جست‌وجوی استاد و پژوهشگر

Sagun Chanilloمشاهده پروفایل

استاد

• Nonlinear Analysis
• Partial Differential Equations
• Geometric Analysis
• +۲ مورد دیگر

Sagun Chanillo is a Professor in the Department of Mathematics at Rutgers, The State University of New Jersey . His research focuses on Nonlinear Analysis , Partial Differential Equations , and related areas in Geometric Analysis and Harmonic Analysis . Research Monographs : "Geometric Analysis of PDE and Several Complex Variables" (AMS), "Harmonic Analysis, Partial Differential Equations and Applications" (Springer), and "Optimal Weak type Inequalities for the Partial Cesaro Sum operator" Research Themes : Dr. Chanillo investigates problems in CR Geometry (e.g., embeddability of CR manifolds, Paneitz operator properties), Fluid Mechanics (e.g., Navier-Stokes with divergence-free data), and Geometric PDE (e.g., Yamabe-type problems, symmetry breaking in eigenvalue optimization). He also explores connections to Number Theory (e.g., Riemann Zeta function in scattering theory) and Mathematical Physics (e.g., Ginzburg-Landau vortices, rotating stars). Recent Publications highlight collaborations with researchers like Paul C. Yang , Jean Van Schaftingen , and Po-lam Yung . Key contributions include sharp bounds for geometric PDEs , nonlinear eigenvalue studies , and probabilistic methods in wave equations .

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +۵ مورد دیگر

Daniele Pretolani is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. He specializes in Operations Research (MATH-06/A) with a focus on decision support systems, multi-objective optimization, and directed hypergraph algorithms. Teaches Methods and Algorithms for Optimization in Digital and Creative Industry (Management Engineering) Teaches Models and Methods for Decision Support (Management Engineering) His research explores: Stochastic time-dependent network routing Multi-criteria decision analysis for supplier selection Hypergraph reductions for satisfiability problems Visual decision support tools for composite indexes Recent work includes developing a decision support system for global service providers (2024) that improved supplier selection by 25% over company practices, and foundational contributions to the SDEWES sustainability index (2018-2020). No specific awards or student advising details were mentioned in the provided texts.

Christopher Herzogمشاهده پروفایل

استاد

• Theoretical Physics
• Quantum Field Theory
• String Theory
• +۴ مورد دیگر

Christopher Herzog is a Professor of Theoretical Physics at King's College London, Department of Mathematics, within the Faculty of Natural, Mathematical & Engineering Sciences. He previously held positions as Associate Professor at the Yang Institute for Theoretical Physics (Stony Brook University) and Assistant Professor at Princeton University. His research focuses on AdS/CFT correspondence, gauge/gravity dualities, and strongly interacting field theories, particularly QCD and string theory applications. He received his PhD from Princeton University in 2002 under Igor Klebanov. Research Interests: Herzog explores quantum field theories using holography and conformal field theory techniques. His work includes boundary CFTs, entanglement entropy, and applications of gauge/gravity duality to condensed matter systems. He is part of a group advancing research in supersymmetry, string theory, and M-theory. Scientific Awards: In 2019, he was awarded the Royal Society Wolfson Fellowship, recognizing his contributions to theoretical physics. Advising & Grants: While specific student names are not listed, his extensive research output indicates active mentorship in theoretical physics. His work is supported by grants related to his cutting-edge research areas. Labs & Teams: Leads the theoretical physics research group at King's College, collaborating internationally on projects in holography and conformal field theory.

Markus Riedleمشاهده پروفایل

استاد

• Stochastic Processes
• Stochastic Analysis
• Stochastic Differential Equations
• +۳ مورد دیگر

Professor Markus Riedle holds the position of Professor of Probability Theory at King's College London's Department of Mathematics, within the Faculty of Natural, Mathematical & Engineering Sciences. He obtained his Ph.D. from Humboldt University Berlin in 2003 and held a postdoctoral position there. Before joining King's as a Reader in 2011 (promoted to Professor in 2017), he served as a lecturer at the University of Manchester and substituted a professorial role in applied mathematics at the University of Mannheim. His research focuses on stochastic processes, stochastic analysis, and stochastic differential equations, with applications in financial mathematics and infinite-dimensional spaces. Key areas include Lévy processes, stochastic integration in Banach spaces, and stochastic evolution equations. Recent publications highlight advancements in cylindrical Lévy processes, stochastic partial differential equations, and large deviations principles. His work has been recognized through notable collaborations, including supervision of Dr. Tomasz Kosmala (2020 King's Outstanding PhD Thesis Prize recipient) and Dr. Gergely Bodo. Riedle leads research projects funded by EPSRC and the London Mathematical Society, exploring cylindrical Lévy processes, stochastic analysis in infinite-dimensional spaces, and their applications. He is an active member of King's Probability group and contributes to the Financial Mathematics research cluster.

• Representation Theory
• Algebraic Geometry
• Lie Algebras
• +۳ مورد دیگر

Arzu Boysal is a Full Professor in the Department of Mathematics at Boğaziçi University's Faculty of Engineering. Her research centers on representation theory and algebraic geometry, with particular focus on Lie algebras, affine Lie algebras, and their geometric representations. Boysal's mathematical investigations explore connections between Lie group representations and complex geometry, examining structures like moduli spaces through combinatorial and topological frameworks. Her recent work addresses problems in mathematical physics including lattice sums and quantum algebra. She teaches advanced courses in Genetic Algorithms and Mathematical Optimization, serving on editorial boards for computational mathematics journals. Her research contributes to understanding geometric structures in representation theory.

Jeffrey Hudson Schenkerمشاهده پروفایل

استاد

• Mathematical Physics
• Quantum Mechanics
• Statistical Physics
• +۳ مورد دیگر

Jeffrey Hudson Schenker is a Professor and Chairperson of the Department of Mathematics at Michigan State University (MSU). His academic journey includes a Ph.D. in Mathematics from Princeton University (2002) under Michael Aizenman, and earlier degrees from the University of Wyoming. He holds administrative roles, including Chair of Mathematics since 2022 and Director of Graduate Studies (2017–2020). His research focuses on mathematical physics, quantum mechanics, statistical physics, and applications of probabilistic models to biology. Key research interests include the effects of disorder in quantum systems, ergodic quantum processes, and interdisciplinary studies combining mathematical models with biological systems. He has been funded by multiple NSF grants, including recent projects on quantum processes and disordered systems. Notable awards include the American Mathematical Society Fellowship (2019) and the J. Sutherland Frame Teaching Award (2009). Dr. Schenker’s work spans theoretical and applied domains, with contributions to operator theory, spectral analysis, and quantum dynamics. His research group includes current Ph.D. students and former members who have pursued academic and industry roles globally. His publications address topics like Anderson localization, quantum diffusion, and ergodic theorems, often leveraging advanced mathematical techniques in physics and probability.

• Optimization
• Signal Processing
• Machine Learning
• +۳ مورد دیگر

Dr. Minh Dao is a Senior Lecturer in the Department of Mathematics at RMIT University's School of Science. His research focuses on optimization theory, algorithm design, and their applications in signal processing, machine learning, and wireless communications. He has contributed to advancements in distributed optimization, nonconvex programming, and federated learning frameworks. Key research interests include operator splitting methods, DC programming, and mathematical modeling for energy-efficient systems. He has published extensively in top-tier journals and conferences such as the European Journal of Operational Research and IEEE Transactions on Intelligent Transportation Systems. Dr. Dao supervises research projects on distributed optimization for federated learning, reboot sensing MIMO systems, and DC programming approaches for clustering problems. His work integrates theoretical analysis with practical applications in telecommunications and energy networks.

Nathan Steeleمشاهده پروفایل

دانشیار

• Group Dynamics
• Negotiation
• Organizational Behavior
• +۵ مورد دیگر

Nathan Steele is an Associate Professor and MBA Program Director at the College of Business and Management, University of Illinois Springfield. He specializes in Organizational Behavior, teaching courses such as Negotiation, Managing Organizational Behavior, and Leadership and Motivation. He has been recognized with multiple teaching awards for his instructional excellence. Dr. Steele earned his Ph.D. in Social Psychology from Indiana University in 2004, focusing on negotiation and bargaining under Dr. Jerome M. Chertkoff. His postdoctoral research at the University of Utah’s Eccles School of Business explored perceptions of equity in negotiation scenarios. His research interests encompass group dynamics, decision making, equity, moral reasoning, and negotiation strategies. His work integrates theoretical and practical insights, addressing issues like stereotype reduction in performance evaluations, the role of balanced scorecards in team decision-making, and moral development in business education. He has consulted with organizations such as the Southwestern Poverty Law Center and Bank of Springfield, offering executive education on leadership and negotiation. His research outputs highlight trends in ethical judgment assessment, bias mitigation in evaluations, and cross-team dynamics. Though awards are mentioned, specific names are not provided. He actively engages in academic discourse through refereed journals and conferences, emphasizing applications of his findings to real-world organizational challenges.

Anthony Kimمشاهده پروفایل

استادیار

• Revenue Management
• Online Decision Making
• Algorithmic Game Theory
• +۵ مورد دیگر

Anthony Kim is an Assistant Professor of Decision Sciences at the SKK Graduate School of Business, Sungkyunkwan University. His research focuses on revenue management, advertising, and online decision-making. Previously, he worked as an applied scientist at Amazon’s APMC team and held a postdoctoral position at Columbia Business School’s Decision, Risk, and Operations Division. He earned his Ph.D. in Computer Science from Stanford University (2018) and multiple degrees from MIT, including dual B.S. in Electrical Engineering/Computer Science and Mathematics (2009), and an M.Eng. (2010). Education: Ph.D., Computer Science, Stanford University, 2018 M.Eng., MIT, 2010 B.S. (Dual), MIT, 2009 Research Interests: Dr. Kim explores algorithmic solutions for dynamic pricing, auction mechanisms, and optimization under uncertainty. His work bridges theoretical computer science with practical applications in e-commerce, energy systems, and network resource allocation. Key areas include robust mechanism design, online budget management, and latency minimization in ride-sharing platforms. Professional Contributions: Program committee member for ACM Web Conference (2020–2025) Reviewer for Operations Research , Management Science , and other top journals Recipient of Research Paper Honorable Mention (2018 Web Conference) Grants & Labs: Active in industry collaborations through Amazon’s APMC team and academic research at Columbia’s DRO Division. His work integrates theoretical rigor with real-world marketplace challenges.

Wilhelm Schlagمشاهده پروفایل

استاد

• Partial Differential Equations
• Mathematical Physics
• Harmonic Analysis
• +۶ مورد دیگر

Wilhelm Schlag is a Professor in the Department of Mathematics at Yale University, specializing in partial differential equations, mathematical physics, and harmonic analysis. His research focuses on nonlinear wave equations, spectral theory, and Anderson localization, with significant contributions to the understanding of wave maps, Klein-Gordon equations, and Schrödinger operators. Dr. Schlag's research interests span multiple areas of mathematical analysis with emphasis on energy critical wave equations , spectral theory of Schrödinger operators , and Anderson localization . His work combines techniques from harmonic analysis, dynamical systems, and geometric analysis to study nonlinear phenomena in mathematical physics. He has developed innovative approaches to understanding the stability of solitons, the behavior of waves on curved backgrounds, and the spectral properties of quasi-periodic operators. Analysis of his recent publications reveals a strong focus on non-perturbative methods in spectral theory, particularly for quasi-periodic operators and Schrödinger cocycles. His work often bridges the gap between mathematical physics and pure analysis, with applications to quantum mechanics and field theory. Schlag has developed multiscale techniques for Anderson localization and made significant contributions to the understanding of wave map dynamics beyond symmetric settings. Dr. Schlag serves on the editorial boards of prestigious journals including Communications in Partial Differential Equations , Inventiones Mathematicae , and Calculus of Variations and PDE . He is the co-author of influential books such as Concentration compactness for critical wave maps and Invariant Manifolds and dispersive Hamiltonian Evolution Equations . His collaborative research program involves extensive numerical computations, as evidenced by the NLKG3_WEB repository containing Bash scripts and data for nonlinear Klein-Gordon equation simulations. Schlag has mentored numerous researchers through his collaborative projects and has presented his work at major international conferences including the International Congress of Mathematicians.

Giuseppe Lopomoمشاهده پروفایل

استاد

• Game Theory
• Auction Theory
• Mechanism Design
• +۳ مورد دیگر

Giuseppe Lopomo is the Alan D. Schwartz Distinguished Professor of Business Administration at Duke University's Fuqua School of Business, with a courtesy appointment in the Economics Department. He holds a Laurea Magna cum laude from Bocconi University and a Ph.D. in Business Administration from Stanford. Prior to Duke, he was an Assistant Professor at NYU Stern and visited the University of Michigan. He teaches Managerial Economics and Competitive Analysis to MBA students and has instructed undergraduate and Ph.D. courses. His research focuses on applied game theory, auction theory, and mechanism design, addressing topics like procurement, surplus extraction, and optimal contracting. His work appears in top journals such as The American Economic Review and The Review of Economic Studies. Education: Laurea Magna cum laude, Bocconi University (Italy) Ph.D. in Business Administration, Stanford Graduate School of Business Research Interests: Professor Lopomo's work explores strategic interactions in economic systems, particularly through applied game theory and mechanism design. His studies often address practical challenges in procurement processes, auction design, and the robustness of economic mechanisms under uncertainty. Key themes include optimizing market structures, managing private information, and ensuring efficiency in resource allocation. Recent Trends in Publications: Recent work emphasizes mechanisms under uncertainty, surplus extraction, and the interplay between budget constraints and economic outcomes. His 2023 paper on procurement quality concerns and 2022 studies on detectability and duality highlight his focus on real-world applications of theoretical models. Awards & Recognition: While no specific awards are listed, his endowed chair position reflects his academic distinction. His extensive publication record in top-tier journals underscores his scholarly impact. Advising & Grants: No specific advising records or grant details are provided in the texts. His teaching and research activities are central to his current professional profile. Labs/Teams: No formal lab or team affiliations are mentioned, though his collaborations are implied through co-authored publications.

• Mathematical Physics
• Harmonic Analysis
• Dynamical Systems
• +۳ مورد دیگر

Dr. Rui Han is an Assistant Professor at Louisiana State University, Department of Mathematics. He previously served as a Visiting Assistant Professor at Georgia Institute of Technology (2018–2020) and was a Member at the Institute for Advanced Study (2017–2018). His academic journey includes a B.S. in Mathematics from the University of Science and Technology of China (2008–2012) and a Ph.D. in Mathematics from the University of California, Irvine (2012–2017). Rui Han's research focuses on Mathematical Physics, Harmonic Analysis, and Dynamical Systems and Ergodic Theory. His work explores topics such as spectral theory, quasi-periodic operators, localization phenomena, and applications to quantum dynamics. He employs advanced analytical techniques to study problems in mathematical physics, including the analysis of Schrödinger cocycles, Lyapunov exponents, and the interplay between dynamical systems and spectral properties. His accolades include the Kovalevsky Outstanding Ph.D. Thesis Award (2017), the Von Neumann Award for outstanding performance (2016), and the Connelly Award for excellence in teaching and research (2014). He has secured significant grants, including the NSF CAREER Award (2022–2027) as Principal Investigator and the RTG grant in Topology, Representation Theory, and Mathematical Physics (2023–2028) as senior personnel. No specific laboratory or team affiliations are mentioned in the provided information.

Laurent El Ghaouiمشاهده پروفایل

استاد

• Robust Optimization
• Decision-making under Uncertainty
• Statistical Estimation
• +۵ مورد دیگر

Laurent El Ghaoui is a Professor in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. He joined the faculty in 1999 after serving as Acting Associate Professor. Prior to Berkeley, he held academic positions at the École Nationale Supérieure de Techniques Avancées (Paris) and part-time roles at École Polytechnique and Université de Paris-I. His research focuses on robust optimization, decision-making under uncertainty, statistical estimation, and applications in air traffic management, bioinformatics, and finance. He is affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Center for New Media (BCNM), and CLIMB. El Ghaoui holds a Ph.D. in Aeronautics and Astronautics from Stanford University (1990) and a B.S. in Mathematics from École Polytechnique (1985). He has been recognized with prestigious awards, including the SIAM Optimization Prize (2008) and the CNRS Bronze Medal (1998). His work integrates optimization theory with real-world challenges, such as robust filtering, dynamic routing, and financial risk modeling. His research spans machine learning, control systems, and stochastic processes. Notable contributions include algorithms for sparse graphical models, distributionally robust optimization, and air traffic flow scheduling. He has collaborated on projects involving microarray data analysis and MEMS design. His academic career combines teaching and industry experience, including a leave at SAC Capital Management (2003–2006).

Thomas Taimreمشاهده پروفایل

مدرس ارشد

• Applied Mathematics
• Operations Research
• Scientific Computing
• +۵ مورد دیگر

Thomas Taimre is a Senior Lecturer in Statistics at the School of Mathematics and Physics, University of Queensland. He teaches undergraduate courses in statistics and financial mathematics and leads research in applied mathematics, stochastic modeling, and optical engineering. His work bridges theoretical frameworks with practical applications in terahertz laser technology and optimization algorithms. Research Focus: Dr. Taimre's interdisciplinary research spans: Mathematical Statistics: Rare-event simulation, stochastic processes, and Monte Carlo methods. Optical Engineering: Terahertz quantum cascade lasers, laser feedback interferometry, and biomedical imaging. Operations Research: Resource optimization, queueing theory, and decision support systems for environmental and industrial challenges. Publication Trends: His recent articles (2022-2025) emphasize terahertz imaging advancements, laser dynamics, and optimization techniques. Dominant themes include quantum cascade laser applications, laser feedback interferometry for medical diagnostics, and stochastic methods for complex system modeling. Funding & Supervision: He contributes to major grants like the ARC Training Centre for Information Resilience (2021-2026) and supervises graduate research. No awards are listed.

Liyuan Linمشاهده پروفایل

مدرس ارشد

• Actuarial Science
• Quantitative Risk Management
• Dependence and Risk Aggregation
• +۴ مورد دیگر

Liyuan Lin is a Senior Lecturer in the Department of Econometrics & Business Statistics at Monash University's Faculty of Business and Economics. He holds a PhD in Actuarial Science from the University of Waterloo, awarded in 2024. His academic work centers on advanced risk modeling and actuarial theory. Research Interests: Actuarial Science Quantitative Risk Management Dependence and Risk Aggregation Stochastic Control Risk Measures and Diversification Reinsurance Strategy and Market Competition His recent publications, appearing in top journals such as Management Science , Mathematics of Operations Research , and Scandinavian Actuarial Journal , reflect a strong focus on theoretical and applied aspects of risk modeling. Key themes include diversification measurement, optimal reinsurance under competition, calibration of risk models, and structural dependence in multivariate settings. His work often involves deep mathematical analysis and collaboration with leading scholars in actuarial mathematics. Scientific Awards: No awards listed in the provided text. Advising and Grants: There is no explicit information available regarding student supervision, grant funding, or advisory roles. However, given his active publication record and position as a Senior Lecturer, it is likely that he mentors students and participates in research projects, though specifics are not disclosed in the source material. Labs and Research Teams: No specific lab or research group is mentioned. However, his collaborations suggest active participation in the broader actuarial and quantitative risk research network, particularly with researchers at institutions connected to the University of Waterloo and international actuarial research centers.