جست‌وجوی استاد و پژوهشگر

• Mechanism Design
• Auction Theory
• Blockchain Economics
• +۴ مورد دیگر

Mallesh M Pai is the Lay Family Associate Professor in the Department of Economics at Rice University and a CEPR Research Fellow. His research bridges mechanism design, auction theory, and blockchain economics, with applications to decentralized finance (DeFi) and privacy economics. Prior to Rice, he was a Janice and Julian Bers Assistant Professor at the University of Pennsylvania. PhD in Managerial Economics and Strategy, Kellogg School of Management, Northwestern University Bachelor's in Computer Science and Engineering, Indian Institute of Technology, Delhi His work focuses on designing robust mechanisms in environments with information asymmetry, privacy constraints, and decentralized systems. Recent publications address dynamic transaction fees, blockchain centralization, and algorithmic collusion. He serves on program committees for major conferences in computer science and economics. Indirect Persuasion (Journal of Political Economy) Dynamic Transaction Fee Mechanism Design (with Max Resnick) Collusive Outcomes via Pricing Algorithms (Marketing Science) Mallesh has received significant recognition for his work, including the Best Paper award at the American Economic Journal: Microeconomics (2021) and Best Pricing Paper from the American Marketing Association RAPSIG (2023). His research is supported by NSF grants on fair data analysis and digital privacy foundations. He teaches graduate and undergraduate courses in microeconomic theory and market design at Rice, emphasizing practical applications of theoretical models. His Erdős number is 3, reflecting interdisciplinary collaborations.

Elchanan Mosselمشاهده پروفایل

استاد

• Probability Theory
• Combinatorics
• Machine Learning
• +۴ مورد دیگر

Elchanan Mossel is a Professor of Mathematics at the Massachusetts Institute of Technology (MIT), with a joint appointment at the Institute for Data, Systems, and Society (IDSS). His research focuses on probability, combinatorics, statistical inference, and their applications to computer science and social choice theory. He earned his B.Sc. from the Open University of Israel, and both his M.Sc. (1997) and Ph.D. (2000) in Mathematics from the Hebrew University of Jerusalem. Before joining MIT in 2016, he was a faculty member at UC Berkeley and held visiting positions at the Weizmann Institute and the Wharton School of the University of Pennsylvania. Mossel's work bridges theoretical foundations and applied problems, including computational complexity, randomized algorithms, Markov random fields, and evolutionary biology. He has made significant contributions to the theory of social choice, game theory, and the mathematical underpinnings of machine learning. Notable achievements include resolving the Majority Is Stablest conjecture and advancing phylogenetic reconstruction methods. His awards include the Sloan Fellowship and Miller Fellowship. He has mentored numerous graduate students, including Sebastien Roch, Allan Sly, and Miklos Racz, and has held editorial roles in journals like the Electronic Journal of Probability . Mossel's teaching spans topics from introductory probability to advanced courses on social networks and game theory.

William Phanمشاهده پروفایل

استادیار

• Market Design
• Game Theory
• School Choice Mechanisms
• +۲ مورد دیگر

Dr. William Phan is an Assistant Professor of Economics in the Department of Economics at North Carolina State University's Poole College of Management. He earned his PhD in Economics from the University of Rochester. His research focuses on theoretical and applied market design, particularly: School choice mechanisms and assignment algorithms Matching theory with applications to education and resource allocation Game theory and incentive design Fair division and representation in allocation systems His recent work examines crowding effects in school choice and representation in reserve systems.

Hedyeh Beyhaghiمشاهده پروفایل

استادیار

• Algorithmic Game Theory
• Mechanism Design
• Machine Learning Theory
• +۳ مورد دیگر

Hedyeh Beyhaghi is an Assistant Professor in the Department of Computer Science at the University of Massachusetts Amherst , affiliated with the Manning College of Information and Computer Sciences. She holds a PhD in Computer Science from Cornell University and completed postdoctoral research at the Toyota Technological Institute at Chicago , Northwestern University , and Carnegie Mellon University . Research Interests : Her work focuses on algorithmic game theory , mechanism design , machine learning theory , and algorithms under uncertainty . She investigates strategic agent behavior, fairness in algorithmic systems, revenue maximization in auctions, and optimization under stochastic constraints. Recent Publications address topics like the Strategic Perceptron , Pandora’s Box Problem , and Fair Incentive Design , reflecting trends in strategic learning , multi-agent optimization , and fairness-aware algorithms . These studies often intersect economics , machine learning , and theoretical computer science . Teaching : She teaches COMPSCI 611 - Advanced Algorithms , covering randomized algorithms, approximation techniques, and computational complexity. Weekly quizzes and biweekly assignments emphasize collaboration policies and academic integrity in algorithm design. PhD Advisee : Amirmahdi Mirfakhar. No scientific awards are currently documented.

• Computation Theory and Mathematics
• Computer Software
• Blockchain Technology
• +۳ مورد دیگر

Ben Livshits is a Reader in Computing at Imperial College London's Department of Computing, part of the Faculty of Engineering. His research focuses on computation theory, computer software, and privacy-preserving technologies in blockchain systems. He holds a Ph.D. from Stanford University. Education: Ph.D. in Computer Science, Stanford University, 2007 Research Interests: Livshits specializes in cryptographic protocols for decentralized systems, ZK-Rollups optimization, MEV analysis, and privacy-enhancing technologies. His work bridges theoretical computer science with practical applications in blockchain scalability and security. Recent Research Trends: His 2024-2025 work emphasizes ZK-proof systems (e.g., zk-bench), MEV mitigation strategies, and formal foundations for rollups. He also explores community-driven verification (CrowdProve) and governance mechanisms for DeFi. Affiliations: He is affiliated with the Centre for Cryptocurrency Research and Engineering, contributing to interdisciplinary blockchain research. Grants & Labs: While specific grants are not listed, his work suggests involvement in Imperial's distributed systems and blockchain initiatives.

Marco Nieمشاهده پروفایل

استاد

• Transportation Engineering
• Transportation Systems Analysis
• Urban Mobility
• +۷ مورد دیگر

Marco Nie is a Professor and Chair of the Department of Civil and Environmental Engineering at Northwestern University, where he has been a faculty member since 2006. His research focuses on Transportation Systems Analysis, emphasizing interdisciplinary approaches that integrate optimization, network science, traffic flow theory, economics, and statistics to address complex interactions between human activities, infrastructure, and urban networks. He teaches three courses: an undergraduate/graduate introduction to transportation engineering, and two graduate courses on analytical and computational tools for surface transportation systems design. Education: Marco Nie earned a BS in Structural Engineering from Tsinghua University (Beijing), followed by graduate studies in Transportation at the National University of Singapore (NUS), and a PhD in Transportation from the University of California, Davis. Research interests include improving transportation efficiency, sustainability, and equity through policy and technology. Recent work explores autonomous vehicles, modular transit systems, congestion pricing, and data-driven solutions for EV charging and ride-hail platforms. He has expressed challenges in securing research funding, noting its critical role despite inherent flaws in evaluating research impact through monetary metrics. Scientific Awards: He received the 2021 Transportation Science Meritorious Service Awards . Marco also serves on editorial boards, including Service Science (2023), and actively publishes on topics like urban mobility, freight logistics, and policy analysis. Advising & Grants: While no specific students or grants are listed, he highlights the importance of funding mechanisms for research. His work often involves collaborations with sponsors and stakeholders to address real-world transportation challenges. Labs/Teams: Affiliated with the Center for Science and Protection of Engineered Environments and engages in interdisciplinary research groups focusing on sustainable and equitable urban systems.

Aurelien Baillonمشاهده پروفایل

استاد

• Behavioral Economics
• Decision Making Under Risk and Ambiguity
• Subjective Probability Elicitation
• +۱۲ مورد دیگر

Dr. Aurelien Baillon is a Professor of Economics of Uncertainty at the Erasmus School of Economics , Erasmus University Rotterdam, specializing in the Department of Applied Economics . His research focuses on individual decision-making under risk and ambiguity, combining empirical and theoretical approaches to understand probability elicitation and expert opinion aggregation. Key research areas: Behavioral Economics, Risk Attitudes, Bayesian Modeling Major projects: Bayesian Markets , Personal Model of Trumpery , Malakoff Humanis Chair His recent publications explore ambiguity theories , cybersecurity decision-making , and linguistic deception detection . Notable grants include the ERC Starting Grant (2016) and NWO Vidi Grant (2014). Collaborations span institutions like BRiO , HITS Institute , and GATE . The Datavisualization project with Alice Havrileck demonstrates his interdisciplinary approach to uncertainty analysis.

• Mechanism Design
• Auction Theory
• Behavioral Operations Management
• +۳ مورد دیگر

Xiaoshuai Fan is an Associate Professor at the College of Business, Southern University of Science and Technology, where she has been affiliated since 2020. Her academic background includes a PhD in Industrial Engineering and Logistics Management from HKUST (2020) and a Bachelor's in Management from Huazhong University of Science and Technology (2015). Education: PhD (2020), Industrial Engineering and Logistics Management, Hong Kong University of Science and Technology Bachelor (2015), Management, Huazhong University of Science and Technology (Management Innovation Experimental Class) Her research focuses on Mechanism Design and Auction Theory under asymmetric information, with applications to Behavioral Operations Management , Sustainable Operations (particularly poverty, income inequality, and carbon emissions), and Supply Chain Management . Recent work explores pay transparency in behavioral economics, carbon emission control through price commitments, and anti-corruption strategies in procurement systems. The 15 most recent publications highlight trends in asymmetric information theory , collusion-resistant contract design , and equity-focused operations research . Key journals include Management Science , Production and Operations Management , and Manufacturing & Service Operations Management . She serves as a doctoral supervisor and has secured research funding from the NSFC Outstanding Young Scholars Program , NSFC Youth Program , and the Shenzhen Science and Technology Innovation Commission . Her lab actively recruits research assistants and postdocs, emphasizing interdisciplinary collaboration in economic, mathematical, and computational fields.

Fang Kongمشاهده پروفایل

استادیار

• Online Learning
• Reinforcement Learning
• Machine Learning
• +۴ مورد دیگر

Fang Kong is an Assistant Professor in the Department of Statistics and Data Science at the Southern University of Science and Technology (SUSTech). He earned his PhD in Computer Science from Shanghai Jiao Tong University under the supervision of Prof. Shuai Li and received his Bachelor's degree in Software Engineering from Shandong University. Education: PhD in Computer Science, Shanghai Jiao Tong University (2020-2024) Bachelor's Degree in Software Engineering, Shandong University (2016-2020) Dr. Kong is broadly interested in developing theoretically guaranteed algorithms for sequential decision-making problems, with particular focus on multi-armed bandits and reinforcement learning, as well as their applications in online experimentation and recommendation systems. His research spans theoretical foundations of bandit algorithms, matching markets, influence maximization, and online learning under various feedback structures. He has made significant contributions to the understanding of best-of-both-worlds algorithms that perform well in both stochastic and adversarial environments. His publication record shows a strong trajectory of high-impact work in top-tier conferences including NeurIPS, ICML, ICLR, AAAI, WWW, and AAMAS. His research demonstrates expertise in theoretical machine learning with a focus on bandit algorithms, particularly in matching markets and sequential decision-making problems. His work often bridges theoretical guarantees with practical applications in recommendation systems and online experimentation. Scientific Awards: CCF Doctoral Dissertation Award in Agent and Multi-Agent Systems (2025) Baidu Scholarship (2024) National Scholarship for PhD students (2023, 2022) AAMAS Student Scholarship (2023) Microsoft Research Asia Excellence Award (2022) Dr. Kong actively mentors students at various levels, including PhD and Master's students at SUSTech, visiting students from other institutions, and undergraduate researchers. He serves as a reviewer for top machine learning conferences (ICLR, NeurIPS, ICML, WWW) and journals (IEEE PAMI, TMLR). His teaching includes graduate Machine Learning and undergraduate Artificial Intelligence courses at SUSTech.

• Human-AI Value Alignment
• Ethical Machine Learning
• Algorithmic Fairness
• +۵ مورد دیگر

Neil S. Gaikwad is an Assistant Professor at the University of North Carolina, Chapel Hill, in the School of Data Science and Society and Department of Computer Science. He holds a PhD in Society-Centered AI from MIT and has affiliations with the MIT Dalai Lama Center for Ethics and UNC’s Parr Center for Ethics. His research focuses on Human-AI Alignment, ethical machine learning, and policy design for global equity, particularly in underserved populations. His work integrates ethical principles into AI systems to address societal disparities, climate change, and algorithmic fairness. Dr. Gaikwad has led projects such as the AI and Policy research program, developed systems like Daemo and EteRNA, and contributed to high-impact publications in AAAI, ACM CSCW, and PNAS. He has mentored over 30 students, many of whom have secured fellowships and advanced AI fairness research. Awards include MIT’s Karl Taylor Compton Prize and Facebook Research Fellowship. His teaching spans courses on AI ethics, policy, and societal impact at MIT, CMU, and UNC, with student evaluations praising his mentorship and course design. He has advised global institutions like the UN and EU on AI policy, and his work bridges academia, industry, and policy through initiatives like Data-driven Humanitarian Mapping. His art installations, such as Beyond Boundaries , explore environmental and ethical themes, reflecting his interdisciplinary approach to science and society.

Rakesh V. Vohraمشاهده پروفایل

استاد

• Economics
• Computer Science
• Game Theory
• +۵ مورد دیگر

Rakesh V. Vohra is the George A. Weiss and Lydia Bravo Weiss University Professor at the University of Pennsylvania, holding primary appointments in the departments of Computer and Information Science, Economics, and Electrical and Systems Engineering. He co-directs the Warren Center for Network and Data Sciences. His research spans game theory, market design, auction theory, and computational economics, with a focus on mechanism design, spectrum markets, and systemic risk in financial networks. He explores interdisciplinary topics such as NFTs, blockchain applications, and algorithmic fairness in healthcare equity. His work integrates economic theory with computational methods, addressing challenges in resource allocation, strategic behavior, and network dynamics. Recent studies analyze optimal bailouts in financial systems, sequential information acquisition, and the implications of unlicensed spectrum policies on wireless competition. He also investigates behavioral aspects of decision-making under uncertainty and the design of robust economic systems. Notable contributions include foundational work on combinatorial auctions, stable matching mechanisms under constraints, and the role of network effects in market stability. Though no formal awards are listed, his prolific publication record reflects significant academic influence across multiple disciplines.

Mikhail Safronovمشاهده پروفایل

دانشیار

• Microeconomic theory
• Game theory
• Mechanism design
• +۴ مورد دیگر

Dr. Mikhail Safronov is a University Associate Professor in Economics at the Faculty of Economics , University of Cambridge, and a Fellow of St Catharine's College. He holds a PhD in Economics from Northwestern University and completed postdoctoral work at the University of Cambridge.

• Economic Theory
• Behavioral Economics
• Mechanism Design
• +۷ مورد دیگر

Shengwu Li is a Professor of Economics at Harvard University, specializing in economic theory and behavioral economics. His research focuses on designing simple and transparent economic systems, particularly addressing computational complexity challenges. He has contributed to mechanism design, auctions, and market design, emphasizing cognitive simplicity and bounded rationality. Key research interests include obviously strategy-proof mechanisms, cursed equilibrium extensions, and the effects of salary benchmarking. His work spans dynamic matching markets, fairness in bargaining, and the ethical dimensions of market design. Awards: Aliprantis Prize (2017), Exeter Prize (2018), EC'18 SIGecom Best Paper Award Notable Projects: Salary benchmarking studies, cursed equilibrium dynamics, and fair bargaining norms Literature Contributions: Maintains a curated page on obviously strategy-proof mechanisms and related literature His research integrates theoretical insights with empirical data, addressing real-world applications in labor markets, auctions, and negotiation systems.

Andrew Randallمشاهده پروفایل

استاد

• Environmental Engineering
• Wastewater Treatment
• Biological Nutrient Removal
• +۵ مورد دیگر

Andrew Randall is a Professor and Graduate Program Director in the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida, College of Engineering and Computer Science. He has been a faculty member at UCF since 1994, contributing significantly to environmental engineering education and research. Education: Bachelor of Science in Civil Engineering, Virginia Tech (1984) Master of Science in Civil Engineering, Virginia Tech (1987) Doctor of Philosophy, Auburn University (1993) Dr. Randall's research focuses on advanced wastewater treatment technologies, particularly in biological nutrient removal, sludge fermentation, high-rate activated sludge systems, and water recycling . His work integrates process optimization, modeling, and sustainable resource recovery from waste streams. He has made significant contributions to understanding intracellular storage mechanisms and microalgal-integrated treatment systems. His recent publications reflect a strong trend toward resource recovery, energy efficiency, and sustainable water reuse , with applications in municipal and military contexts. The studies span from lab-scale fermentation optimization to full-system modeling and toxicity evaluation, showcasing a systems-level approach to environmental engineering challenges. Scientific Awards: UCF Teaching Incentive Program Award (2010) UCF CEE Department Excellence in Undergraduate Teaching Award (2007) Journal of Environmental Engineers (ASCE) Editor Award for Service (2004) Outstanding Young Alumni Award, Virginia Tech (2002) Dr. Randall has actively advised graduate students, including Sultan K. Salamah and T.M. Nogaj, and has served on numerous thesis committees. His research has been supported through institutional and professional recognition, though specific grant details are not provided in the text. He is a key figure in graduate education as the Graduate Program Director, shaping curriculum and student development. His work often involves interdisciplinary collaboration, particularly in developing integrated biological systems for water treatment and reuse, including microalgal-based processes and high-rate activated sludge. These efforts align with emerging trends in circular economy and low-carbon technologies in the water sector.

• Multi-Agent Systems
• Computational Intelligence
• Smart Energy Systems
• +۴ مورد دیگر

J.A. La Poutré is a Full Professor at Delft University of Technology and a Scientific Staff Member at CWI (Centrum Wiskunde & Informatica) in the Intelligent and Autonomous Systems group. He holds part-time positions and is involved in research on multi-agent systems and computational intelligence for smart energy systems, with a focus on market-based optimization and fairness in network congestion management. PhD in computer science (Utrecht University, 1991) MSc in mathematics (TU Eindhoven, 1986) His research spans algorithm design, game theory, and reinforcement learning applied to energy systems, particularly smart grids and market mechanisms. Recent publications address cybersecurity threats in power networks, auction-based energy trading, and AI integration in media sectors. The 2019–2025 publications highlight his work in combining game theory with smart grid optimization , covering topics such as topology attacks , demand-side bidding , and fair congestion management . Papers frequently involve reinforcement learning , metaheuristics , and market mechanisms . Scientific Awards : Best paper award at GECCO-2015 KNAW fellow (Utrecht University, 1991–1997) He has led funded projects like Computational Capacity Planning in Electricity Networks (STW program) and co-chairs the Commit2Data Energy division. La Poutré also serves as Vice President of ERCIM (European Research Consortium for Informatics and Mathematics).