جستجوی استاد راهنمای دانشگاهی

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

Fatma Kılınç-Karzan is an Associate Professor of Operations Research at Carnegie Mellon University's Tepper School of Business, with a courtesy appointment as Associate Professor of Computer Science. She is also affiliated with the Algorithms Combinatorics and Optimization (ACO) PhD Program and was a Visiting Scientist at Berkeley's Simons Institute for the Theory of Computing during Fall 2017. Her educational background includes a PhD from Georgia Institute of Technology's H. Milton Stewart School of Industrial & Systems Engineering with a minor in Mathematics, supervised by Prof. Arkadi Nemirovski. She earned her B.S. and M.S. degrees from the Industrial Engineering Department of Middle East Technical University with a minor in Information Systems. Dr. Kılınç-Karzan's research spans mathematical optimization with emphasis on convex and non-convex optimization theory, algorithms, and applications. Her work bridges theoretical foundations with practical implementations in optimization under uncertainty (robust optimization, chance constraints, distributionally robust optimization), machine learning (preference learning from limited data), and business analytics. She develops foundational theory for large-scale optimization problems with applications in decision making under uncertainty and high-dimensional statistical inference. Analysis of her recent publications reveals a strong focus on convex hull characterizations, semidefinite programming relaxations, distributionally robust optimization, and online convex optimization frameworks. Her work demonstrates increasing integration of optimization theory with machine learning applications, particularly in developing data-driven approaches for decision making under uncertainty. NSF CAREER Award (2015) INFORMS Optimization Society Young Researcher Prize (2015) INFORMS Junior Faculty Interest Group (JFIG) Best Paper Award (2014) BP Junior Faculty Chair (2014-2015) Faculty Giving Chair (2012-2013) Wimmer Fellowship (2012-2013) Dr. Kılınç-Karzan has successfully mentored numerous PhD students who have received prestigious awards, including the 2021 INFORMS Optimization Society Best Student Paper (1st prize) and multiple honorable mentions. Her research has been supported by significant grants including an NSF CAREER Award, an ONR grant (with S. Küçükyavuz), and an AFOSR grant. She serves on editorial boards for Mathematical Programming, Operations Research, Mathematics of Operations Research, and other leading journals, and has held leadership positions in professional societies including the Mathematical Optimization Society and INFORMS Computing Society. Through her affiliations with CMU's Tepper School, Computer Science Department, and ACO Program, she collaborates across disciplines to advance optimization theory and its applications. Her professional service includes committee chair roles for major INFORMS competitions and program committee leadership for international optimization conferences.

• Mathematical Optimization
• Convex Optimization
• Non-convex Optimization
• +۷ 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.

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

Kuldeep S. Meel is the Stephen Fleming Early-Career Associate Professor at the School of Computer Science, Georgia Institute of Technology, and an Associate Professor at the University of Toronto (on leave). He previously held a NUS Presidential Young Professorship at the National University of Singapore. His research focuses on automated reasoning, aiming to enable computing systems to handle uncertain real-world environments through scalable techniques integrating randomized algorithms, statistical inference, formal methods, distribution testing, and software engineering. Core research areas: Automated Reasoning, Formal Methods, Approximate Model Counting, Probabilistic Inference, Constraint Solving His research group has achieved significant recognition in both individual awards and publications. Key trends in his recent work include advancing model counting algorithms, developing frameworks for probabilistic explanations, and improving scalability in formal verification and constraint satisfaction. His tools have consistently ranked top in international competitions, demonstrating practical impact in automated reasoning. 2019 NRF Fellowship for AI 2022 ACP Early Career Researcher Award 2020 IEEE Intelligent Systems AI's 10 to Watch Top placements in Model Counting, SAT, and CAV competitions He mentors a diverse group of PhD and Master's students and collaborates with institutions worldwide. His group's publications span premier conferences in AI, formal methods, and design automation, reflecting interdisciplinary contributions to theoretical and applied computer science.

• Automated Reasoning
• Formal Methods
• Artificial Intelligence
• +۶ مورد دیگر

Joseph Eremondi is an Assistant Professor in the Department of Computer Science at the University of Regina, Faculty of Science, Canada. He began his tenure in 2024 after serving as a Royal Society Newton International Fellow at the University of Edinburgh, where he conducted postdoctoral research with Ohad Kammar in the Laboratory for Foundations of Computer Science. He earned his PhD from the University of British Columbia (UBC) under the supervision of Ron Garcia at the UBC Software Practices Laboratory. His research is centered on programming languages theory, with a strong focus on type systems that enhance software reliability and usability. He is particularly known for his work in dependent types, gradual typing, and the integration of both paradigms. His research interests include: Dependent pattern matching and its semantic foundations Gradual dependent types and approximate normalization Error message generation and usability in dependently typed languages Static analysis using set constraints and SMT solvers Theoretical properties of reversal-bounded counter automata and shuffle operations His recent publications, appearing in premier venues like POPL, ICFP, and CPP, reflect a consistent trajectory toward making advanced type systems more accessible and practical. Key themes include coverage semantics for dependent pattern matching, formal models of gradual dependent typing, and improving the developer experience through better tooling and error diagnostics. Notable scientific recognitions include the NSERC Discovery Grant (awarded in 2025) and the prestigious Royal Society Newton International Fellowship. These awards underscore the impact and promise of his research program on the usability of dependently typed programming languages. Joseph is actively mentoring and recruiting graduate students, particularly in areas such as dependently typed programming (Lean, Agda, Idris, Coq), gradual typing, live programming environments, and static analysis. He emphasizes close collaboration within a small, focused research group. He has also served on program committees, including for TyDe and POPL Artifact Evaluation, demonstrating active engagement in the programming languages community. His work bridges theoretical rigor with practical implementation, evident in his artifact releases on GitHub and integration with tools like Ott and DrRacket. He maintains a personal website and open-source repositories that support reproducibility and community involvement.

• Programming Languages
• Type Theory
• Dependent Types
• +۱۲ 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

Raphael Hauser is an Associate Professor in Numerical Mathematics at the University of Oxford's Mathematical Institute, Director of Graduate Studies - Teaching, and Tanaka Fellow in Applied Mathematics at Pembroke College. His affiliations include membership in the Data Science, Numerical Analysis, and Mathematical and Computational Finance research groups, as well as a fellowship at the Alan Turing Institute. Education: PhD in Operations Research, Cornell University, Ithaca, USA Dipl. Math. ETH, Swiss Federal Institute of Technology (ETH Zurich), Switzerland Research interests span data science, numerical optimisation, medical imaging, distributed computing, and applied probability/statistics. His work integrates mathematical rigor with practical applications, particularly in optimization algorithms, machine learning theory, and medical imaging technology. Publications focus on optimization theory, stochastic processes, medical imaging systems, and computational finance, with recurring themes in non-convex optimization guarantees, PCA variants, and X-ray tomography innovations. Awards: Oxford University Teaching Award (2007) SIAM Optimization Prize (2005) SIAM Student Paper Prize (2000) Advising includes 15+ DPhil students and 40+ MSc students, with projects in optimization, finance, imaging, and machine learning. Current postdocs and students are affiliated with the Alan Turing Institute and industrial partners like Siemens and Macquarie Group. He leads teams in the Mathematical Institute's research groups and collaborates with the Alan Turing Institute on large-scale data science initiatives.

• Data Science
• Numerical Optimisation
• Medical Imaging
• +۳ مورد دیگر

Prof. Dr. Ieke Moerdijk is a distinguished Professor of Mathematics at the Mathematical Institute of Utrecht University, part of the Faculty of Science. Previously, he held positions at Radboud University (2011–2016) and has been affiliated with institutions like the University of Chicago, Cambridge, and the University of Amsterdam, where he earned his PhD in Mathematics (1985, Cum Laude). His research focuses on algebraic and differential topology, homotopy theory, and applications of topological structures to mathematical logic. He is renowned for co-authoring influential books such as Sheaves in Geometry and Logic (with S. Mac Lane) and Introduction to Foliations and Lie Groupoids (with J. Mrcun). Moerdijk has received prestigious awards including the Spinoza Prize (2012) and the Descartes-Huygens Prize (2011), and is a member of the KNAW and Academia Europaea. His current research emphasizes the theory of dendroidal sets and homotopy operads. He has held visiting positions at institutions like Cambridge, McGill, and Sydney. His academic contributions span editorships, teaching, and supervising numerous students. Moerdijk’s work bridges foundational mathematics with advanced categorical and topological frameworks, influencing areas from algebraic geometry to logic. Education: Bachelor’s/Master’s in Mathematics, Philosophy, and Linguistics at University of Amsterdam PhD in Mathematics, University of Amsterdam (1985) Awards: Spinoza Prize (2012), Descartes-Huygens Prize (2011) Member of KNAW (2006), Academia Europaea (2014) Huygens Fellowship (1986), PIONIER Grant (1995) Research Interests: Algebraic topology, homotopy theory, operads, category theory, and mathematical logic. Moerdijk’s publications include foundational works on dendroidal sets and simplicial methods, with recent contributions addressing ∞-operads and univalent completion. His research often explores connections between algebraic structures and topological spaces, with applications to higher category theory.

• Algebraic Topology
• Differential Topology
• Mathematical Logic
• +۳ مورد دیگر

Paata Ivanisvili is an Associate Professor at the University of California, Irvine (UCI), Department of Mathematics, School of Physical Sciences. His research focuses on Analysis, Probability, Harmonic Analysis, and Functional Analysis, with a particular emphasis on isoperimetric inequalities, functional inequalities, and discrete structures such as the Hamming cube. He has held visiting positions at institutions including the Hausdorff Research Institute for Mathematics and Princeton University. Ivanisvili has organized conferences such as the Dual Trimester Program at the Hausdorff Institute on Boolean Analysis in Computer Science (2024) and annual Summer/Fall Schools since 2021. He earned his PhD in Mathematics from Michigan State University (2015) and a BS from Saint Petersburg State University (2011). His research interests include sharp inequalities in analysis (e.g., Poincaré, Beckner, Ehrhard), hypercontractivity, and applications to discrete mathematics and probability. He has collaborated with prominent mathematicians such as Fedor Nazarov, Alexander Volberg, and Roman Vershynin. Notable awards include the NSF CAREER Award (2021–2025) and Simons Fellowship in Mathematics (2025–2026). Ivanisvili’s recent work explores the interface between harmonic analysis and discrete mathematics, including studies on additive energies, convex hulls of space curves, and learning theory. His articles frequently address foundational questions in geometric functional analysis, often using tools like Bellman functions and optimal control theory. He actively advises PhD students and has mentored visiting researchers at UCI.

• Analysis
• Partial Differential Equations
• Probability
• +۵ مورد دیگر

Thomas Lam is a professor of mathematics at the University of Michigan , specializing in algebraic combinatorics, total positivity, and connections to mathematical physics. His work bridges cluster algebras, positive geometry, and integrable systems, with applications to scattering amplitudes in quantum field theory. Lam has collaborated extensively with physicists such as Nima Arkani-Hamed and mathematicians like Pavlo Pylyavskyy and Mark Shimozono. Key research areas: Cluster algebras, total positivity, electrical networks, positroid varieties, and quantum cohomology. Notable contributions: Defining polypositroids, proving regularity theorems for totally nonnegative flag varieties, and establishing cluster structures in braid varieties. Recent work focuses on positive geometries , including the amplituhedron and moduli spaces of points on projective lines, with implications for particle physics. His articles often explore dual graded graphs, K-theoretic Schubert calculus, and the interplay between combinatorics and algebraic structures. Lam's research has been supported by NSF grants, including DMS-0748636 and DMS-1249708 .

• Algebraic Combinatorics
• Total Positivity
• Cluster Algebras
• +۵ مورد دیگر

Prof. Dennis Komm is an Associate Professor at ETH Zurich's Department of Computer Science, leading the group for Algorithms and Didactics. He chairs the Center for Computer Science Education (ABZ) and serves on committees such as the Swiss Maturity Board (Schweizerische Maturitätskommission) and the STEM Commission of the Swiss Academies. Previously, he held roles at RWTH Aachen University (Master's, 2008), ETH Zurich (PhD, 2012), University of Zurich (external lecturer, 2014–2020), and PH Graubünden (including department head and professor of 'Fachdidaktik Informatik'). Education: He completed a Master's in Computer Science at RWTH Aachen (2008), a PhD at ETH Zurich (2012), and studies in Information Technology at Queensland University of Technology (2006). His academic journey includes visiting roles at King's College, Stanford, and Comenius University. He has taught extensively across institutions, emphasizing Python and LOGO-based approaches for beginners. Research focuses on algorithm design, approximation algorithms, reoptimization, and advice complexity in theoretical CS. His work in education explores computational thinking, programming pedagogy (especially for K–12), and interdisciplinary approaches (e.g., robotics in math). Recent trends in his articles highlight advancements in online algorithms, optimization under dynamic conditions, and initiatives to integrate CS into Swiss school curricula sustainably. He actively promotes CS education through platforms like WebTigerPython and collaborates on projects such as CyberQuest and MINTerlink. His outreach includes organizing conferences (e.g., STIU 2025) and workshops on programming and cybersecurity for teachers and students. Despite no listed scientific awards, his contributions to education and theoretical CS are recognized through editorial roles in journals like Informatics in Education and contributions to the TigerJython Group. Grant-related advising includes co-supervising doctoral theses on robotics, USOs, and programming didactics. He advocates for equitable educational opportunities via the Passerelle exam and the Swiss Beaver Competition. His team's work spans teacher training, didactic certifications, and bridging university-school collaborations through initiatives like MINTerlink. Labs and teams: Head of ABZ (ETH's CS education center), collaborator with the Computational Robotics Lab, and part of the TigerJython Group. He also co-organizes the Colloquium on Mathematics, Computer Science, and Education with ETH's Mathematics Department.

• Algorithm Design and Analysis
• Computer Science Education
• Theoretical Computer Science
• +۳ مورد دیگر

Kazushi Ueda is an Associate Professor at the Graduate School of Mathematical Sciences, The University of Tokyo, where he has been since April 2015. His research spans algebraic geometry, symplectic geometry, and mathematical physics, with a focus on homological mirror symmetry and its applications to moduli spaces, Calabi-Yau manifolds, and singularities. He previously held academic positions at Osaka University from 2006 to 2015, including roles as Assistant Professor and Associate Professor. Ueda has also had visiting appointments at institutions such as the University of Oxford, Max Planck Institute for Mathematics, and Korea Institute for Advanced Study. Bachelor of Science, Kyoto University (1997-2001) Master of Science, Kyoto University (2001-2003) Doctor of Science, Kyoto University (2003-2006) Ueda's research explores the deep interplay between complex and symplectic geometry through mirror symmetry, particularly in the context of Calabi-Yau varieties, toric degenerations, and dimer models. His work addresses derived categories, stability conditions, and moduli problems, with recent contributions to noncommutative algebraic geometry and applications in mathematical physics. He has collaborated extensively with researchers like Akira Ishii, Masahiro Futaki, and Shinnosuke Okawa. His publications highlight homological mirror symmetry for K3 surfaces, Grassmannians, and singularities, as well as studies on modular forms, cluster transformations, and the Grothendieck ring. Ueda is a member of the Mathematical Society of Japan and has contributed to educational programs, including graduate lectures on mirror symmetry and symplectic geometry.

• Algebraic Geometry
• Symplectic Geometry
• Mathematical Physics
• +۱ مورد دیگر

Chee-Wooi Ten is a tenured Professor in the Department of Electrical and Computer Engineering at Michigan Technological University, where he has served since 2010 and achieved tenure in 2016. He concurrently holds an Affiliated Professor appointment in Applied Computing and directs both the PSERC Site and ICC CPS Center. His institutional roles emphasize cyber-physical security integration within power infrastructure. His educational background includes: PhD in Electrical Engineering from University College Dublin (2009) MSc in Electrical Engineering from Iowa State University (2001) BSc in Electrical Engineering from Iowa State University (1999) Ten's research pioneers cyber-informed security engineering strategies for bulk power systems, focusing on quantifying rare events through system risk models and data science. His work bridges power grid interactions with robotics and transportation systems to advance decarbonization and electrification. Key methodologies include validating cyber-physical security frameworks against steady-state and dynamic grid approaches, with emphasis on attack/defense combinatorics and smart home technologies. This transdisciplinary approach supports the fourth industrial revolution's resilience requirements. His publication trends reveal strong focus on risk-aggregated substation testbeds using generative adversarial networks, cyber insurance models for power systems, and cascading failure analysis from switching attacks. Recent works increasingly integrate machine learning with physics-based modeling to address cybersecurity threats in inverter-based resource integration and distribution emergency operations. Ten has secured over $6.5M in active funding including: $2M DOE grant (MTU portion $105,000) for CyDERMS Center on DERs/Microgrids cybersecurity $704,409 CyManII award for secure digitalization in smart manufacturing $1.05M DOE ARPA-E grant for decarbonized freight transportation modeling NSF CyberCorps Scholarship for Service program ($3.38M) His grants consistently address risk management through data-driven and physics-based modeling, with industry partnerships through PSERC and utility collaborations. As ICC CPS Center Director, he leads research on cyber-physical security testbeds and coordinates the PSERC Summer Transformation School. His team develops validation frameworks for NERC CIP compliance while addressing practical pain points in OT cybersecurity for grid operators.

• Power systems engineering
• Power grid cybersecurity
• Cyber-informed security engineering
• +۴ مورد دیگر

Gene Cooperman is a Professor at the Khoury College of Computer Sciences at Northeastern University, with an affiliation in the College of Engineering. His research focuses on high-performance computing (HPC), transparent checkpoint-restart systems, and model checking. He leads the High Performance Computing Laboratory, where he explores checkpointing technologies like DMTCP, MANA for MPI, and CRAC for CUDA, aiming to enhance HPC workflows on supercomputers such as NERSC's Perlmutter. His work bridges distributed computing, parallel algorithms, and system software to address challenges in fault tolerance, scalability, and resource management. Cooperman has advised 10 PhD students and co-authored over 125 refereed publications, contributing to projects like Geant4-MultiThreaded and Roomy for disk-based computation. His teaching includes courses on computer systems and HPC seminars. Education: Background in computational algebra and parallel computing, transitioning to HPC systems and checkpointing. Research Themes: Transparent checkpointing, MPI agnostic solutions, CUDA integration, and HPC resource optimization. Recent articles emphasize MPI checkpointing, reversible debugging (FReD), and CUDA support, reflecting trends in distributed and GPU-accelerated systems. His grants include NSF, NERSC/DOE, and MemVerge funding. Cooperman collaborates with institutions like CERN and NERSC, advancing applications in particle physics simulations and supercomputing. Current students include Aayushi Gautam, Jiajun Cao, Rohan Garg, and Twinkle Jain.

• High-Performance Computing
• Computer Systems
• Transparent Checkpointing
• +۴ مورد دیگر

Joachim Rosenthal is a Professor of Applied Mathematics at the University of Zurich's Department of Mathematics, leading the Applied Algebra Group. His research integrates coding theory, cryptography, and algebraic geometry with applications in communications and security systems. His primary research explores algebraic coding theory including convolutional codes, subspace codes, and post-quantum cryptography. He develops algorithms for error correction, code optimization, and cryptographic protocol analysis, with emphasis on mathematical structures in finite fields and rings. Professor Rosenthal serves as President of the Swiss Mathematical Society (2024-2025) and sits on IEEE Information Theory Society's Board of Governors. He has organized multiple international conferences on coding theory and cryptography, including the Zurich COST Meeting and Workshop on Convolutional Codes. His editorial contributions include roles at Archiv der Mathematik and SIAM Journal on Applied Algebra and Geometry. Recent publications focus on code construction methods, complexity analysis in group-based cryptography, and algebraic approaches to error-correcting codes.

• Coding Theory
• Cryptography
• Algebraic Geometry
• +۲ مورد دیگر