann is a Full Professor (W3) at the Department of Physics PH-I, Technical University of Munich (TUM), leading the Chair of Theoretical Solid-State Physics since 2022. His research focuses on condensed matter theory and quantum information concepts , particularly in systems of correlated electrons and quantum many-body dynamics . PhD: Max Planck Institute for the Physics of Complex Systems / TU Ilmenau (2006) Postdoc: UC Berkeley (2008-2010) Group Leader: MPIPKS Dresden (2011-2016) Associate Professor: TUM (2017-2022) His work spans topological phases , frustrated spin systems , and non-equilibrium quantum dynamics , utilizing tensor network methods and quantum information theory to study phenomena like many-body localization and Hilbert space fragmentation . His publications demonstrate trends in quantum scar states , Kardar-Parisi-Zhang hydrodynamics , and quantum transport anomalies . Scientific Awards : ERC Consolidator Grant (2017) Walter Schottky Prize (2015) Otto-Hahn Medal (2007) He teaches courses including Advanced Methods in Quantum Many-Body Theory , Solid State Theory , and Topology in Condensed Matter , while leading the Pollmann Group under the TUM School of Natural Sciences.

• Condensed Matter Theory
• Quantum Information Theory
• Correlated Electrons
• +۶ مورد دیگر

Meng Cheng is an Assistant Professor of Physics at Yale University, specializing in condensed matter theory. He holds a B.S. from Nanjing University (2008) and a Ph.D. in Condensed Matter Theory from the University of Maryland (2013). After a postdoctoral position at Microsoft Research Station Q (2013–2016), he joined Yale in 2017. His research focuses on quantum criticality, fractonic phases, and symmetric topological phases, with a particular emphasis on classification and characterization of exotic quantum matter. He has received prestigious awards including the NSF CAREER Award (2019) and the Alfred P. Sloan Fellowship (2019). Key research interests include topological superconductivity, global symmetry interactions, and applications in quantum information. His work bridges theoretical frameworks with experimental implications, exploring topics like Wilson loop operators, disorder operators, and entanglement entropy in gapless systems. He has contributed to advancements in understanding symmetry-enriched topological phases and their surface topological order. Publications span high-impact journals and cover topics such as fractionalization in electronic insulators, quantum Hall effects, and topological stabilizer models. His talks highlight interdisciplinary approaches, including seminars at the Perimeter Institute and Université de Montréal on fractonic topological phases and infinite-component Chern-Simons theories. Awards and grants underscore his contributions to advancing theoretical physics, with a focus on fostering innovation in quantum materials and computational methods. Teaching and mentorship activities further his commitment to education within the Yale Physics Department.

• Condensed Matter Physics
• Quantum Criticality
• Fractonic Phases
• +۳ مورد دیگر

Yuan Cao is an Assistant Professor of Electrical Engineering and Computer Science at the University of California, Berkeley, since July 2024. He completed his BSc in Applied Physics at the University of Science and Technology of China (2014), followed by an MS (2016) and PhD (2020) in Electrical Engineering at MIT. Before joining Berkeley, he was a Junior Fellow at Harvard University (2021–2024). His research focuses on the electrical properties of low-dimensional materials and their applications via nanotechnology, including MEMS. Notable achievements include pioneering work on twisted graphene superconductivity, recognized as a Nature’s 10 highlight (2018) and Physics Breakthrough of the Year . He has received awards such as the Sackler Prize in Physics (2020), McMillan Award (2021), and NSF CAREER Award (2025). His research integrates experimental physics, nanofabrication, and low-temperature transport to explore novel quantum phenomena in 2D materials. Recent breakthroughs include the MEGA2D platform, an on-chip MEMS system enabling precise manipulation of 2D materials. Collaborations with Prof. Nguyen secured a $1M DARPA NIMBUS contract, and his NSF CAREER award funds studies on reconfigurable graphene superlattices. Education: PhD, Electrical Engineering, MIT (2020) MS, Electrical Engineering, MIT (2016) BSc, Applied Physics, USTC (2014) Awards: NSF CAREER Award (2025) Sackler Prize in Physics (2020) McMillan Award (2021) TIME 100 Next (2019) Grants & Funding: $1M DARPA NIMBUS Program Contract (2023) $810K NSF CAREER Award (2025) Prof. Cao’s lab actively recruits motivated graduate students and postdocs with expertise in 2D materials, MEMS, nanofabrication, or low-temperature physics. The lab is part of UC Berkeley’s College of Engineering, fostering interdisciplinary research at the forefront of quantum and nanoscale systems.

• Physical Electronics
• MEMS
• Low-Dimensional Materials
• +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.

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

David Goldhaber-Gordon is a Professor in the Department of Physics at Stanford University, specializing in nanoscale electron behavior and quantum effects. His research spans nanofabrication, materials growth, low-temperature measurements, and scanning probe techniques, focusing on materials like graphene, carbon nanotubes, and topological insulators. Harvard AB in Physics (1994) Harvard AM in History of Science (1994) MIT PhD in Physics (1999) His work explores electron organization and flow in nanoscale systems, emphasizing quantum effects and interactions. Research areas include twisted bilayer graphene, helical trilayer platforms, and topological insulator applications for quantum devices and energy technologies. Recent publications focus on strain effects in twisted graphene, moiré superlattice engineering, and quantum anomalous Hall integration. Themes include topological phases, correlated insulators, and metrology advancements. Co-founder and Director, Center for Probing the Nanoscale (NSF Center) Junior Fellow, Harvard Society of Fellows He teaches advanced physics labs, independent research, and dissertation courses at Stanford. His group collaborates with materials scientists, engineers, and chemists to develop novel electronic applications.

• Quantum Physics
• Nanotechnology
• Condensed Matter Physics
• +۳ مورد دیگر

Sergei Gukov is the John D. MacArthur Professor of Theoretical Physics and Mathematics at the California Institute of Technology (Caltech), where he has been a faculty member since 2005. He serves in the Division of Physics, Mathematics and Astronomy, with primary affiliation in the Department of Mathematics. His research bridges the fields of mathematics and theoretical physics, focusing on deep connections between geometry, topology, and quantum field theory. Gukov received his B.S. from Moscow Institute of Physics and Technology in 1997, followed by an M.S. and Ph.D. from Princeton University in 2001. He joined Caltech as an Associate Professor in 2005, was promoted to Professor in 2007, and was named the John D. MacArthur Professor in 2021. His research spans several interconnected areas at the frontier of mathematics and physics. A central theme is the exploration of quantum topology and its connections to mathematical physics. He has made significant contributions to the geometric Langlands program, gauge theory, and the categorification of knot and 3-manifold invariants. His recent work increasingly incorporates machine learning approaches to mathematical problems, reflecting his interest in the intersection of traditional mathematical research and modern computational techniques. Gukov's work often reveals deep connections between seemingly disparate areas of mathematics and physics, such as the relationship between Rozansky-Witten geometry and Coulomb branches in supersymmetric gauge theories. Gukov's publications demonstrate a consistent focus on the mathematical structures underlying quantum field theories and their topological implications. His recent work shows an increasing emphasis on computational approaches to mathematical problems, particularly through his interest in mathematics and machine learning. The recurring themes across his research include the application of physical insights to solve mathematical problems and the discovery of new mathematical structures through physical reasoning. He serves on the editorial boards of several prestigious journals including the Journal of Knot Theory and Its Ramifications, Communications in Mathematical Physics, and Letters in Mathematical Physics. Gukov is also active in the academic community, having delivered plenary talks at major conferences such as the First International Congress of Basic Science and presenting at String Math 2023 on the potential impact of AI on mathematical research. Gukov teaches Ma 146 ab, Introduction to Knot Theory and Quantum Topology, a course that reflects his research interests. He also runs a seminar on Mathematics and Machine Learning, held Tuesdays from 2-3pm in East Bridge Conference room 114, demonstrating his commitment to fostering interdisciplinary research at the intersection of mathematics and computational methods.

• Mathematics
• Machine Learning
• Quantum Topology
• +۹ مورد دیگر

Jin Ma is a Professor in the Department of Mathematics at the University of Southern California (USC), where he has served since 2007. He previously held professorships at Purdue University (1994–2008). His research focuses on stochastic analysis, stochastic differential equations, mathematical finance, and control theory. He directs USC's Mathematical Finance Program and serves on editorial boards for journals like Probability, Uncertainty and Quantitative Risk and SIAM Journal on Control and Optimization . Ma received his Ph.D. in Mathematics from the University of Minnesota (1992) and M.S./B.S. in Applied Mathematics from Fudan University (1985/1982). His work bridges theoretical stochastic analysis and applied domains like finance and insurance, with notable contributions to forward-backward SDEs and mean-field games. Research Highlights: Developed frameworks for stochastic control and backward SDEs in financial and insurance contexts. Advanced mean-field game models for limit order book dynamics and equilibrium analysis. Explored set-valued stochastic differential equations and their applications in risk management. Grants & Advising: Advised numerous graduate students in stochastic processes and mathematical finance. Research supported by NSF grants and industry collaborations.

• Stochastic Analysis
• Stochastic Differential Equations
• Stochastic Control Theory
• +۳ مورد دیگر

Michael Knap is an Associate Professor of Collective Quantum Dynamics at the Technical University of Munich (TUM), within the Department of Physics at the TUM School of Natural Sciences. His research group focuses on condensed matter theory, quantum many-body systems, and quantum simulation. Knap holds office in room 5101.01.037 at James-Franck-Str. 1, 85748 Garching b. München, and can be reached at michael.knap@ph.tum.de or +49 (89) 289 - 53777. Prof. Knap's research delves into the rich physics of quantum many-body systems, particularly exploring non-equilibrium dynamics and transport phenomena in ultracold quantum gases, interacting light-matter systems, and correlated quantum materials. His work spans multiple subfields including topological phases of matter, quantum simulation with trapped ions, fracton physics, and quantum computation. He develops novel numerical approaches based on quantum information theory and utilizes artificial intelligence and machine learning to tackle challenging problems in condensed matter physics. His group's research connects fundamental theoretical questions with experimental implementations in quantum simulators. The analysis of Prof. Knap's recent publications (2023-2025) reveals a strong focus on topological quantum matter, quantum simulation, and emergent phenomena in constrained quantum systems. His work frequently bridges condensed matter theory with quantum information science, as evidenced by publications on fracton hydrodynamics, higher-form symmetries, and quantum error correction. There's a clear progression toward increasingly complex quantum systems and connections to experimental implementations on quantum processors. His research shows significant interdisciplinary reach, connecting condensed matter physics with quantum computing and quantum information theory. ERC Consolidator Grant (2025) ERC Starting Grant (2019) Supervisory Award, TUM Department of Physics (2018) Promotio sub auspiciis Praesidentis rei publicae, Austria (2013) Prof. Knap has established a robust research program supported by prestigious European Research Council grants. His group actively collaborates with both theoretical and experimental groups worldwide, particularly in the quantum simulation community. He has supervised numerous students through Master's Seminars on Collective Quantum Dynamics covering topics like quantum simulation with trapped ions and theoretical quantum computation. His research has received significant attention, with several publications featured as Editors' suggestions and Research Highlights in leading journals. The Collective Quantum Dynamics group maintains strong connections with experimental quantum simulation efforts, particularly in the areas of ultracold atoms and trapped ion systems. Knap's theoretical work often provides frameworks for interpreting experimental results in quantum simulators, creating a productive feedback loop between theory and experiment. His group participates in collaborative research networks focused on advancing quantum simulation capabilities and understanding fundamental aspects of quantum many-body physics.

• Condensed Matter Theory
• Quantum Many-Body Systems
• Non-Equilibrium Quantum Dynamics
• +۵ مورد دیگر