جستجوی استاد راهنمای دانشگاهی

Shie Mannorمشاهده پروفایل

استاد

• Machine Learning
• Reinforcement Learning
• Game Theory
• +۸ مورد دیگر

Shie Mannor is a Professor at the Technion - Israel Institute of Technology in the Department of Electrical Engineering. He also holds a visiting professorship at Cornell-Tech in New York City and is affiliated with the Technion Machine Learning Center and the Grand Technion Energy Program . Key Research Interests: Machine Learning: Theory, algorithms, and applications to high-dimensional data and dynamics modeling. Reinforcement Learning and Markov Decision Processes: Adaptive control in large stochastic systems. Learning and control under uncertainty: Robust/stochastic optimization frameworks. Game Theory: Stochastic, dynamic, and network games applied to power markets and resource allocation. Multi-agent systems: Online learning and designing economic systems with optimal equilibria. Power Grid: Data-driven reliability, pricing, and decision-making in smart grids (e.g., EU-funded GARPUR project). Applications: Communication network optimization, mobile health, LDPC codes, and large-scale optimization problems. He actively seeks postdocs, graduate, and undergraduate students with strong mathematical or programming skills for projects in mobile phone programming and complex system optimization. Contact: shie.mannor@ee.technion.ac.il | Phone: ++972-4-829-3284

Noam Nisanمشاهده پروفایل

استاد

• Algorithmic Game Theory
• Economics and Computation
• Computer Science
• +۴ مورد دیگر

Noam Nisan is a Full Professor at the School of Computer Science and Engineering at the Hebrew University of Jerusalem, Israel. He is a member of the Center for the Study of Rationality and the Israeli Academy of Sciences and Humanities. He also serves on the Board of Directors of the National Library of Israel and chairs its Digital Strategy Subcommittee. Additionally, he is a Principal Researcher at Starkware, focusing on blockchain technologies. His research bridges Computer Science, Game Theory, and Economics, particularly in algorithmic game theory and electronic markets. Education: Ph.D. in Computer Science, University of California, Berkeley (1988), advised by Richard Karp B.Sc. summa cum laude in Mathematics and Computer Science, Hebrew University (1984) Research Interests: Algorithmic Game Theory, Economics and Computation, Electronic Markets, Auction Design, and Mechanism Design . His work explores strategic interactions in computational systems, including market equilibria, fair division, and decentralized resource allocation. Key Contributions: Co-authored foundational texts like Algorithmic Game Theory and Elements of Computing Systems Pioneered work on pseudorandom generators, communication complexity, and secure multi-party computation Grants & Awards: Holder of major grants (e.g., ERC, Binational Science Foundation) and honors including the Gödel Prize (2012), Knuth Award (2015), and STOC Test of Time Award (2022). Service: Extensive editorial roles (e.g., Games and Economic Behavior ), program committee leadership (EC, FOCS), and academic governance (Dean of School of Computer Science, 2018-2021). Co-founded the Algorithmic Game Theory Blog (Turing’s Invisible Hand). Labs/Teams: Active in Starkware’s research on zero-knowledge proofs and blockchain scalability, and collaborates with the Center for Rationality on behavioral algorithmic mechanisms.

Yonatan Loewensteinمشاهده پروفایل

استاد

• Decision-making
• Reinforcement Learning
• Neurobiology
• +۳ مورد دیگر

Prof. Yonatan Loewenstein is a Professor in the Department of Neurobiology at the Hebrew University of Jerusalem. His research focuses on computational neuroscience and cognition, particularly the neural mechanisms underlying decision-making, reinforcement learning, and sensory processing. He leads an interdisciplinary laboratory exploring how learning principles govern behaviors in both biological and artificial systems. Key contributions include studies on somatosensory cortex organization, neuronal homeostasis, and human-machine synergy in decision-making. He co-authored the book Computational Models in Cognition , blending theoretical frameworks with empirical findings. Education details are not explicitly provided in the text, but his affiliations suggest advanced training in neurobiology and computational sciences. Research interests span decision-making biases, reinforcement learning dynamics, and the interplay between brain structure and function. His recent work addresses topics like idiosyncratic choice stability, value modulation in impulsivity, and abstract reasoning in neural networks. Publications highlight collaborations in fields ranging from cognitive dissonance to schizophrenia diagnostics. While no specific awards are listed, his involvement in high-impact journals and interdisciplinary projects underscores his academic contributions. The lab’s work is housed in the Goodman Faculty building, with active group members and experimental facilities.