Zvi Lotker is a Lecturer in the Department of Communication Systems Engineering at Ben-Gurion University. His research focuses on computer networks, distributed systems, and mobile/wireless computing. Education: Ph.D. in Electrical Engineering (2003), Tel-Aviv University, Israel. Dissertation: Algorithms in Networks under Prof. Boaz Patt-Shamir. M.Sc. in Mathematics (1998), Tel Aviv University. Thesis: On the d distance between iid and Markov process under Prof. Meir Smordinsky. B.Sc. in Mathematics & Computer Science (1991), Ben-Gurion University. B.Sc. in Industrial Engineering (Information Systems track, 1991), Ben-Gurion University. No scientific awards, grants, or advised students are listed in the provided information.
Dr. Miri Adler is a Senior Lecturer (Assistant Professor) at the Alexander Silberman Institute of Life Sciences and the Faculty of Medicine at the Hebrew University of Jerusalem, and a visiting scientist at Yale University's Tananbaum Center. Her research focuses on uncovering universal principles of tissue organization and function, particularly in health and disease, with an emphasis on fibrosis, cell-cell communication circuits, and systems-level analysis of complex biological networks. She leads a multidisciplinary team combining theoretical models, computational methods, and experimental data to study tissue repair, homeostasis, and pathological processes like fibrosis. Education: Ph.D. in Physics (Weizmann Institute, 2019), M.Sc. in Physics (Weizmann Institute, 2013), B.Sc. in Physics (Technion, 2010). Previous positions include postdoctoral fellowships at the Broad Institute (MIT/Harvard) and Weizmann Institute, and a visiting scientist role at Yale. Research interests span network hyper-motifs, division of labor in tissues, fibrosis mechanisms, and fold-change detection in biological systems. Key contributions include identifying fibrosis subtypes (‘cold’ and ‘hot’) and developing theoretical frameworks to predict therapeutic targets. Her work integrates concepts from mathematics, computer science, and physics with biology. Scientific awards include the Alon Fellowship (2024), EMBO Excellence in Life Sciences Fellowship (2020), and the Lee A. Segel Prize in Theoretical Biology (2017). The lab actively seeks students and researchers in computational biology, systems biology, and mathematical modeling. Advising: Supervises graduate and undergraduate students in projects related to tissue dynamics, network analysis, and fibrosis modeling. Collaborates with experimental labs to validate theoretical predictions in heart, lung, and liver tissues. Current team includes postdocs, M.Sc. students, and undergraduate researchers. Labs & Teams: The Adler Lab at Hebrew University focuses on multidisciplinary approaches to tissue biology, with a particular emphasis on fibrosis and systems-level tissue organization. Collaborations span institutions including Yale University and the Broad Institute.
Dr. Gili Greenbaum is an Assistant Professor at The Hebrew University of Jerusalem's Department of Ecology, Evolution and Behavior. His research focuses on computational population genomics, addressing eco-evolutionary processes through genomic data analysis and mathematical modeling. Key areas include conservation genomics, gene drive technology, and human evolution under disease pressures. He leads a lab with interdisciplinary collaborations, advising students across biology, mathematics, and computer science disciplines. Research emphasizes genomic approaches for endangered species conservation, particularly fragmentation impacts on population genetics. Projects also explore gene drive deployment risks and ecological modeling of ancient human interactions with Neanderthals. His lab develops tools like DORA for ancient DNA visualization and modelRxiv for model sharing. Current projects include predicting conservation risks using machine learning, studying immune-related genomic signatures in human populations, and modeling social evolution dynamics. The lab collaborates with institutions globally and offers training opportunities for graduate students and postdocs in computational biology and theoretical ecology.
Prof. Alon Zaslaver is a Professor in the Department of Genetics at the Hebrew University of Jerusalem's Institute of Life Sciences. He leads the Zaslab, an interdisciplinary Systems Biology lab combining molecular genetics, computational modeling, and neurobiology. His work focuses on understanding neural circuits and gene networks in C. elegans, particularly in learning/memory mechanisms and sensory processing. Research Interests: Computation in neural circuits with single-neuron resolution Plasticity in neural networks (aging, neurodegeneration) Epigenetic memory transmission across generations Evolutionary genomics of transcription networks Neuro-developmental disorders modeling Gut-brain axis signaling Awards & Grants: ERC Starting Grant 2013: 'Design Principles in Encoding Complex Noisy Environments' Farkas-Himsley 2016 Award for Young Researchers Lab Team: PhD students: Eddie Bokman (computational biology), Yuval Balshayi (physics-based modeling) MSc students: Neta Barlam (neurodevelopmental disorders), Omri Babay (memory mechanisms) Alumni: Dr. Rotem Ruach (data scientist at Prospera Technologies)
Michael London is an Associate Professor at The Hebrew University of Jerusalem's Edmond and Lily Safra Center for Brain Sciences. His research focuses on the interface between biophysical properties of neurons and information encoding, particularly nonlinear dendritic processes and neuronal noise effects. Key projects involve studying sensory systems (mouse barrel cortex) and self-generated activity (ultrasonic vocalization circuits). Techniques include patch-clamp, two-photon imaging, optogenetics, and computational modeling. Notable collaborations include work on cortical interneurons with Idan Segev and studies of adrenergic modulation with Inbal Goshen. His lab has published extensively on topics like neural coding dynamics, circuit function, and neuron-network interactions. He advises a team of ~9 PhD students and postdocs, focusing on experimental/theoretical integration. Laboratory location: Goodman Brain Sciences Building, Level 1, Room 2103. Active in neuroscience education through ELSC's PhD program and summer internships. Maintains an open-source lab website at www.mikilon.org with research tools and datasets.
Michael Elad is a Professor of Computer Science at the Technion - Israel Institute of Technology, where he has held a permanent faculty position since 2003. He also holds a courtesy appointment in the Technion's Electrical & Computer Engineering Department. Elad received his B.Sc. (1986), M.Sc. (1988) and D.Sc. (1997) in Electrical Engineering from the Technion, followed by a research associate position at Stanford University (2001-2003). His educational background includes: B.Sc. in Electrical Engineering from the Technion (1986) M.Sc. in Electrical Engineering from the Technion (1988), focusing on video compression algorithms under Prof. David Malah D.Sc. in Electrical Engineering from the Technion (1997), focusing on super-resolution algorithms for image sequences under Prof. Arie Feuer Michael Elad's research spans signal and image processing and machine learning, with specialization in inverse problems, sparse representations, deep learning, and generative models. He is particularly renowned for his work on sparse representations, having created the influential K-SVD algorithm together with Michal Aharon and Bruckstein. His 2010 book "Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing" is a leading publication in this field. Elad has also made significant contributions to diffusion models and generative AI, applying these concepts to solve complex problems in signal and image processing. His extensive publication record shows a clear evolution from foundational work on sparse representations to more recent applications in deep learning and generative models. While his early work focused on theoretical aspects of sparse coding and dictionary learning, his more recent publications demonstrate an integration of these concepts with modern deep learning techniques, particularly in the areas of image restoration, super-resolution, and generative modeling. Elad's scientific achievements have been recognized with numerous awards: Rothschild Prize in Engineering (2024) Member of the Israel Academy of Sciences and Humanities (2024) Weizmann Award for contributions in Sparse Modeling (2021) IEEE SPS Sustained Impact Paper Award (2018) IEEE SPS Best Paper Award (2018) IEEE SPS Technical Achievement Award (2018) Fellow of the Society for Industrial and Applied Mathematics (SIAM Fellow) (2018) IEEE Fellow (2012) ERC advanced grant (2013) Throughout his career, Elad has been actively involved in academic service and mentorship. He has served as an Associate Editor for several prestigious journals including IEEE Transactions on Image Processing, IEEE Transactions on Information Theory, and Applied Computational Harmonic Analysis. From 2016 to 2021, he was the Editor-in-Chief for SIAM Imaging Sciences. He has advised numerous students, including Michal Aharon and Yaniv Romano. Elad also headed the Rothschild-Technion Program for Excellence from 2015 to 2018, an undergraduate program for exceptional students. Elad maintains an active research laboratory at the Technion focused on advancing the theory and applications of sparse representations, deep learning, and generative models in signal and image processing. His team continues to push the boundaries of what's possible in image restoration, super-resolution, and other inverse problems in imaging.
Prof. Alex Bronstein is a Professor at the Henry and Marilyn Taub Department of Computer Science, Technion – Israel Institute of Technology, where he holds the Dan Broida Academic Chair and heads the VISTA Lab and the Center for Intelligent Systems. He concurrently serves as a Visiting Professor at the Austrian Institute of Science and Technology. His research spans computer vision, machine learning, computational geometry, signal processing, and bioinformatics, with a focus on geometric data analysis and AI applications in science. He has held significant industry roles including Principal Engineer at Intel Corporation, co-founding startups such as Invision (acquired by Intel), VideoCites, and Sibylla. His work bridges academia and industry, emphasizing practical applications of theoretical insights. Research interests include foundational AI models for molecular biology, robust machine learning systems, and interdisciplinary applications in healthcare and robotics. Notable projects include protein structure prediction using AlphaFold integration, adversarial robustness frameworks, and medical imaging innovations like T1-PILOT for MRI acceleration. He actively collaborates with global institutions, maintaining labs in Haifa, Vienna, and Sardinia. Recent publications highlight advancements in quantum computing simulations, wearable health monitoring systems, and AI-driven biomedical solutions. While no explicit awards are listed, his leadership roles and industry impact underscore significant contributions to computational science. He mentors graduate students in his VISTA Lab, focusing on cutting-edge projects in AI, computer vision, and computational chemistry.
Dr. Tamar Berenblum serves as Research Director of the Federmann Cyber Security Research Center – Cyber Law Program at the Hebrew University of Jerusalem's Faculty of Law. She concurrently holds Post-Doctoral Research Fellow positions at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), the Rachel and Selim Benin School of Computer Science and Engineering (Hebrew University), and the Center for Cyber Law & Policy at Haifa University (CCLP). Her research expertise spans victimology , sociology of knowledge , cybercrime , online social control , and digital rights , rooted in her doctoral thesis The Internet as a Sphere of Social Control which examines cyberspace as both a domain and tool for social control over deviant activities. Current projects investigate deterrence mechanisms, online-shaming phenomena, language accessibility in legal proceedings, and juvenile cyber-delinquency. Analysis of her publications reveals consistent focus on human-centered cybersecurity challenges, with recurring themes in ransomware mitigation ( Security Vaccination ), hacking network topology ( Hackers Topology Matter Geography ), and digital justice dynamics ( Viral Justice and E-shaming ). Her methodological approach blends criminological theory with computational analysis of real-world cyber incidents. Beyond research, Berenblum serves as a public representative in Parole Committees of the Court Administration and contributes to policy discussions through the Cyber Law Program's regulatory work on computer crime prevention and IoT security standards.
Keren Censor-Hillel is a Professor in the Department of Computer Science at the Technion, Israel Institute of Technology. Her research focuses on distributed computing and theoretical computer science, with a particular emphasis on simplifying parallel programming and optimizing network bandwidth through algorithmic innovation. Her work has been supported by prestigious grants including the ISF (2014, 2023), NSF-BSF (2016), ERC Starting Grant (2017), and Henry Taub Research Grant (2018). She actively mentors graduate students and postdoctoral researchers, seeking candidates with strong algorithmic and mathematical foundations. Research Highlights: Contributions to lock-free algorithms, maximal independent set problems, and vertex connectivity analysis. Media Recognition: Featured in Communications of the ACM, MIT News, and other outlets for her work on distributed systems. Keren serves as a key organizer for academic events like the Technion Distributed Computing Seminar (TDC) and supports initiatives such as Women in Theory (WIT).
Oren Tsur is an Assistant Professor in the Department of Software & Information Systems Engineering (SISE) at Ben Gurion University of the Negev, where he heads the NLP and Social Dynamics Lab (NAS-LAB) and directs the Center for the Study of Digital Politics and Strategy (DPS@BGU). He joined the university in September 2017 and teaches core courses including Natural Language Processing, Social Network Analysis, and Introduction to NLP at both undergraduate and graduate levels. His research focuses on computational modeling of social dynamics through language and network analysis. Key interests include social contagion, language evolution, political network analysis, and sentiment analysis. He employs methodologies from exponential random graph models (ERGM), machine learning, and natural language processing to study how language shapes and is shaped by social interactions, particularly in political contexts and online communities. His publication trends reveal strong interdisciplinary work spanning computational linguistics, political science, and social network analysis. Recent research emphasizes hate speech detection in platforms like Parler, suicide risk identification in counseling services, and modeling semantic drift in emoji usage. His work consistently bridges technical NLP innovations with real-world social applications, particularly in political discourse and community dynamics. NSF Political Network Fellowship (2014, 2015, 2016) TIME Magazine's 50 Best Inventions of 2010 for sarcasm detection research Work featured in Science Magazine, BBC, The Atlantic, CNET, and Politico Best Paper award at HICSS 2020 Tsur actively mentors prospective students through his lab, emphasizing excellence in candidates through academic transcripts and research interest statements. His grants include multiple NSF Political Network Fellowships supporting computational social science research. He serves as Director of BGU's Cyber Politics and Policy Research Center and organizes major NLP workshops including the Natural Language Processing and Computational Social Science series at top conferences. His NAS-LAB focuses on data-driven modeling of social coordination and influence, with applications in sentiment analysis, dialogue systems, and digital forensics. The lab maintains strong industry connections through past collaborations with IBM Research (Watson Debater project), Yahoo! Research, and startup consulting.
Nir Friedman is a Professor at The Hebrew University of Jerusalem with dual appointments at The Rachel and Selim Benin School of Computer Science and Engineering and The Alexander Silberman Institute of Life Sciences. His research spans three interconnected fields: Molecular Biology of Chromatin and Transcriptional Regulation: Understanding cellular transcription regulation, chromatin-transcription interactions, and gene expression mechanisms Computational Systems Biology: Applying probabilistic models to analyze high-throughput biological data and understand complex biological systems Inference and Learning in Probabilistic Models: Developing methods for representation, inference, and learning with Bayesian networks and Markov networks Professor Friedman's lab has created significant bioinformatics resources including SEMPHY for phylogenetic reconstruction, ScoreGenes for gene expression analysis, GeneXPress for visualization, and LibB for Bayesian network learning. His interdisciplinary work bridges computer science and molecular biology, with offices in both the Rothberg Building (Computer Science) and Silberman Building (Life Sciences). He has supervised over 20 graduate students since 2001, mentoring researchers who have gone on to contribute significantly to computational biology. His lab maintains an active blog and continues to develop tools that advance research in systems biology and probabilistic modeling.
Dr. Itay Safran is a faculty member in the Department of Computer Science at Ben-Gurion University of the Negev, Faculty of Natural Sciences. He completed his BSc in computer science and mathematics at Ben-Gurion University, followed by MSc and PhD studies at the Weizmann Institute, and postdoctoral research at Princeton and Purdue Universities in the US. His academic journey reflects a strong foundation in theoretical and applied computer science. Research interests focus on artificial intelligence and deep learning, particularly on developing theoretical foundations to understand the mechanisms behind deep learning technologies and their potential improvements. He aims to establish a laboratory at Ben-Gurion University to advance this research. His academic career emphasizes inspiring students to achieve high professional and human standards while fostering flexibility in research environments. Personal interests include travel, influenced by his postdoctoral experiences in the US, and he expresses a desire to continue exploring Israel.
Associate Professor Tamir Hazan is a faculty member at Technion - Israel Institute of Technology, where he joined in 2015. His research focuses on theoretical and practical aspects of machine learning, with applications spanning computer vision, natural language processing, and computational biology. His work bridges mathematical foundations with real-world problem solving in complex systems. Professor Hazan received his Ph.D. from the Hebrew University in 2009. His academic trajectory has established him as a leading researcher in machine learning theory and its applications, with a particular emphasis on developing mathematically rigorous approaches to modern AI challenges. Professor Hazan's research centers on mathematically founded solutions to problems demonstrating non-traditional statistical behavior. His work encompasses perturbation models for efficient learning of high-dimensional statistics, deep learning of infinite networks, and primal-dual optimization for high-dimensional inference problems. His research program spans three major interconnected areas: attention models that improve prediction interpretability, perturbation frameworks that integrate optimization and sampling through extreme value statistics, and convex duality approaches to message-passing in graphical models. His work demonstrates both theoretical depth and practical relevance across multiple domains. Analysis of Professor Hazan's recent publications reveals an evolving research trajectory with increasing emphasis on interpretable machine learning, causal modeling, and applications in medical imaging and behavioral science. His work consistently bridges theoretical foundations with practical implementations, with recent publications showing strong connections between perturbation theory, attention mechanisms, and optimization frameworks. The interdisciplinary nature of his research is evident in applications ranging from pedestrian navigation using smartphone sensors to video-text matching systems and medical image analysis. Professor Hazan has mentored numerous students throughout his career, including: Alex Schwing, now Assistant Professor at UIUC Alon Cohen, now Associate Professor at Tel Aviv University Idan Schwartz, currently Postdoc at Tel Aviv University Current Ph.D. students: Guy Lorberbom, Itai Gat, and Hedda Cohen Multiple M.Sc. students including Adi Manos, Ram Yazdi, and others Professor Hazan's research group maintains an active program with several key focus areas: Attention models for interpretable and improved prediction processes in visual question answering and multimodal applications Perturbation models that enable efficient statistical reasoning in complex systems with exponential configuration spaces Markov random fields, convex duality, and message-passing algorithms for structured prediction and distributed computing
Yoav Goldberg is a Professor in the Department of Computer Science at Bar Ilan University and serves as the Research Director of the Israeli branch of the Allen Institute for Artificial Intelligence. Previously, he was a Research Scientist at Google Research New York. He completed his PhD at Ben-Gurion University in 2011 under the supervision of Prof. Michael Elhadad. His research focuses on Natural Language Processing and Machine Learning, with specific expertise in: Syntactic parsing and structural analysis Development of structured-prediction models Algorithms for greedy decoding optimization Cross-lingual and multilingual understanding Domain adaptation techniques Neural network architectures for NLP tasks He has authored a book on neural network methods for NLP and maintains active contributions through publications, open-source software, and curated datasets.
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.
