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
Lihi Zelnik-Manor is a Professor at the Faculty of Electrical and Computer Engineering at the Technion - Israel Institute of Technology . Her research focuses on digitizing the sense of touch, integrating Haptics , Robotics , and Computer Vision to create digital representations of physical properties and develop haptic feedback devices for virtual interactions. Executive Vice President for Innovation and Industry Relations (2023-2026) Vice Dean for Graduate Studies (2022-2023) General Chair: CVPR’21, ECCV’22 Her work spans Neural Architecture Search (NAS) , 3D Reconstruction , and Image Processing , with recent publications on haptic devices (2025), diffusion models (2025), and soft-tissue simulation (2024). She actively contributes to academic leadership through roles in top conferences and community initiatives like the Schmidt Postdoctoral Award steering committee.
Omri Abend is an Associate Professor at The Hebrew University of Jerusalem, affiliated with the School of Computer Science and Engineering and serving as Chair of the Department of Cognitive and Brain Sciences. His research lies at the intersection of Computational Linguistics, Natural Language Processing, and Cognitive Science, with a focus on semantic representation and language acquisition modeling. His primary research interests include: Computational modeling of child language acquisition Semantic representation frameworks, particularly Universal Conceptual Cognitive Annotation (UCCA) Statistical learning and machine translation Unsupervised grammar learning and lexical relation induction Cross-lingual and cross-domain alignment in language models Evaluation methodologies for NLP systems His recent publications demonstrate a strong trend toward analyzing large language models (LLMs), exploring human-like patterns in AI, improving evaluation metrics, and applying NLP to humanitarian domains such as Holocaust testimony analysis. His work combines theoretical linguistic insights with practical machine learning applications. Scientific awards include: Outstanding Paper Award at ACL 2017 Area Chair Award for Best Paper in the Track at ACL 2023 He has supervised and collaborated with numerous researchers and students across projects in semantic parsing, machine translation, and cognitive modeling. His work has been supported by community-wide initiatives such as the MRP shared tasks, which he co-organized. He also leads research on ethical AI, open human feedback, and the computational analysis of historical narratives. Omri Abend leads several research teams focused on: The development and application of the UCCA framework for semantic annotation Cross-lingual and cross-domain knowledge representation in LLMs Computational modeling of language acquisition Evaluation and improvement of NLP systems Application of NLP to digital humanities and historical testimony analysis
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)
Tomer Michaeli is an Associate Professor at the Faculty of Electrical and Computer Engineering, Technion – Israel Institute of Technology. His research focuses on interdisciplinary areas bridging computer vision, machine learning, and signal processing methodologies. Research Interests Computer Vision Machine Learning Image Processing Signal Processing
Prof. Adi Mizrahi is a Professor at the Hebrew University of Jerusalem's Edmond and Lily Safra Center for Brain Sciences (ELSC), leading the NeuroPlasticity Lab. His research focuses on neuronal plasticity in auditory and olfactory systems, parental neuroscience, and adult neurogenesis. He holds the Eric Roland Chair in Brain Sciences. Research Interests: Neuronal & Circuit Plasticity in Sensory Systems Auditory Learning & Perceptual Boundaries Social and Parental Behavior Neural Mechanisms Adult Neurogenesis Functional Role Olfactory Bulb Circuit Dynamics Key Findings: Discovered maternal behavior-driven plasticity in auditory cortex representations of pup vocalizations Elucidated odor categorization mechanisms in the olfactory bulb Showed learning-induced cortical map expansions in auditory cortex Awards & Honors: ERC Starting Grant (2007) Sir Zelman Cowen Universities Fund Prize (2009) Labs & Teams: Directs the NeuroPlasticity Lab, collaborating with multiple postdocs and students investigating auditory, olfactory, and parental neurobiology. Lab develops automated behavioral systems and advanced imaging techniques.
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)
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.
Prof. Yonatan Sivan is a Professor at the School of Electrical & Computer Engineering, Ben-Gurion University. His research focuses on nanophotonics, plasmonics, and electromagnetism, with particular emphasis on thermal and non-thermal effects in metallic systems. Key areas include plasmon-assisted photocatalysis, electron non-equilibrium dynamics, and numerical methods for nanophotonic systems. He advises multiple PhD and MSc students, including current candidates like Tamir Grossinger and Ben Spiegel, and collaborates internationally (e.g., with South China Normal University and UC Berkeley). Education details are not explicitly stated, but his work spans theoretical and experimental domains, integrating advanced numerical techniques with experimental validation. Notable contributions include redefining plasmonic photocatalytic mechanisms through thermal/non-thermal analysis and pioneering modal expansion methods for open optical systems. Research interests are organized into thematic clusters: Thermo-plasmonics, Drude materials, metal luminescence, thermal emission, and numerical methods. His work often involves interdisciplinary collaborations, addressing both fundamental physics and applied nanotechnology challenges. Publications span high-impact journals like ACS Catalysis , Nano Letters , and Physical Review Applied , with a focus on experimental validation and theoretical modeling. He also contributes to teaching courses on plasmonics, metamaterials, and wave propagation. Current group members include Dr. Imon Kalyan and Sravya Rao, while past members hold positions at institutions like UC Berkeley and KLA Tencor. His lab focuses on advancing nanophotonic technologies through rigorous computational and experimental frameworks.
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.
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
Dr. Michal Breker-Dekel is an Assistant Professor and Head of the Breker Lab at the Hebrew University of Jerusalem's Department of Plant & Environmental Sciences. Her research focuses on systems genetics of green microalgae, particularly Chlamydomonas reinhardtii , to understand chloroplast biogenesis and protein quality control under stress conditions. She develops innovative genetic and imaging tools to study these processes, with translational applications in agritech and foodtech to engineer climate-resilient crops and protein production platforms. Key achievements include securing an ERC Starting Grant (2023) for mapping chloroplast protein import systems. Her lab emphasizes interdisciplinary approaches, combining fundamental cell biology with industry collaboration. Current lab members include PhD candidate Elad Meilin (co-PI: Silvia Ramundo) and M.Sc. student Shai Gelbart, alongside B.Sc. researchers exploring diverse projects like septin protein roles and microbiota interactions. Dr. Breker-Dekel's career spans postdoctoral research at the Rockefeller University (Simons Foundation Award) and academic training at the Weizmann Institute of Science. She actively mentors students and fosters collaborations across academia and industry to advance sustainable agricultural solutions.
Prof. Ami Citri is a prominent neuroscientist at the Hebrew University of Jerusalem's Edmond and Lily Safra Center for Brain Sciences. He holds a faculty position as Professor and leads the Citri Lab for Experience-Dependent Plasticity. His work focuses on understanding how the brain encodes experiences, particularly in regions like the claustrum, and explores neural mechanisms underlying addiction, attention, and synaptic plasticity. His research integrates molecular, synaptic, and behavioral approaches to unravel how salient experiences shape brain circuits and behavior. Education and Positions: PhD in Biological Regulation (Weizmann Institute of Science, 2006) Postdoctoral Research (Stanford University, 2012) Current PI at Hebrew University of Jerusalem since 2012 Research Interests: His work bridges molecular mechanisms (e.g., transcriptional networks, non-coding RNA) with systems-level processes like attention, addiction, and learning. Key areas include: Role of the claustrum in attention and sensory processing Neural circuits driving drug addiction and compulsive behaviors Experience-dependent plasticity and memory formation Awards and Recognition: ERC Consolidator Award (2018) CIFAR Azrieli Global Scholar (2016) ADELIS Prize in Neuroscience (2015) Grants and Collaborations: His lab has secured funding from major institutions including the European Research Council and Canadian Institute for Advanced Research. Collaborations span molecular neurobiology, behavioral neuroscience, and systems neuroimaging. Labs and Teams: The Citri Lab at the Goodman Brain Sciences Building houses a multidisciplinary team of PhD students, postdocs, and technicians investigating neural circuits using advanced techniques like fiber photometry and optogenetics.
Prof. Harel Itamar is a Professor of Genetics at the Hebrew University of Jerusalem's Silberman Institute of Life Sciences. He leads the Harel Lab, focusing on experimental biology of vertebrate aging and age-related diseases using the African turquoise killifish as a genetic model. His work explores lifespan diversity, molecular mechanisms of aging, and disease modeling. Itamar holds a BSc from Ben-Gurion University, a PhD from the Weizmann Institute, and completed postdoctoral research at Stanford University. Research focuses include genetic engineering, live imaging of aging processes, and CRISPR/Cas9-based approaches. Key achievements include developing a comprehensive genetic platform for the killifish and discovering the germline's role in longevity. Awards include the 2024 Krill Prize and ERC Starting Grant. Teaching roles include courses on aging biology and developmental genetics. The lab is located at Givat Ram campus, with contact via itamarh@mail.huji.ac.il. Education: BSc (Ben-Gurion), PhD (Weizmann), Postdoc (Stanford) Lab Affiliations: Department of Genetics, Hebrew University Key Collaborations: Valenzano Lab, Stanford University
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.
