جست‌وجوی استاد و پژوهشگر

• Stochastic Control
• Backward Stochastic Differential Equations (BSDEs)
• Actuarial Science
• +۶ مورد دیگر

Anis Matoussi is a Professor of Applied Mathematics at Le Mans University and serves as the Director of the Institut du Risque et de l'Assurance du Mans. He coordinates the master's program in Actuarial Science and leads multiple research initiatives, including ANR DREAMeS (2021-2025) and ITCA (Groupama, Fondation du Risque). Role: Professor, Applied Mathematics Institution: Le Mans University Research Leadership: Director of Institut du Risque et de l'Assurance, Head of Master Actuarial Science His research focuses on stochastic control, backward stochastic differential equations (BSDEs), and their applications in finance, insurance, and energy systems. He has developed numerical methods for second-order BSDEs and studied stochastic nonlinear PDEs, maximum principles for SPDEs, and extended mean field control models. Recent projects include the application of deep learning to forward utilities via ergodic BSDEs and multivariate risk measures. Matoussi has supervised numerous PhD students, including current advisees Zakaria Bensa (industrial thesis with Natixis) and Lucas Da Silva (co-supervised with Caroline Hillairet). Former students like Achraf Tamtalini (Bank of America) and Jing Zhang (Fudan University) hold prominent positions globally. His work includes collaborations on smart grids, control of electrical systems, and robust utility maximization under uncertainty. Publications span journals in applied mathematics, optimization, probability, and financial mathematics, with recent emphasis on numerical schemes and probabilistic representations.

Fabio Angelo Maccheroniمشاهده پروفایل

استاد

• Decision Theory
• Game Theory
• Mathematical Economics
• +۵ مورد دیگر

Summary Fabio Angelo Maccheroni is a Full Professor at Bocconi University's Department of Decision Sciences, affiliated with the IGIER research center. He holds a Laurea in Mathematics from the University of Milan (1995) and a PhD in Applied Mathematics from a joint program of several Italian universities (1999). His research focuses on decision theory, game theory, mathematical economics, and ambiguity aversion, with contributions to risk analysis and behavioral economics. He has been recognized with awards including the Economic Theory Fellow (2019) and the Carlo Alberto Medal (2010). Education: University of Milan (Laurea), Joint PhD Program (1999) Professional Roles: Full Professor since 2005, IGIER Fellow since 2008 Research interests include axiomatic foundations of decision making, ambiguity preferences, and applications to finance and insurance. His work bridges economics, mathematics, and neuroscience, particularly through diffusion models of decision processes. Over 50 journal articles span top venues like Econometrica , Journal of Economic Theory , and Management Science . Awards Economic Theory Fellow (2019) Cours Bachelier (2012) Carlo Alberto Medal (2010)

Samuel Thibaultمشاهده پروفایل

استاد

• Parallel Computing
• High Performance Computing
• Task-Based Runtime Systems
• +۳ مورد دیگر

Samuel Thibault is a Professor at University of Bordeaux, affiliated with Laboratoire Bordelais de Recherche en Informatique (LaBRI) and Inria Bordeaux -- Sud-Ouest. He is a member of the SATANAS team at LaBRI (theme: High Performance Runtime Systems for Parallel Architectures) and the STORM research team at Inria Bordeaux (previously RunTime). His work bridges academic research and practical implementation of high-performance computing systems. Thibault's research focuses on task-based runtime systems, particularly StarPU, for heterogeneous and parallel computing architectures. His work addresses critical challenges in scheduling algorithms, memory management under constraints, data locality optimization, and performance modeling for complex NUMA architectures. He has made significant contributions to the field of parallel computing through the development and analysis of runtime systems that efficiently manage tasks across diverse hardware resources including CPUs, GPUs, and other accelerators. His research has practical applications in scientific computing, deep learning inference, and large-scale simulations requiring extreme computing power. His recent publication trends show a strong emphasis on optimizing task-based runtime systems for heterogeneous architectures with particular attention to memory constraints and data locality. There's a clear progression toward applying these techniques to deep learning inference workloads, as evidenced by his StarONNX project. His work consistently addresses the challenge of balancing throughput and latency in complex computing environments, with increasing focus on recursive task graphs and dynamic adaptation strategies. Thibault is actively involved in European research initiatives including TEXTAROSSA (focusing on exascale technologies) and EXA2PRO (high development productivity on heterogeneous systems). His work has been published consistently in top-tier conferences and journals in parallel and distributed computing. As part of the STORM team at Inria Bordeaux, Thibault contributes to advancing the state of the art in runtime systems for high-performance computing. His team's work on StarPU has become a reference implementation in the field, enabling researchers and practitioners to develop applications that can efficiently utilize heterogeneous computing resources without needing to manage the complexity of different hardware architectures directly.

Ian Dew-Beckerمشاهده پروفایل

دانشیار مدعو

• Asset Pricing
• Macroeconomics
• Uncertainty
• +۴ مورد دیگر

Ian Dew-Becker serves as an Adjunct Associate Professor of Finance at the University of Chicago Booth School of Business and as a Senior Economist at the Federal Reserve Bank of Chicago. His academic work centers on theoretical and empirical asset pricing and macroeconomics, with particular emphasis on uncertainty, skewness, and tail risk in economic systems. He received his PhD in economics from Harvard University and has held prior positions at Northwestern University, Duke University, and the Federal Reserve Bank of San Francisco. His educational background includes: PhD in Economics, Harvard University Dew-Becker's research explores how agents form beliefs about economic fundamentals and how these beliefs translate into asset prices and macroeconomic outcomes. He investigates the dynamics of uncertainty and skewness across business cycles, develops novel measures using options data, and examines how production networks propagate economic shocks. His work demonstrates that firm-level uncertainty does not significantly forecast aggregate output, challenging existing models, while revealing how interconnectedness can reduce sensitivity to small shocks while amplifying vulnerability to large ones. Recent studies focus on real-time skewness measurement and tail risk transmission through input-output structures. Analysis of his publication record shows a consistent focus on risk measurement and pricing across financial and macroeconomic domains. Collaborating frequently with Stefano Giglio, he has pioneered methodologies using options data to construct cross-sectional uncertainty indices and measure conditional skewness. His research demonstrates that while exchange-traded options earn negative alphas implying rising risk aversion during downturns, synthetic options show constant risk aversion, suggesting intermediary frictions drive pricing anomalies. Key contributions include establishing empirical regularities about macro skewness and demonstrating how production networks generate left-skewed economic activity. No scientific awards were mentioned in the available information. Information regarding graduate student advising, research grants, or specific funding sources was not provided in the source materials. Dew-Becker teaches the Investments course at Chicago Booth during Autumn quarters but no details about mentored students or grant-supported projects are available. Dr. Dew-Becker actively collaborates with researchers across institutions including Stefano Giglio (Yale University), Andrea Vedolin (London School of Economics), and Bryan Kelly (Yale University), forming a network focused on financial economics and macro-finance linkages. His work bridges theoretical modeling with empirical analysis of market data, particularly options markets, to address fundamental questions about risk and uncertainty in economic systems.

Piotr Gmytrasiewiczمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Multiagent Systems
• Decision Theory
• +۷ مورد دیگر

Piotr Gmytrasiewicz is an Associate Professor at the Department of Computer Science, University of Illinois at Chicago (UIC). He leads the Multiagent Systems Group within the Artificial Intelligence Laboratory at UIC. His research focuses on rationality in artificial agents , particularly in environments with multiple interacting agents. Key areas include Interactive Decision-Making Bayesian Modeling for Agent Communication Recursive Belief Frameworks Time Pressure and Computational Trade-offs Evolution of Agent Communication Languages Dynamic Resource Allocation His recent work examines the rationality of insincere communication and methods to discount potentially insincere information. Past projects include modeling emotions in agent design and developing decision-theoretic approaches to game theory. He has secured funding from prestigious institutions such as the National Science Foundation (NSF) , Office of Naval Research (ONR) , and DARPA . Current and past projects emphasize Automated Linguistic Competence Evolution Emergent Communication Protocols Scalable Multiagent Learning Strategic Coordination under Uncertainty He earned his Ph.D. from the University of Michigan, Ann Arbor (1992) and has previously collaborated with the Department of Computer Science and Engineering (CSE) at the University of Texas at Arlington on DARPA-funded research.

Martin Herdegenمشاهده پروفایل

دانشیار

• Mathematical Finance
• Probability Theory
• Stochastic Processes
• +۵ مورد دیگر

Martin Herdegen is a Reader in Financial Mathematics at the Department of Statistics, University of Warwick. He previously served as a postdoc at ETH Zürich under Johannes Muhle-Karbe and holds a PhD in Mathematics from ETH Zürich (2014) under Martin Schweizer. His research focuses on equilibrium theory, utility maximization, stochastic processes, and risk measures, with applications to financial bubbles and market microstructure. Herdegen’s academic career includes supervising multiple PhD students (e.g., Florian Gutekunst, Andreea Popescu) and postdocs (e.g., Nazem Khan). His research group explores topics like ρ-arbitrage, recursive utility, and liquidity provision under adverse conditions. He has contributed to foundational work on strict local martingales and their implications for financial markets. Publications span leading journals such as Finance and Stochastics , Mathematical Finance , and Annals of Applied Probability , addressing equilibrium models with transaction costs, optimal investment strategies, and risk measurement techniques. His work frequently integrates stochastic analysis and control theory to solve practical finance problems. Herdegen’s research also intersects with reinforcement learning applications in trading, as seen in the Mbt-gym framework for limit order book simulations. His contributions emphasize rigorous mathematical foundations while addressing real-world market frictions and liquidity dynamics.

• Decision Theory
• Game Theory
• Economic Learning Models
• +۴ مورد دیگر

Nabil Al-Najjar is the John L. and Helen Kellogg Professor of Managerial Economics & Decision Sciences at Northwestern University's Kellogg School of Management. He holds a PhD in Economics from the University of Minnesota (1989), preceded by an MA from the University of Ottawa (1982) and a BA from Al-Mustansiriah University (1979). Prior to joining Kellogg in 1995, he taught at the University of Quebec in Montreal. His research focuses on decision theory, game theory, and learning-based models in markets and contracts. Notable contributions include frameworks for uncertainty modeling, aggregate risk analysis, and recursive utility theory. He has published in top journals such as the Journal of Economic Theory, Econometrica, and the American Economic Review. Award-winning educator, Al-Najjar twice received the Sidney J. Levy Teaching Award (1996-97, 2006-07) for excellence in microeconomics and competitive strategy instruction. He also holds editorial roles at the International Journal of Game Theory and Journal of Mathematical Economics. His work bridges theoretical economics with practical applications, addressing issues like market fundamentals, contractual complexity, and policy design under uncertainty. Over 49 peer-reviewed publications and 12 case studies reflect his interdisciplinary impact across economic theory and applied fields.

Andrzej Nowakمشاهده پروفایل

استاد

• Game theory
• Nash equilibria in non-zero-sum stochastic games
• Mathematical economics
• +۱۹ مورد دیگر

Andrzej Nowak is a Professor at the Institute of Mathematics, University of Zielona Gora, specializing in game theory, mathematical economics, and applied mathematics with significant applications in economics and finance. His academic profile includes: Research on Nash equilibria in non-zero-sum stochastic games with constraints on player strategies Work on Recursive Utilities in Dynamic Economic Models and General Equilibrium Theory Investigations of Risk Measures in Dynamic Programming and Markovian Decision Processes Analysis of multivariate linear models and Inclusions and multivalued stochastic equations Studies of Preference models using graded and interval relations for decision support systems Professor Nowak teaches fundamental courses in game theory, mathematical economics, and mathematical foundations of economics in finance (including portfolio analysis, capital market lines, and time series). He also covers probability theory and stochastic processes with applications to economics and finance, particularly Markov chain theory and discrete-time martingales. His broader research encompasses: Approximation theory using Fourier series and summability methods Combinatorial geometry including partitions of n-dimensional space Mathematical means and their invariance properties Applications of computer science to secure data transmission and privacy standards

Caspar Oesterheldمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Theoretical Computer Science
• Game Theory
• +۴ مورد دیگر

Caspar Oesterheld is a doctoral student and Researcher at the Computer Science Department of Carnegie Mellon University, supervised by Vincent Conitzer . He focuses on foundational topics in theoretical computer science, game theory, and AI safety. His work includes program equilibrium, decision theory, and cooperative AI. Education : Pursuing PhD in Computer Science at CMU Advisor : Vincent Conitzer Teaching : Co-instructor for CMU CS 15-784 – Foundations of Cooperative AI (Fall 2022), and TA at Duke University (2019–2020). His research spans game theory, decision theory, and AI safety. Notable contributions include simulation-based program equilibria, analysis of imperfect recall games, and cooperative AI foundations. His work often intersects with multi-agent systems, Pareto improvements, and ethical AI design. Caspar has published extensively at top venues like AAAI, ICML, and NeurIPS. His recent work explores surrogate goals, observational interference, and dataset creation for decision-theoretic reasoning. He received the AI Alignment Prize and Duke CS Outstanding TA award . Grants : FLI AI existential risk fellowship Peer-reviewed publications : 15+ papers on game theory, AI safety, and decision theory Reviewing : EC, ICML, NeurIPS, and others

Errikos Melissinosمشاهده پروفایل

استادیار

• Macroeconomics
• Finance
• Monetary Economics
• +۳ مورد دیگر

Errikos Melissinos is an Assistant Professor of Finance at Özyeğin University's Faculty of Business. He holds a PhD in Economics from Goethe University Frankfurt, an MA in Economics and Finance from the Barcelona School of Economics, and a Bachelor's in Law from the University of Athens. His research focuses on monetary economics, asset pricing, and computational methods, with special emphasis on real term premia in consumption-based models and solution methods for complex economic models. Prior to his current position, he worked at the Leibniz Institute for Financial Research SAFE and the Deutsche Bundesbank. His research explores topics such as stochastic volatility effects on bond premia, perturbation methods for recursive utility models, and multidimensional skill learning in labor markets. Current work in progress includes analysis of stock market participation and equity premium puzzles, as well as regional Phillips curve dynamics. Teaching responsibilities include courses in Finance (FIN202), Investments (FIN301), and International Finance (FIN401). No scientific awards are explicitly mentioned, though his active research output indicates potential for future recognition. He has no listed advisees/students or grant information in the provided materials. His work frequently intersects with computational techniques applied to macro-finance problems, reflecting a strong methodological focus complementing his theoretical contributions.

Caroline Salfingerمشاهده پروفایل

پژوهشگر

• Artistic Research
• Gender Studies
• Curatorial Practice
• +۵ مورد دیگر

Caroline Salfinger is a PhD candidate and University Assistant in the PhD Research Collective at the University of Art and Design Linz . Her work bridges artistic practice (painting, photography) with theoretical exploration of liminal moments, ambivalence, darkness, and melancholy through an artistic-scientific lens. Born 1991 in Grieskirchen Studied Fine Art (Painting & Graphics) and Applied Cultural Studies at University of Art and Design Linz (Diploma with Distinction 2018/2022) Current research: Spaces of Loneliness: Figures of Refusal and Their Relationship to Space (Artistic Research) Notable scientific awards include the Emanuel & Sofie Fohn Scholarship 2022. Her exhibition history spans 2013–2024 with prominent appearances at NEXTCOMIC FESTIVAL and OÖ Kulturquartier. She contributes to cultural discourse through catalogue essays and editorial collaborations. Research trends in her work include: Intersection of spatial theory and affective states Exploration of withdrawal as creative strategy Visual representation of melancholy and resistance Curatorial practice as research method Epistemological boundaries in artistic research Gender-inflected spatial topologies As member of KUNSTSCHAFFENDEN since 2020, she participates in collective artistic practice and knowledge production.

• Dependent Type Theory
• Verification
• Interactive Theorem Proving
• +۵ مورد دیگر

Talia Ringer is an Assistant Professor at the University of Illinois Urbana-Champaign, affiliated with the Grainger College of Engineering and the Siebel School of Computing and Data Science. Her research focuses on proof engineering, formal verification, and bridging neural and symbolic proof automation. She holds a PhD in Computer Science from the University of Washington and a BS in Mathematics and Computer Science from the University of Maryland. Prior to academia, she worked at Amazon as a software engineer. Ringer is known for founding initiatives like SIGPLAN-M and the Computing Connections Fellowship, fostering inclusivity in computer science research. She has received prestigious awards including the 2023 ACM SIGPLAN Distinguished Service Award and the DARPA Young Faculty Award. Education: PhD, University of Washington (2021); BS, University of Maryland (2012) Research Areas: Dependent Type Theory, Verification, Interactive Theorem Proving, Proof Automation, Formal Methods Awards: ACM SIGPLAN Distinguished Service Award (2023), ESEC/FSE Distinguished Paper Award (2023), DARPA Young Faculty Award (2023) Her work emphasizes making formal verification accessible to programmers through tools like Proof Repair and Baldur , while advocating for ethical AI research and LGBTQ+ inclusivity. She advises a diverse team of graduate and undergraduate students in the Illinois Theorem Provers (ITP) lab, exploring topics including proof repair, reinforcement learning for proofs, and quotient type equivalences.

Larry Yueli Zhangمشاهده پروفایل

استادیار

• Social Network Analysis
• Computing Education
• Data Structures
• +۵ مورد دیگر

Larry Yueli Zhang is an Assistant Professor, Teaching Stream in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. He holds a PhD from the University of Toronto's Department of Computer Science and previously served as teaching faculty at the University of Toronto Mississauga's Department of Mathematical and Computational Sciences. His research focuses on social network analysis, information networks, and computing education. He is actively involved in curriculum development for York University's Markham Campus, including the Computer Science for Software Development (CSSD) and Digital Technologies (DT) programs. His teaching spans undergraduate courses in data structures, algorithms, computer organization, and distributed systems. Notable projects include SlideChat (an interactive slide-based discussion platform), Velocity (a course management tool), and OkShell (a human-friendly command-line interface). He has received awards such as the Alexander Graham Bell Canada Graduate Scholarship (2013) and Outstanding Master's Thesis from Tsinghua University. Larry's research emphasizes improving computing education through innovative pedagogical tools and analyzing student learning behaviors. His work includes studies on gamified quizzes, online exam strategies, and breakout room utilization in large courses.

Steven Seyedinمشاهده پروفایل

استادیار

• Radiation Oncology
• Genitourinary Cancers
• Stereotactic Body Radiation Therapy
• +۶ مورد دیگر

Dr. Steven Seyedin is a radiation oncologist at the University of California, San Francisco (UCSF), affiliated with the School of Medicine and the Department of Radiation Oncology. He specializes in treating genitourinary cancers, including prostate, kidney, bladder, and testicular cancers, utilizing advanced techniques such as stereotactic body radiation therapy and biology-guided radiotherapy. His research is focused on integrating radiation therapy with immunotherapy and targeted agents to enhance treatment efficacy. He actively participates in clinical trials and collaborates with multidisciplinary teams at UCSF to translate laboratory discoveries into clinical practice. B.A. in Biochemistry, University of California, Berkeley, 2008 M.D., University of California, Los Angeles (David Geffen School of Medicine), 2014 Internship in Medicine, University of Illinois at Chicago, 2016 Residency in Radiation Oncology, University of Iowa, 2020 Dr. Seyedin's research interests span radiation oncology , genitourinary cancers , immunotherapy integration , precision radiotherapy , and health disparities in cancer care . His work emphasizes improving clinical outcomes through technological innovation and combination therapies. His recent publications reflect a strong trend in combining radiotherapy with systemic agents, exploring biomarkers for treatment response, and addressing socioeconomic barriers in cancer care. He has published in high-impact journals such as JAMA Oncology , Frontiers in Oncology , and Cancers (Basel) . Scientific Awards and Honors: Association of Residents in Radiation Oncology Educator of the Year, 2022 ASTRO Annual Meeting Resident Recognition Award in Biology, 2020 UIHC Excellence in Clinical Teaching Award, 2020 American Brachytherapy Society HDR LDR Prostate Scholarship Workshop, 2019 RSNA Roentgen Resident Research Award (2019, 2012) ASTRO Annual Meeting Abstract Travel Award, 2018 David Geffen School of Medicine at UCLA Student Teacher Award Dr. Seyedin is actively involved in medical education and clinical research, contributing to grants and collaborative projects across UCSF. While no formal lab or independent students are listed, he mentors through clinical teaching and research collaboration. His future work is likely to continue advancing personalized radiotherapy and equitable access to cutting-edge cancer treatments.

• Macroeconomic Theory
• Financial Economics
• General Equilibrium
• +۱ مورد دیگر

Gaetano Bloise is a Full Professor at the Department of Economics of the University of Rome Tor Vergata. He specializes in Macroeconomic Theory and Financial Economics, with a focus on General Equilibrium and Political Economy [SECS-P/01]. His teaching includes the course Financial Markets Theory for the Master's Degree program, and he holds office hours on Mondays from 2pm to 4pm or by appointment. Research Interests: Robust constrained social optima under nonconvex economic environments Dynamic programming with recursive and unbounded utility Macroprudential policies and economic inefficiency Correlation between growth and marginal utility in overlapping-generations economies Contact Information: Email: gaetano.bloise@uniroma2.it Room: 2B3 - 11 Phone: +39 06 7259 5691