جست‌وجوی استاد و پژوهشگر

Arijit Bishnuمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Randomized Algorithms
• Approximation Algorithms
• +۶ مورد دیگر

Arijit Bishnu is an Associate Professor at the Indian Statistical Institute in the Advanced Computing and Microelectronics Unit (ACMU). He has taught courses such as Design and Analysis of Algorithms , Randomized Algorithms , Computational Geometry , and Algorithms for Big Data over multiple years (2008–2025), focusing on theoretical and applied aspects of computer science. Research Interests: His work spans Theoretical Computer Science , Randomized and Approximation Algorithms , Computational Geometry , and Combinatorics . He explores problems in sublinear algorithms, streaming computation, geometric data analysis, and complexity theory. Publications: Recent papers include contributions to STOC 2025 , RANDOM 2025 , and APPROX 2024 , covering topics like property testing, triangle counting complexity, and streaming algorithms. Collaborations with researchers like Sourav Chakraborty, Gopinath Mishra, and Sayantan Sen highlight his interdisciplinary approach. Academic Leadership: He has co-organized research courses such as Approximation Algorithms and Topics in Algorithms and Complexity , emphasizing mentorship and knowledge dissemination in theoretical computer science. His comprehensive work integrates algorithmic innovation with rigorous mathematical analysis, advancing computational techniques for large-scale and geometric data.

Hamid Hezariمشاهده پروفایل

دانشیار

• Analysis
• Partial Differential Equations
• Spectral Geometry
• +۳ مورد دیگر

Hamid Hezari is an Associate Professor in the Department of Mathematics at the University of California, Irvine (UCI). He holds a PhD from Johns Hopkins University (2009) and was a CLE Moore Instructor at MIT (2009–2012), with a postdoctoral fellowship at the Mathematical Sciences Research Institute (MSRI) during 2010. His research focuses on analysis and partial differential equations, particularly semiclassical/microlocal analysis and its applications in spectral geometry and quantum chaos. Key research interests include spectral geometry, quantum chaos, inverse problems, and the analysis of eigenfunctions. He has published over 25 peer-reviewed articles in top journals such as the Annals of Mathematics, Journal of Spectral Theory, and Communications in Mathematical Physics. His work explores topics like spectral rigidity of geometric domains, nodal set properties, and Bergman kernel asymptotics. Teaching responsibilities at UCI include courses in analysis, partial differential equations, and graduate-level topics like microlocal analysis. He has been supported by grants and has contributed to collaborative research with leading institutions. No specific awards are highlighted in the provided texts, though his prolific publication record underscores his scholarly impact. Hezari’s research often bridges mathematical physics and pure analysis, with applications to understanding geometric and dynamical systems through spectral methods.

Grey Ballardمشاهده پروفایل

دانشیار

• Numerical Linear Algebra
• High Performance Computing
• Computational Science
• +۶ مورد دیگر

Dr. Grey Ballard is an Associate Professor in the Department of Computer Science at Wake Forest University . He earned a B.S. in Math and Computer Science (2006), M.A. in Math (2008) from Wake Forest, and PhD in Computer Science (2013) from the University of California, Berkeley. He was a Truman Fellow at Sandia National Laboratories before joining Wake Forest. Research Focus: Ballard develops communication-optimal algorithms for high-performance computing , particularly in tensor decompositions , symmetric matrix computations , and nonnegative matrix factorization . His work combines numerical linear algebra with parallel algorithm design to reduce data movement costs in distributed systems. Publications demonstrate expertise in communication lower bounds , randomized tensor rounding , and visualization tools for parallel algorithms. He has contributed software packages such as TuckerMPI , GentenMPI , and PLANC for large-scale data compression and clustering. Scientific Awards: Wake Forest Excellence in Research Award NSF CAREER Award SIAM Linear Algebra Prize Three Conference Best Paper Awards (SPAA, IPDPS, ICDM) C.V. Ramamoorthy Distinguished Research Award (UC Berkeley) ACM Doctoral Dissertation Award – Honorable Mention Teaching: Courses include Introduction to Computer Science , Numerical Linear Algebra , and Parallel Algorithms . He has developed educational tools using the Thread-Safe Graphics Library to visualize parallel dynamic programming and collective communication.

• Fault-Tolerant Distributed Algorithms
• Digital Integrated Circuits
• Topology
• +۷ مورد دیگر

Ulrich Schmid is a Full Professor and Head of the Research Unit for Embedded Computing Systems at TU Wien. He holds a position in the Faculty of Informatics and leads the department of Embedded Computing Systems (E191-02). His roles include Curriculum Coordinator for the Bachelor and Master programs in Computer Engineering, as well as the Excellence Program Bachelor with Honors. He is also the Chair of the Curriculum Commission for Computer Engineering and a Substitute Member of the Informatics Commission. His research focuses on fault-tolerant distributed algorithms, digital integrated circuits, and topology-based approaches to distributed systems. He coordinates major projects such as the FWF-funded DMAC (2019–2024) and ByzDEL (2020–2025), which integrate topological semantics and hybrid delay models for robust hardware design and distributed system analysis. Schmid has contributed to groundbreaking work in Byzantine fault tolerance, epistemic logic for system recovery, and real-time scheduling through collaborations with researchers like Chatterjee, Függer, and Rajsbaum. Notable awards include the 2018 Edsger W. Dijkstra Prize and the 2021 Principles of Distributed Computing Doctoral Dissertation Award. His research also bridges formal verification techniques with physical hardware implementations, exemplified by projects like HEX (a Byzantine-tolerant clock distribution system) and the Involution tool for timing analysis. Schmid actively contributes to academic governance, advancing rigorous education and research standards in computer engineering. His advising and grant work involve mentoring on fault-tolerant architectures and securing funding from agencies like FWF and the European Commission. Labs and teams under his leadership include the Embedded Computing Systems group, specializing in hardware-software co-design for dependable systems-on-chip, and collaborations with institutions like GSI Helmholtzzentrum and the University of Amsterdam.

• Formal Verification
• Probabilistic Systems
• Game Theory
• +۵ مورد دیگر

Krishnendu Chatterjee is a Professor at the Institute of Science and Technology Austria (IST Austria) , Department of Computer Science. His research spans formal verification, probabilistic systems, game theory, and evolutionary dynamics, with over 300 peer-reviewed publications in top venues such as DISC, AAAI, LICS, PNAS, Nature , and Journal of the ACM . His research focuses on developing theoretical foundations and practical algorithms for analyzing complex systems, including Markov decision processes, stochastic games, probabilistic programs, and evolutionary models. He has made significant contributions to topics such as reachability analysis, termination of probabilistic programs, synthesis of controllers, and evolutionary game dynamics. Chatterjee's work is highly interdisciplinary, bridging computer science, mathematics, and biology. He has collaborated extensively with leading researchers worldwide and has been involved in editorial roles and program committees for major conferences in formal methods and theoretical computer science.

Christian R. Proañoمشاهده پروفایل

استاد

• Macroeconomic theory
• Behavioral economics
• Monetary policy
• +۵ مورد دیگر

Christian R. Proaño is a Professor of Economics at Otto-Friedrich-Universität Bamberg, specializing in Macroeconomics and International Finance. He previously served as an Assistant Professor at The New School for Social Research (2010–2015) and as a Research Economist at the Institute for Macroeconomics and Economic Research (IMK) in Germany (2008–2010). His academic journey includes a PhD in Economics from Bielefeld University (2008) and studies at the Catholic University of Ecuador (PUCE). Education: PhD in Economics (Bielefeld University, 2008) Current Roles: Professor at Bamberg University, Vice-Chairman of Keynes Gesellschaft, Research Fellow at CAMA Research Focus: Behavioral macroeconomics, income distribution, financial cycles, and macroeconomic stability Proaño’s research integrates behavioral economics into macroeconomic frameworks, analyzing how heterogeneous expectations and psychological factors influence financial markets, monetary policy, and business cycles. His work on non-linear macroeconometrics and climate change economics explores systemic risks and policy design for sustainable growth. His recent publications highlight trends in financial cycle analysis, behavioral political economy, and inequality dynamics. Notable collaborations include studies on income inequality’s macroeconomic effects and agent-based modeling of financial stability. Scientific Awards: Research Fellow, Centre for Applied Macroeconomic Analysis (CAMA) Fellow, Euro Area Business Cycle Network (EABCN) Proaño supervises external doctoral candidates and contributes to academic governance via roles in the German Network for New Economic Dynamics (GENED) and the Computational and Financial Econometrics (CFE) Network.

• Cryptography
• Distributed Computing
• Secure Multi-Party Computation (MPC)
• +۷ مورد دیگر

Chen-Da Liu-Zhang is a Lecturer and Researcher at the Lucerne University of Applied Sciences and Arts, leading the Information Systems Lab and Blockchain Lab. He is also a Research Scientist at the Web3 Foundation. His academic journey includes a PhD from ETH Zurich (advised by Prof. Ueli Maurer), a master's degree from ETH Zurich, and dual bachelor's degrees in computer science and mathematics from Universidad Autónoma de Madrid. His research focuses on secure distributed systems, encompassing cryptography, distributed computing, multi-party computation (MPC), blockchain technology, consensus protocols, and quantum computing security. Key areas include asynchronous protocols, communication complexity, constructive cryptography, and network-agnostic security. Recent work emphasizes optimizing cryptographic broadcast protocols, achieving efficient MPC with linear communication, and advancing blockchain-related flooding protocols. He has contributed to over 40 publications in top venues like CRYPTO, EUROCRYPT, and TCC. His lab leadership positions reflect his role in bridging academic research with practical applications in distributed systems. Serving on program committees for CT-RSA 2025, S&P 2025, and Asiacrypt 2024 highlights his active role in the cryptography community. Notable collaborations include work with Prof. Vipul Goyal at Carnegie Mellon University and NTT Research.

• Algebraic Geometry
• Differential Geometry
• Geometric Complexity Theory
• +۴ مورد دیگر

Joseph Landsberg is the Owen Professor and Professor in the Department of Mathematics at Texas A&M University , affiliated with the College of Arts & Sciences . His research focuses on Algebraic Geometry, Differential Geometry, and their applications to computational complexity, particularly matrix multiplication and tensor analysis. He has contributed to geometric complexity theory, secant varieties, and the study of symmetric tensors. Education: Ph.D., Mathematics, Duke University, 1990 Habilitation, Université de Toulouse, 1997 B.Sc. and M.Sc., Brown University, 1986 Research Interests: Landsberg explores the geometry of tensors, matrix multiplication algorithms, and complexity theory. His work bridges algebraic geometry, representation theory, and computational problems, with applications in quantum computing and cryptography. Recent studies include secant varieties, border rank analysis, and symmetry exploitation in tensor networks. Grants & Awards: AF: Small grants (2022, 2018) for complexity theory and matrix multiplication research Labs & Affiliations: Affiliated with the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M. His work intersects with interdisciplinary teams in computational mathematics and theoretical physics.

• Optimization Theory
• Variational Analysis
• Bilevel Programming
• +۶ مورد دیگر

Zhang Jin is a Professor at the Department of Mathematics in the College of Science at Southern University of Science and Technology (SUSTech) since December 2024. He also serves as the Associate Vice Director of the Shenzhen National Applied Mathematics Center since February 2023. Education: Ph.D. in Applied Mathematics (2014, University of Victoria); M.Sc. in Operational Research (2010, Dalian University of Technology); B.Art in Journalism (2007, Dalian University of Technology) Research Interests span optimization theory , variational analysis , bilevel programming , and their applications in machine learning , economics , and data science . His work includes convergence analysis of first-order methods , stochastic/robust optimization , and error bound conditions . Recent Publications focus on nonconvex bilevel optimization , gradient-based algorithms , and stochastic programming , with papers in IEEE TPAMI , SIAM Journal on Optimization , and conferences like ICML , NeurIPS , and ICLR . Scientific Awards include the Youth Science and Technology Innovation Award from Guangdong Province (2022) , Youth Science and Technology Award from the Operations Research Society of China (2020) , and Junior Research Award from SUSTech's Faculty of Science (2020) . Students: Supervises Ph.D. candidates like Yixia Song , Peixuan Yang , and Qichao Cao , along with Master's students Yixuan Zhang , Kaiqi Sun , and Feifan Wang . Grants: Leads projects such as the National Key R&D Program (3.2M RMB, 2024-2028) and National Science Fund for Distinguished Young Scholars (2M RMB, 2023-2025) .

• Mathematical Optimization
• Game Theory
• Mechanism Design
• +۷ مورد دیگر

Max Klimm is an Assistant Professor for Discrete Optimization at Technische Universität Berlin, affiliated with Faculty II – Mathematics and Natural Sciences and the Department of Mathematics. He leads the research group in Discrete Optimization and holds editorial roles at journals like the International Journal of Game Theory and Operations Research Forum . His academic journey includes a PhD in Mathematics from TU Berlin (2012), followed by roles as an Assistant Professor at Humboldt-Universität zu Berlin and Head of the Junior Research Group at the Einstein-Center for Mathematics. His research focuses on mathematical optimization, game theory, and mechanism design applied to multi-agent systems in traffic, telecommunications, and economics. Recent work addresses equilibrium computation in congestion games, stochastic optimization, and algorithmic challenges in network design. Key projects include Combinatorial Network Flow Methods for Gas Markets and the Math+ projects on mechanism design and evolutionary models for networks. Teaching responsibilities include courses on Discrete Optimization, Algorithmic Game Theory, and introductory mathematical courses. His research has been funded by DFG, Einstein Center, and Math+ initiatives. Notable contributions include advancements in parametric flow algorithms, impartial selection mechanisms, and reconstructing historical road networks using cost-benefit models.

Nathanaël Fijalkowمشاهده پروفایل

پژوهشگر

• Games
• Machine Learning
• Automata Theory
• +۹ مورد دیگر

Nathanaël Fijalkow is a Researcher at CNRS in LaBRI (Bordeaux) and a Research Fellow at The Alan Turing Institute in London. His primary research fields include games , machine learning , automata theory , and dynamical systems , with a focus on synthesizing programs from logical specifications and probabilistic models. Research Interests span program synthesis (programming by example), controller synthesis (temporal logic specifications), games on graphs (parity/mean payoff games), probabilistic automata (bounded ambiguity), and invariants for linear dynamical systems. He bridges formal methods with machine learning through projects like DeepSynth . Scientific Contributions include: Undecidability results for probabilistic automata Advances in parity game algorithms (quasi-polynomial lower bounds) Foundations of probabilistic modal logics Efficient synthesis techniques using SMT solvers and distributional learning Supervision involves guiding postdocs and PhD students such as Guillaume Lagarde, Antonio Casares, and Pierre Ohlmann. He has secured grants like the Momentum DeepSynth project (2019-2021) , aiming to merge formal methods with ML for program synthesis.

• Optimization
• Machine Learning
• Statistics
• +۵ مورد دیگر

Siqi Zhang is a Tenure-Track Assistant Professor in the Department of Industrial Engineering and Operations Management (IEOM) at the School of Management and Engineering (SME) of Nanjing University (NJU). Holding a Ph.D. in Operations Research from the University of Illinois at Urbana-Champaign (UIUC) and postdoctoral experience at Johns Hopkins University (JHU), their research bridges optimization theory with machine learning applications. Ph.D. from UIUC's Industrial and Enterprise Systems Engineering (ISE) Department (2017-2022) Postdoctoral Fellow at JHU's Applied Mathematics and Statistics Department (2022-2024) Visiting Ph.D. at ETH Zurich's Optimization & Decision Intelligence Group Research focuses on stochastic optimization , nonconvex optimization , and minimax optimization with applications to federated learning and the intersection of machine learning and operations research . Their recent work establishes theoretical bounds for optimization algorithms in minimax settings. Publication trends reveal expertise in distributed optimization , communication efficiency , and algorithm stability . Key venues include AISTATS, ICLR, NeurIPS, and UAI conferences, with technical reports on arXiv and PMLR proceedings. 2025 ICLR Blogpost on optimization bounds 2024 ICLR/ICML algorithm stability analysis 2022 UAI complexity bounds 2020 NeurIPS series on optimization frameworks Awarded the Acheson J. Duncan Fund (2024) and "Yu Qian" Scholarship (2016), Siqi also serves as reviewer for top venues like NeurIPS, AAAI, and SIOPT journal. Teaching portfolio includes optimization theory, probability, and linear algebra applications at both JHU and ETH Zurich.

Robert Dalangمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Stochastic Partial Differential Equations
• +۳ مورد دیگر

Robert Dalang is a Full Professor and Chair of Probabilities at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. He is affiliated with the School of Basic Sciences, Department of Mathematics, specifically the Probability Section. His office is located in building MA, room B2 493 at EPFL's Lausanne campus. He also serves as a Full Professor in the Section of Mathematics (SMA) and for the Doctoral Program in Mathematics (EDMA). Professor Dalang's research focuses on probability theory and stochastic analysis. His work primarily centers on: Stochastic partial differential equations (SPDEs), particularly stochastic heat and wave equations Brownian motion and Brownian sheet Lévy processes and Lévy white noise Hitting probabilities and polarity Fractal properties of random fields Stochastic optimization problems His recent publications demonstrate a continued focus on the theoretical properties of solutions to stochastic partial differential equations, including their regularity, hitting probabilities, and asymptotic behavior. He has made significant contributions to understanding the fine properties of solutions to stochastic heat and wave equations, particularly in critical dimensions. Professor Dalang has served on the elected committee for the Pension fund PUBLICA since Fall 2007, being reelected for 2009-2012. His work on this committee has focused on preserving employee interests during the transition from a defined benefits system to a defined contributions system. He has supervised numerous PhD students, including: Candil David Jean-Michel Chen Le Ciccarella Carlo Conus Daniel Dumas Frédéric Humeau Thomas Marie Jean-Baptiste Pu Fei Rossel Jean-Benoît Vinckenbosch Laura Professor Dalang teaches courses including Analysis III, Analysis IV, and Theory of Stochastic Calculus at EPFL.

Malte Helmertمشاهده پروفایل

استاد

• Automated Planning
• Combinatorial Search
• Artificial Intelligence
• +۷ مورد دیگر

Malte Helmert is a Professor at the University of Basel in the Department of Mathematics and Computer Science. He previously worked at the University of Freiburg's Research Group on the Foundations of Artificial Intelligence from 2001 to 2011. His research focuses on intelligent problem-solving , particularly in automated planning , combinatorial search , constraint satisfaction , and NP-hard graph problems . Helmert has made significant contributions to classical planning, including the development of the Fast Downward planning system and its derivatives. Education : Diploma in Computer Science (M.Sc.) from the University of Freiburg (2001) Ph.D. in Computer Science from the University of Freiburg (2006) Research interests encompass the theoretical and practical aspects of automated planning, including heuristic search , optimal planning , abstraction techniques , and domain-independent planning . His work explores merge-and-shrink abstractions , landmark progression , and cost partitioning algorithms for classical planning systems. Recent publications analyze advancements in pseudo-Boolean proof logging , higher-dimensional potential heuristics , and correlation complexity in planning domains. These works often integrate mathematical modeling, algorithm design, and empirical benchmarking. Scientific awards include the AAAI Fellow (2021), EurAI Fellow (2020), multiple Best Paper Awards at ICAPS and SoCS conferences, and the Computers and Thought Award (2011). He also received the VDI-Förderpreis for his Master’s thesis. Software contributions include the Fast Downward planning system, MIPS (now maintained by Stefan Edelkamp), and COVER (a vertex cover solver). Helmert has organized tutorials at ICAPS and AAAI conferences on topics like landmark progression , abstraction heuristics , and LP-based heuristics .

• Calculus of Variations
• Geometric Measure Theory
• Non-Linear PDEs
• +۲ مورد دیگر

Prof. Dr. Thomas Schmidt is a full-time Professor for Geometric PDEs at the University of Hamburg , affiliated with the Department of Mathematics under the Faculty of Mathematics, Informatics and Natural Sciences . He leads the research group on Geometric Partial Differential Equations , focusing on calculus of variations, nonlinear PDEs, geometric measure theory, and regularity theory. Education: Diplom in Mathematics (2004, HHU Düsseldorf), Doctor in Mathematics (2006, HHU Düsseldorf), Habilitation in Mathematics (2015, FAU Erlangen-Nürnberg). Career: Appointed as W2 Professor at University of Hamburg since 2016; postdoctoral positions at SNS Pisa, University of Zurich (2011–2013), and FAU Erlangen-Nürnberg (2008–2016). His research investigates boundary/obstacle problems for BV functions, currents near the Plateau problem, least gradient problems, Mumford-Shah functionals, quasiconvex integrals, and PDEs with degenerate ellipticity. Recent work includes existence theory for linear-growth functionals with signed measures, optimal Hölder exponents in Massari-type theorems, and duality frameworks for BV minimizers. Publications span journals like Advances in Calculus of Variations , Mathematische Annalen , and J. Lond. Math. Soc. . Key trends in his publications involve geometric measure theory, regularity analysis, and convex duality. His group addresses existence/uniqueness of generalized solutions, L p estimates, and partial regularity. He has collaborated with researchers such as Eleonora Ficola, Jule Helena Schütt, and Christoph Scheven. For administrative support, contact his team assistant Katrin Kopp at the department office.