Prof. Yair Weiss is a faculty member at the School of Computer Science and Engineering, The Hebrew University of Jerusalem . He holds a PhD in Brain and Cognitive Sciences from MIT and an MSC in Applied Mathematics from Tel-Aviv University. Education: MSc in Applied Mathematics, Tel-Aviv University (1993) PhD in Brain and Cognitive Sciences, MIT (1998) His research focuses on Human and Machine Vision , Machine Learning , Bayesian Methods , and Neural Computation . Recent work explores adversarial examples, generative models, and robustness in neural networks. Recent publications highlight trends in: Understanding neural network representations Advancements in GANs and adversarial training Image restoration and translation techniques Perceptual distance modeling Bayesian approaches to computer vision Mathematical analysis of deep learning architectures
Aryeh Kontorovich is a Professor in the Computer Science Department at Ben-Gurion University. His research primarily focuses on theoretical machine learning, with expertise in probability, statistics, Markov chains, and metric spaces. His research interests span theoretical machine learning, with particular emphasis on: Probability theory and concentration inequalities Statistical learning theory Markov chains and mixing time estimation Metric space learning Kernel methods Sample compression schemes Professor Kontorovich's recent publications (2021-2025) demonstrate a continued focus on theoretical foundations of machine learning. His work shows strong trends in statistical estimation for Markov processes, distribution learning, metric space analysis, and sample compression. Many papers explore the intersection of probability theory and machine learning, particularly examining concentration inequalities, minimax optimality, and theoretical guarantees for learning algorithms. His research consistently bridges abstract mathematical theory with practical machine learning applications. Scientific awards and recognitions: Distinguished contribution award at MLG 2007 for "A Universal Kernel for Learning Regular Languages" Professor Kontorovich has advised numerous students and collaborated extensively with researchers in theoretical machine learning. His work spans both theoretical foundations and practical applications, with significant contributions to understanding the mathematical limits of learning algorithms. While specific grant information isn't provided in the source material, his extensive publication record in top venues suggests successful funding for his research programs. He maintains active collaborations with researchers worldwide, including prominent names like L. Gottlieb, D. Berend, and S. Hanneke.
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
Prof. Danny Dolev is a distinguished academic holding the Berthold Badler Chair in Computer Science at The Hebrew University of Jerusalem's Rachel and Selim Benin School of Computer Science and Engineering. He is an ACM Fellow and IEEE Fellow. His research focuses on distributed computing, fault-tolerant systems, algorithms, and secure protocols. He has held leadership roles, including Director of his school (1999–2002) and Chair of the Israeli National Committee for Information Technology (1994–1998). Education: B.Sc., The Hebrew University of Jerusalem, 1971 M.Sc., Weizmann Institute of Science, 1973 PhD., Weizmann Institute of Science, 1979 Research Interests: Danny Dolev's work spans distributed algorithms, Byzantine fault tolerance, consensus protocols, and hardware algorithms. His contributions include groundbreaking research on self-stabilizing systems, secure communication, and fault-tolerant clock synchronization. His HEX and Chronos protocols exemplify innovations in scalable synchronization and network security. Publications: His recent work emphasizes Byzantine agreement, asynchronous fault tolerance, and game-theoretic distributed systems. Key papers address optimal resilience in consensus algorithms and secure multi-party computation. Awards: ACM Fellow (2010) IEEE Fellow (2004) Grants & Leadership: Member of the Scientific Council, European Research Council (2010–2014) Chair of Israel's National Committee for Information Technology (1994–1998) Leadership roles at IBM Almaden Research Center (1987–1993) and Stanford University (1979–1981) Labs & Teams: His research group at Hebrew University focuses on distributed systems, with collaborations on projects like Steward (wide-area Byzantine replication) and Self-Stabilizing Circuits .
Prof. Ariel Porat is the Alain Poher Professor of Law and current President of Tel Aviv University (2019-present). He holds the Alain Poher Chair in Private Law at the Buchmann Faculty of Law and has served as Dean (2002-2006) and Director of the Cegla Center for Interdisciplinary Research of the Law (1997-2002). He is a member of the Israel Academy of Sciences and Humanities and the American Law Institute, with visiting professorships at the University of Chicago (2003-2019), Stanford, Columbia, NYU, Berkeley, Virginia, and Toronto. LL.B. (magna cum laude), Tel Aviv University (1983) J.S.D., Tel Aviv University (1989) Post-Doctoral Studies, Yale Law School (1990) His research focuses on torts , contract law , and remedies , with recent contributions to personalized law and legal robotics . His work explores the intersection of law and economics , particularly in harm-benefit interactions , disgorgement damages , and private law restoration . His 15 most recent publications (2020-2012) examine topics spanning contractual disclosures , discriminatory government liability , free speech , and empirical legal studies . Themes include economic analysis , legal precision , and data-driven law . EMET Prize (2014) European Law and Economics Association Lifetime Award (2020) Zeltner Prize for Academic Excellence (2012) Chesin Prize (2010) Zusman Prize for Junior Faculty (1991) Prof. Porat has collaborated extensively with scholars like Omri Ben-Shahar, Robert Cooter, and Alex Stein. He founded the journal Theoretical Inquiries in Law and co-authored influential books on personalized legal systems and incentive design .
Idit Keidar is currently the Dean of the Viterbi Faculty of Electrical and Computer Engineering at the Technion - Israel Institute of Technology, where she also holds the Lord Leonard Wolfson Academic Chair. She received her BSc, MSc, and PhD (all summa cum laude) from the Hebrew University of Jerusalem in 1992, 1994, and 1998 respectively, with Danny Dolev as her PhD advisor. She completed her postdoctoral studies at MIT with Nancy Lynch. Her academic lineage includes notable figures such as Copernicus, Leibniz, Jacob Bernoulli, Euler, Lagrange, Laplace, and Poisson. Keidar's research focuses on fault-tolerant distributed and concurrent algorithms and systems, with particular interest in distributed storage theory and systems, concurrent data structures and transactions, and scalable Byzantine fault-tolerance. She approaches her work with the goal of finding theoretical foundations that can help explain and improve practical implementations. Her research has significant implications for large-scale distributed systems, cloud computing, and multi-core architectures. Keidar has made substantial contributions to the field through her editorial work as editor of the ACM SIGACT News Distributed Computing Column from 2007-2013 (previously co-editing with Sergio Rajsbaum from 2000-2007). Her publications span theoretical foundations, practical applications, and educational aspects of distributed computing. The trends in her work show a consistent focus on bridging theory and practice in distributed systems, with increasing attention to large-scale systems, transactional memory, and Byzantine fault tolerance as these areas have gained practical importance. Scientific Awards and Recognition: Lord Leonard Wolfson Academic Chair Editor of ACM SIGACT News Distributed Computing Column (2000-2013) Keidar has held significant leadership positions in the distributed computing community, serving as PC Chair for PPoPP 2019 and PODC 2018, Organizing Committee Chair for DISC 2013 in Jerusalem, and PC Co-Chair for LADIS 2021. She has been actively involved with the Networked Software Systems Laboratory at the Technion. Beyond her technical work, Keidar is also a creative writer, with a short story winning 2nd place in the Shirat Ha'Mada creative writing contest for scientists.
Prof. Liran Carmel is a Professor of Genetics at the Hebrew University of Jerusalem's Alexander Silberman Institute of Life Sciences (Faculty of Science). His lab focuses on ancient DNA analysis to study human evolution, paleo-epigenetics, and molecular evolution. Recent work includes reconstructing Denisovan anatomy through epigenetic maps and analyzing Bronze Age population dynamics in the Southern Levant. Research Interests: Decoding genetic and epigenetic changes driving human evolution Reconstructing ancient DNA methylation patterns Studying RNA biology mechanisms like splicing and nonsense-mediated decay Developing computational tools for paleogenomics (e.g., RoAM, Gene ORGANizer) Key Achievements: Identified Denisovan morphological traits through epigenomic analysis Discovered Neolithic-era metabolic adaptations via ancient methylation studies Received the 2021 Massry Prize and 2020 Science Breakthrough award Lab Activities: Current members: 4 PhD students, 1 MSc student, lab managers, and programmers Alumni include 19 researchers now in academia and industry roles worldwide Hosts annual retreats and collaborates internationally on projects like the Punic genome study
Eran Treister is an Assistant Professor at the Ben Gurion University of the Negev in the Department of Computer Science. He completed his postdoctoral fellowship at the University of British Columbia (2014-2016) and earned his PhD from the Technion in 2014 under Prof. Irad Yavneh. His research spans computational science, numerical methods, and machine learning, with a focus on: Scalable algorithms for inverse problems Graph Neural Networks (GNNs) optimization Seismic and optical imaging via PDE solvers Low-precision deep learning acceleration Multilevel preconditioning techniques Recent work explores: Graph neural networks for PDEs with adaptive meshes Deep learning approaches to Helmholtz equation modeling 3D shape reconstruction via parametric level sets He serves on editorial boards: SIAM Journal on Scientific Computing (2024-) Copper Mountain Conference on Multigrid Methods (2025) International Conference on Machine Learning (ICML) as Area Chair (2025) Current teaching: Optimization Methods for Data Science (Spring 2025) Deep Learning Mini-Project (Winter 2024/5) Advanced Numerical Optimization (Spring 2025)
Hila Peleg is an Assistant Professor in the Department of Computer Science at the Technion – Israel Institute of Technology, where she co-leads the TecSE lab with Prof. Shachar Itzhaky. Her research lies at the intersection of Programming Languages, Software Engineering, and Human-Computer Interaction, focusing on program synthesis and interactive developer tools. Her research interests center on creating intelligent, theory-driven tools that enhance programmer productivity and correctness. She explores interaction models that integrate formal methods like separation logic into practical synthesis systems, enabling more versatile and reliable code generation. Her work spans both foundational models and real-world applications, from web layout synthesis to computational crafting. The trend in her recent publications shows a strong focus on interactive and practical program synthesis, blending formal verification with user-centered design. She investigates how synthesis can be made more usable through live programming, best-effort results, co-design of tools and languages, and integration with developer workflows. Her work increasingly emphasizes the human aspect of programming tools. Distinguished Paper Award, PLDI 2021 Distinguished Artifact Award, SPLASH 2020 Hila Peleg advises multiple graduate students, including PhD and MSc candidates, and leads the ERC-funded EXPLOSYN project, which supports advanced research in program synthesis. She has taught advanced courses such as User-Centered Programming Tools and seminars in programming languages, and is actively involved in the academic community through conference service and organization. She is a core member of the TecSE lab, which focuses on advancing software engineering through programming language theory and interactive systems. The lab fosters interdisciplinary research at the boundary of formal methods and human-centered tool design.
Oren Weimann is a Professor in the Department of Computer Science at the University of Haifa, Faculty of Natural Sciences. His research lies at the intersection of theoretical computer science, algorithm design, and data structures, with a strong focus on planar graphs, combinatorial pattern matching, and fine-grained complexity. He has published extensively in top-tier venues such as STOC, SODA, ICALP, PODC, and ESA. Education: Ph.D., Massachusetts Institute of Technology (MIT), 2005–2009. Advisor: Erik Demaine. Dissertation: "Accelerating Dynamic Programming" Postdoc, Weizmann Institute of Science, 2009–2011. Host: David Peleg M.Sc., University of Haifa, 2004–2005. Advisor: Gad Landau. Dissertation: "Using PQ trees for Comparative Genomics" B.A., Technion – Israel Institute of Technology, 1999–2002 Oren Weimann's research centers on the design and analysis of efficient algorithms, particularly for planar and structured graphs. His work explores fundamental problems such as shortest paths, distance oracles, fault tolerance, edit distance, and pattern matching. He investigates both upper and lower bounds, often pushing the limits of what is computationally feasible under fine-grained complexity assumptions. His contributions include optimal labeling schemes, compressed data structures, and breakthroughs in dynamic and distributed graph algorithms. His recent publications reveal a consistent trend in developing highly efficient algorithms for planar graphs, with a focus on distance computation, fault tolerance, and compression. Keywords across these works include planar graphs, dynamic programming, string matching, and conditional lower bounds, reflecting a deep integration of algorithmic techniques and complexity theory. He frequently collaborates with leading researchers such as Shay Mozes, Paweł Gawrychowski, and Philip Bille. Scientific Awards: Best Paper Award, CPM 2007 Best Paper Award, ICALP 2020 (mentioned in context of work) Oren Weimann has advised numerous PhD and Master’s students, including Yaseen Abd-Elhaleem, Nathan Wallheimer, Aviv Bar-natan, and Shon Feller, whose dissertations have led to publications in major conferences. He has also mentored several postdoctoral researchers such as Shay Golan, Itai Boneh, and Panagiotis Charalampopoulos. His work has been supported by competitive research grants, though specific grant titles are not listed in the text. He has served on the program committees of key conferences including SODA, ICALP, CPM, ESA, and SPIRE, demonstrating active leadership in the theoretical computer science community. He is associated with a vibrant research group focused on algorithms and data structures, likely involving collaboration with students and postdocs on projects related to graph algorithms, string processing, and complexity. While no formal lab name is mentioned, his collaborative output suggests a strong, productive research team at the University of Haifa.
Michael Elkin is a Professor in the Department of Computer Science at Ben-Gurion University of the Negev, Israel. His research focuses on Theoretical Computer Science, Discrete Mathematics, and Algorithms, with specializations in graph algorithms, distributed computing, and metric embeddings. He has held editorial roles, including Associate Editor of the Journal of Computer and System Sciences, and has contributed to numerous program committees for top conferences like FOCS and SODA. Elkin's research interests include low-distortion embeddings, streaming and dynamic graph algorithms, and approximation algorithms. His work bridges distributed and centralized algorithm design, with applications in network optimization and computational geometry. Recent trends in his publications emphasize efficient spanner constructions, symmetry-breaking in distributed systems, and algorithmic approaches to graph coloring and metric spaces. Elkin has advised multiple PhD and Master’s students, including Leonid Barenboim (winner of the 2015 Distributed Computing Doctoral Dissertation Award) and Shay Solomon. He has been awarded Best Paper and Best Student Paper awards at PODC conferences for groundbreaking contributions to distributed algorithms. Additionally, he leads a postdoctoral research group focusing on graph algorithms and metric embeddings, collaborating with Eden Chlamtac and Ofer Neiman. Teaching highlights include courses on Distributed Algorithms, Design of Algorithms, and Metric Graph Algorithms. His academic service includes organizing academic programs and mentoring early-career researchers in theoretical computer science.
Dr. Nir Kalisman is a Senior Lecturer in the Department of Biological Chemistry at The Hebrew University of Jerusalem's Silberman Institute of Life Sciences. His research focuses on structural biology of large protein complexes using cross-linking mass spectrometry (XL-MS) and computational modeling. He leads the Kalisman Lab, which pioneers methods to study protein interactions in systems like the SARS-CoV-2 proteins and neuronal synapses. PhD in Computer Science (Ben-Gurion University, 2008) Postdoc in Michael Levitt's Lab at Stanford University (2008–2013) Research interests include XL-MS method development, integrative structural modeling, and low-resolution crystallography applications. Key projects involve: Deciphering architectures of SARS-CoV-2 proteins (Nsp1, Nsp2, Nucleocapsid) Protein complex studies in neurobiology and transcription Formaldehyde cross-linking chemistry analysis Publications span structural biology innovations and protein interaction studies. Lab members include graduate students and specialists in mass spectrometry. Software contributions include tools for cross-link interpretation and sequence inference from crystallographic data.
Dr. Michael Kalyuzhny is a Senior Lecturer and Principal Investigator at the Hebrew University of Jerusalem's Department of Ecology, Evolution and Behavior. His research focuses on understanding ecological community dynamics, species coexistence mechanisms, and the application of data science to ecological systems. He won the prestigious Alon Fellowship in 2024. Education: BSc in Biology, Hebrew University MSc and PhD in Ecology, Evolution & Behavior, Hebrew University Postdoctoral research at the University of Michigan and University of Texas at Austin Research Interests: Exploring how ecological communities maintain high biodiversity, spatial and temporal dynamics of species, and the integration of theoretical models with large-scale datasets. Current projects include studying conspecific negative density dependence in tropical forests and the impact of environmental heterogeneity on biodiversity. Awards: Alon Fellowship (2024) Advising & Grants: Supervising MSc student Yuval Neumann, investigating disturbance effects on plant community diversity. Active in securing grants for theoretical ecology and field experiments. Labs & Teams: Leads the Kalyuzhny Lab, which combines theoretical ecology with empirical studies to address fundamental questions in community assembly and biodiversity maintenance.
Shay Moran is an Associate Professor at the Faculty of Mathematics , Technion - Israel Institute of Technology, with affiliations to the Faculties of Computer Science and Data and Decision Sciences . They are also affiliated with Google Research in Tel Aviv . Shay's research interests center on mathematical problems inspired by learning theory and computer science , particularly in areas like machine learning theory, differential privacy, algorithmic stability, and online learning . Their work bridges abstract mathematics with practical algorithm design. Recent publications highlight trends in reductions between learning models, geometric interpretations of learning problems, and privacy-preserving algorithms . Key themes include sample compression, PAC learnability, boosting mechanisms, and adversarial robustness . Best Paper Runner-up , COLT 2021 Best Paper Award , COLT 2020 Final Award for Outstanding Paper in Machine Learning Shay has supervised numerous PhD and Master's students, including Vanessa Kosoy, Liza Nesterova, Hilla Schefler, Alexander Shlimovich, Tom Waknine , and Iska Tsubari . Former advisees include Idan Mehalel (PhD, co-advised with Yuval Filmus) and Zachary Chase (Postdoc) .
Dr. Eyal Tytler is a researcher in the Department of Industrial Engineering and Management at Ben-Gurion University of the Negev, affiliated with the Faculty of Engineering Sciences. His research focuses on integrating adaptive learning tools with classical algorithms to enhance decision-making in autonomous systems such as vehicles and robots. He completed his postdoctoral studies at the University of Toronto in artificial intelligence and decision-making, following a Ph.D. in autonomous systems and robotics at the Technion. His work emphasizes interdisciplinary collaboration to balance flexibility and safety in complex environments. Dr. Tytler’s research interests span artificial intelligence, robotics, and control systems, with a particular focus on combining modern learning techniques with traditional algorithmic frameworks. His academic journey reflects a dedication to advancing autonomous technologies through hybrid methodologies.
