جست‌وجوی استاد و پژوهشگر

Hugo Duminil-Copinمشاهده پروفایل

استاد

• Mathematical Physics
• Combinatorics
• Probability Theory
• +۳ مورد دیگر

Hugo Duminil-Copin is a Full Professor at the University of Geneva (appointed 2013) and a permanent professor at the Institut des Hautes Études Scientifiques (IHES) in Bures-sur-Yvette (since 2016). He leads the Analysis, Mathematical Physics and Probability research group at the University of Geneva's Section of Mathematics. Born in 1985 in the Paris region, he graduated from the École Normale Supérieure (ENS) in Paris and the University of Paris-Saclay. His primary research explores probabilistic aspects of mathematical physics and combinatorics, with specific focus areas including: Statistical mechanics and phase transitions Percolation theory and random cluster models Lattice models and critical phenomena Combinatorial inequalities and probability theory His publications (2019-2024) predominantly address statistical mechanics, combinatorial optimization, and number theory, featuring rigorous analysis of lattice models, phase transitions, and mathematical physics frameworks. Recent works demonstrate advanced studies on the Blume-Capel model, Brunn-Minkowski inequalities, and self-avoiding walks. Awards include: Fields Medal (2022) for transformative contributions to statistical physics He supervises doctoral candidates and postdoctoral researchers, currently guiding PhD students Émile Averous , Aman Markar , and Tiancheng He , among others. His research group includes postdoctoral scholars Remy Mahfouf , Florian Schweiger , and Wildemann Peter .

Eric L. Grinbergمشاهده پروفایل

استاد

• Integral Geometry
• Mathematical Analysis
• Geometric Analysis
• +۳ مورد دیگر

Eric L. Grinberg is a Professor in the Department of Mathematics at the University of Massachusetts Boston, affiliated with the College of Science and Mathematics. He holds a Ph.D. in Mathematics from Harvard University. His research focuses on integral geometry, geometric analysis, and their applications, with notable contributions to Radon transforms, X-ray transforms, and geometric inequalities. Education: Ph.D. in Mathematics, Harvard University Research interests include: Integral transforms (Radon, X-ray) Geometric analysis (Busemann-Petty problems, convex bodies) Applications in discrete mathematics and algebra Recent work explores matrix theory, geometric puzzles, and finite field geometry. His articles often bridge theoretical mathematics with applied problems in imaging and signal processing. No awards listed. Advising and grants details are not explicitly provided in the text. He collaborates with researchers like Mehmet Orhon on geometric projects. Office: Wheatley 3-154-10.

Vasanth Sarathyمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• Natural Language Processing
• Neuro-symbolic Machine Learning
• +۷ مورد دیگر

Vasanth Sarathy is a Research Assistant Professor of Computer Science at Tufts University, specializing in the intersection of Artificial Intelligence and Natural Language Processing. His work combines neuro-symbolic machine learning techniques with social and cognitive sciences to develop socially-competent and safe AI systems. Education: Ph.D. in Computer Science and Cognitive Science, Tufts University (2020) Juris Doctor (J.D.), Boston University School of Law (2010) M.S. in Electrical Engineering and Computer Science, MIT (2005) B.S. in Electrical Engineering, University of Arkansas (2003) His research spans three interconnected themes: Social NLP, Reasoning with Social Norms, and Sense-making and Problem-Solving. Through Social NLP, he develops computational methods to uncover patterns in human social behavior using qualitative texts. His work on Reasoning with Social Norms focuses on building AI architectures that can understand and apply social norms in reasoning and language interpretation. His Sense-making research explores how humans and AI systems simplify complex worlds for efficient problem-solving. His recent publications demonstrate a growing trend toward integrating Large Language Models with symbolic reasoning for more trustworthy AI. His work spans applications including automated writing assistance, intelligent tutoring, fact-checking, social media content moderation, and embodied social robots. His research shows particular strength in developing methods that combine neural and symbolic approaches to address complex social reasoning tasks that neither approach could solve alone. Previously, Dr. Sarathy worked as a Senior Researcher of AI at Smart Information Flow Technologies, collaborating with the U.S. Department of Defense and Intelligence Community. Before his AI career, he practiced intellectual property law at Ropes and Gray for nearly a decade. His unique interdisciplinary background bridges technology, law, and cognitive science. He advises students in AI, NLP, and cognitive systems, with research supported by grants from DARPA and other government agencies. His work has applications in human-robot interaction, social media analysis, and educational technologies. Outside academia, he creates single-panel cartoons, practices martial arts, plays chess, and designs puzzle video games. His interdisciplinary journey from law to AI has been featured in a BU Law article.

Lucas Lehnertمشاهده پروفایل

استادیار

• Reinforcement Learning
• Sequential Decision Making
• Generative AI
• +۴ مورد دیگر

Lucas Lehnert is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan, specializing in Artificial Intelligence and Reinforcement Learning (RL). His research focuses on how intelligent systems can learn to solve complex decision-making tasks through representation learning, abstraction mechanisms, and lifelong learning strategies. He also explores applications of AI/RL in scientific and engineering domains. Education: PhD in Computer Science (Brown University, 2021), MSc (McGill University, 2016), BSc (McGill University, 2014). Postdoctoral positions included Meta's FAIR team (2022–2024) and the Mila Quebec AI Institute (2021–2022). Research interests include reinforcement learning fundamentals, generative AI reasoning, exploration strategies, and reward-predictive representations. His work bridges model-based and model-free RL paradigms, emphasizing scalable and generalizable solutions. Awards include the Best Student Workshop Paper Award (2017) and an NIMH training grant in cognitive neuroscience. His research has been published in top conferences like NeurIPS, ICML, and ICLR. He advises graduate students in RL and collaborates on projects involving transformer-based planning, exploration algorithms, and multi-agent systems. Current work includes developing SearchFormer for efficient planning tasks and exploring maximum entropy exploration methods.

Mikael Pichotمشاهده پروفایل

دانشیار

• Geometric Group Theory
• Analysis
• Group Theory
• +۳ مورد دیگر

Mikael Pichot is an Associate Professor in the Department of Mathematics and Statistics at McGill University, located in Montreal, Quebec. His research focuses on Geometric Group Theory, Analysis, and related areas such as Operator Algebras and Metric Geometry. He is actively involved in organizing academic events and seminars, including the Group Theory Seminar and CRM-ISM Colloquium, and has contributed to numerous collaborations, often with co-authors like Sylvain Barre and Robert Graham. His teaching includes courses such as Math 223 (Linear Algebra) and Math 570/571 (Higher Algebra sequences). Pichot's research interests span topics like geometric group actions, sofic dimension, L2 invariants, and random groups. He has published extensively in peer-reviewed journals and presented at international conferences. His work often bridges algebraic, geometric, and analytic approaches to group theory. Despite his active academic contributions, no specific awards or grants are explicitly listed in the provided texts. He maintains a personal webpage and collaborates on projects such as 'Surgery on discrete groups' and 'Random groups and nonarchimedean lattices.' His research also touches on foundational questions in operator algebras and geometric topology, reflecting a deep engagement with the structural properties of groups and their applications.

Vardges Melkonianمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Network Design Problems
• Approximation Algorithms
• +۷ مورد دیگر

Vardges Melkonian is an Associate Professor in the Department of Mathematics at Ohio University, part of the College of Arts and Sciences. His academic work bridges theoretical and applied mathematics, with a strong emphasis on optimization and algorithmic problem-solving. Research Interests: Dr. Melkonian specializes in combinatorial optimization, network design, approximation algorithms, and applications of operations research. His research integrates mathematical programming and discrete modeling to solve complex real-world scheduling and allocation problems. These interests are reflected in his extensive publication record spanning sports leagues, hybrid work, exercise routines, and social partitioning. Publication Trends: Over the past decade, his scholarly output has consistently focused on developing integer programming and optimization models for diverse domains—from recreational puzzles like KenKen to large-scale logistical challenges in manufacturing and public policy. His work demonstrates a unifying theme: transforming practical problems into formal mathematical frameworks for efficient solution. Scientific Awards: No awards are mentioned in the provided text. Advising and Grants: The available information does not list any students or grant funding. However, his research contributions suggest active engagement in academic mentorship and potential involvement in funded projects, though specifics are not disclosed. Labs and Research Teams: There is no mention of specific labs, research groups, or collaborative teams associated with Dr. Melkonian in the provided content.

Ning Baoمشاهده پروفایل

استادیار

• High Energy Physics
• Quantum Information Science
• Quantum Algorithms
• +۴ مورد دیگر

Ning Bao is an Assistant Professor in the Departments of Physics and Mathematics at Northeastern University's College of Science. His research bridges high energy theory and quantum information science, focusing on topics such as holographic correspondences, quantum entanglement classification, and quantum algorithm development. He explores the interplay between quantum information principles and fundamental physics concepts like black hole thermodynamics and spacetime geometry. His work often involves cutting-edge techniques from machine learning and applied mathematics to address questions in quantum gravity and condensed matter systems. Key research interests include the information-theoretic properties of black holes, entanglement structure in holographic systems, and the application of quantum information tools to machine learning. He contributes to foundational studies in quantum error correction, entanglement wedge reconstruction, and the ER=EPR conjecture. His articles span topics from AdS/CFT correspondence to quantum cellular automata, reflecting his interdisciplinary approach to theoretical physics. Bao’s research is supported by contributions to holographic entropy inequalities, tensor network models, and the exploration of quantum algorithms through frameworks like classical shadows and reinforcement learning. His work has advanced understanding of entanglement in gauge theories, quantum complexity measures, and the interplay between geometry and quantum information in gravitational systems.

• Combinatorics
• Combinatorial Design
• Latin Squares
• +۵ مورد دیگر

Ian Wanless is a Research Professor at the School of Mathematics, Monash University. He specializes in combinatorics, with a focus on Latin squares, graph theory, and matrix permanents. His work bridges theoretical mathematics and applications in information technology, such as coding and experimental design. Wanless leads collaborative projects funded by the Australian Research Council, including studies on combinatorial structures and hypergraph matchings. He has authored over 120 peer-reviewed articles, with recent work addressing quantum states, Latin square properties, and quasigroup isomorphisms. Key Awards: Australian Mathematical Society 2009 Medal Collaborations: Global partnerships with institutions in the US, Europe, and Asia His research emphasizes universal solutions to combinatorial puzzles, such as Sudoku and the four-color theorem, while prioritizing theoretical rigor over direct applications.

• Card-based Cryptography
• Puzzle Complexity Analysis
• Secure Multi-Party Computation
• +۳ مورد دیگر

Suthee Ruangwises is a Lecturer at the Department of Computer Engineering, Chulalongkorn University. He holds a PhD and Master's from Tokyo Institute of Technology (2020 and 2017) under Prof. Toshiya Itoh and Prof. Osamu Watanabe, and a Bachelor's from MIT (2015). His research focuses on card-based cryptography, puzzle complexity analysis, and matching under preferences, with notable work on physical zero-knowledge proofs and NP-completeness proofs for puzzles. Postdoctoral positions at Tokyo Institute of Technology (2020–2024) and University of Electro-Communications (UEC). Recipient of the Best Paper Award at APKC 2025 for work on Sumplete puzzles. Active in international conferences such as UCNC, CiE, and WALCOM. Research interests span secure multiparty computation, graph algorithms, and cryptographic protocol design. He maintains databases of card-based cryptography papers and NP-completeness proofs for pencil puzzles. His Erdős number is 3 via collaboration with Toshiya Itoh. Teaching includes Computational Theory at Chula. Recent publications emphasize innovations in physical cryptographic protocols and puzzle-based computational problems, reflecting his interdisciplinary approach at the intersection of cryptography, algorithms, and combinatorics.

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.

• Cryptography
• Coding Theory
• Sequences and Their Applications
• +۵ مورد دیگر

Oğuz Yayla is a full-time faculty member at Middle East Technical University (METU), Türkiye, active in research and graduate supervision. His scholarly output comprises 57 Web-of-Science-indexed publications, 31 peer-reviewed conference papers and numerous invited talks, with a WoS h-index of 13 and Scopus h-index of 3 (as of the latest data dump). Research Interests Algebraic and applied cryptography, including post-quantum schemes Coding theory, particularly algebraic-geometry codes and codes over rings Sequences with good correlation properties for CDMA, stream ciphers and 5G/6G applications Blockchain security, distributed consensus, and IoT-medical data integrity Hardware-oriented security: TRNG design, side-channel countermeasures on FPGA/SoC Over the past decade, his publications reveal a clear evolution from foundational work on finite fields and pseudorandom sequences toward practical cryptographic engineering, including verifiable timed signatures, threshold multi-secret sharing for blockchain storage, and FPGA-based true random number generators compliant with AIS-20/31. Scientific Awards & Recognition Consistently high citation impact: >34 WoS citations and >20 Scopus citations PlumX reader and capture metrics place him in top percentiles for cryptography outputs in Türkiye Principal investigator / senior researcher on 7 funded national projects Graduate Advising & Collaborative Grants Yayla has formally supervised 15 graduate theses (MS and PhD) in mathematics and cryptography. He leads or co-leads multiple TÜBİTAK and BAP-funded projects on post-quantum cryptography, secure IoT medical devices, and code-based cryptography. Laboratory & Teams He heads the Cryptography & Information Security Research Group at METU, where a multidisciplinary team of graduate students and post-doctoral researchers work on lattice-based cryptography, side-channel analysis, and blockchain protocol design.

Li Haitaoمشاهده پروفایل

استاد

• Asset Pricing
• Financial Engineering and Derivatives
• Credit Risk
• +۷ مورد دیگر

Li Haitao serves as Dean, Dean's Distinguished Chair Professor of Finance, and Director of the Family Business Research Center at Cheung Kong Graduate School of Business (CKGSB). Holding a PhD from Yale University, he previously held faculty positions at the University of Michigan's Stephen M. Ross School of Business and Cornell University's Johnson Graduate School of Management. His academic leadership extends to editorial roles at Management Science and the International Review of Finance . Education: PhD in Finance, Yale University Professor Li's research spans quantitative finance with emphasis on asset pricing anomalies, derivative securities valuation, and fixed income modeling. His work integrates advanced mathematical techniques including Lévy processes and Bayesian analysis to address complex market phenomena. Key contributions examine volatility smiles in interest rate caps, survival bias in equity returns, and nonparametric estimation of state-price densities. His expertise bridges theoretical finance with practical applications in hedge fund performance evaluation and corporate risk management. His publication record reveals consistent contributions to top finance journals including the Journal of Finance , Review of Financial Studies , and Journal of Financial Economics , with research evolving from foundational term structure modeling toward contemporary challenges in liquidity risk and machine learning applications in finance. Scientific Awards: Sanford R. Robertson Professorship, University of Michigan (2007-2008) NTT Research Fellowship, University of Michigan (2006-2007) Q-Group Research Grant (2004) Best Student Paper Award, Eastern Finance Association (1997) Trefftz Award, Western Finance Association (1996) Sterling Prize Fellowship, Yale University (1991-1993) Professor Li actively contributes to academic governance through editorial board service while directing CKGSB's Family Business Research Center. His current research agenda focuses on AI applications in financial markets and China's evolving role in global finance, evidenced by recent speaking engagements at the 2025 Summer Davos and Boao Forum for Asia. He serves on the editorial boards of Management Science (Finance Department) and the International Review of Finance . As Director of the Family Business Research Center, he leads initiatives examining succession planning in Chinese family enterprises and cross-border investment patterns, with recent projects analyzing Macau's casino industry leadership transitions and China-Africa economic relationships.

Haohan Wangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Computational Biology
• Healthcare Applications
• +۵ مورد دیگر

Haohan Wang is an Assistant Professor at the University of Illinois Urbana-Champaign's School of Information Sciences, with affiliations to the Carl R. Woese Institute for Genomic Biology and the National Center for Supercomputing Applications. His research focuses on developing trustworthy machine learning methods for computational biology and healthcare applications , emphasizing robustness , causality , and interpretability in vision-based models. Recent research trends in his work include: Large Language Model interactions with biomedical challenges (GenoAgent, GenoTex) Adversarial security in language and vision models (Guard, Jailbreakzoo) Genomic data analysis through robust machine learning frameworks (Precision Lasso, Kernel Mixed Models) Interactive toolkits like Robustar for data annotation and model training Scientific awards include recognition as Baidu's Top 50 AI+X Rising Young Scholars (2022), Best Paper Honorable Mention at WSDM 2023, and Broad Institute's Next Generation status (2019). Current projects explore AI-made scientists for biomedical discovery and Robustar development for GUI-based robust vision learning.

Alexander R. Blockمشاهده پروفایل

استادیار

• Cryptography
• Coding Theory
• SNARKs
• +۷ مورد دیگر

Dr. Alexander R. Block is an Assistant Professor at the University of Illinois at Chicago (UIC) , specializing in Cryptography and Coding Theory . He focuses on the concrete security and space-efficiency of SNARKs, error-correcting codes , and locally decodable codes . Before UIC, he was a postdoctoral researcher at Georgetown University and University of Maryland , advised by Justin Thaler and Jonathan Katz. His PhD from Purdue University (2022) was supervised by Jeremiah Blocki. His research bridges theoretical and applied aspects, including field-agnostic SNARKs (CRYPTO 2024) with expand-accumulate codes, Fiat-Shamir security analysis of FRI protocols (ASIACRYPT 2023), and memory-hard puzzles in the standard model (SCN 2022). He has contributed to insertion-deletion error codes (CCC 2023) and secure computation with leaky correlations (TCC 2018, CRYPTO 2017). Dr. Block has received multiple scientific awards , including the Emil Stefanov Fellowship (2021) and Purdue Three Minute Thesis Competition Finalist (2022). His teaching includes courses like UIC's CS 505 - Computability and Complexity Theory (Spring 2025), where he emphasizes interactive proofs and zero-knowledge systems . He actively serves on program committees for CRYPTO , EUROCRYPT , and ZKProof Workshop , and has reviewed for leading journals and conferences.

Iftach Haitnerمشاهده پروفایل

استاد

• Cryptography
• Computational Complexity
• Secure Computation
• +۳ مورد دیگر

Iftach Haitner is a Professor at Tel Aviv University's School of Computer Science, currently on leave while serving as Principal Researcher at the Stellar Development Foundation. His primary academic affiliation remains with Tel Aviv University where he maintains an active research group and supervises multiple PhD students. His educational background includes a PhD (2008) and Master's degree from the Weizmann Institute of Science under Omer Reingold and Oded Goldreich respectively, and undergraduate studies in Mathematics and Computer Science at Tel Aviv University. His research focuses on Cryptography and Computational Complexity , with significant contributions to coin-flipping protocols, one-way functions, differential privacy, and secure computation. Analysis of his 15 most recent publications reveals consistent focus on foundational cryptographic problems. His work demonstrates strong emphasis on computational entropy concepts (inaccessible entropy, next-block pseudoentropy), protocol security against adaptive adversaries, and tight complexity bounds for cryptographic primitives. The publications span top venues including STOC, FOCS, Crypto, and Eurocrypt, showing sustained high-impact research output. The Kadar Family Award for Outstanding Research (2018) Tel Aviv University Rector's Awards for Excellence in Teaching (2017, 2018) SIAM Outstanding Paper Prize (2011) Intel Israel award for outstanding PhD students (2008) Multiple best paper awards (CRYPTO 2006, ICALP 2006) Haitner has advised numerous PhD students including Noam Mazor, Jad Silbak, and Eliad Tsfadia. His research has been supported by multiple Israel Science Foundation grants (2011-2023), an ERC Starting Grant (2015-2020), and Blavatnik ICRC grants. He also maintains industry connections through roles at Coinbase (2022-2024) and previous consulting positions at Unbound Security and Team8. His professional service includes editorial work for SIAM Journal on Computing and program committee memberships for major cryptography conferences including Crypto, Eurocrypt, and TCC. He co-organizes the Greater Tel Aviv Area Cryptography Seminar and other specialized workshops.