Dr. Aya Soffer is the Vice President of AI Technologies at IBM Research and the Director of IBM’s research labs in Israel. In her role, Dr. Soffer is responsible for setting strategic directions and collaborating with IBM scientists globally to transform innovative ideas into cutting-edge AI technologies. She also works closely with IBM’s product groups and customers to bring research innovations to market. Dr. Soffer specializes in generative AI and its application in enterprise contexts, focusing on effectiveness, evaluation, trust, governance, and integration with enterprise data and assets. As the director of IBM Research – Israel, she ensures the lab remains a vibrant environment where research and innovation converge to tackle real-world challenges. Additionally, Dr. Soffer plays a key role in positioning the lab within the Israeli hi-tech ecosystem, fostering collaborations with academic institutions, multinational companies, and VC-backed startups. Throughout her tenure at IBM, she has spearheaded several strategic initiatives that evolved into successful products and solutions in the AI domains. Dr. Soffer has authored over 50 peer-reviewed papers, filed more than 15 patents, and has been an invited speaker at numerous conferences.

Dr. Darío Gil is an IBM Senior Vice President and the Director of IBM Research. Dr. Gil leads the technology roadmap and the technical community of IBM, directing innovation strategies in areas including hybrid cloud, AI, semiconductors, quantum computing, and exploratory science. Dr. Gil is responsible for IBM Research, one of the world’s largest and most influential corporate research labs, with over 3,000 researchers. He is the 12th Director in its 76-year history. He is also responsible for IBM's intellectual property strategy and business. Dr. Gil is a globally recognized leader of the quantum computing industry. Under his leadership, IBM was the first company in the world to build programmable quantum computers and make them universally available through the cloud. An advocate of collaborative research models, Dr. Gil co-chairs the MIT-IBM Watson AI Lab, which advances fundamental AI research to the broad benefit of industry and society. He also co-chairs the COVID-19 High-Performance Computing Consortium, which provides access to the world’s most powerful high-performance computing resources in support of COVID-19 research. Dr. Gil is a member of the National Science Board (NSB), the governing body of the National Science Foundation (NSF), serves on the President’s Research Council of the Canadian Institute for Advanced Research (CIFAR), and the MIT School of Engineering Dean's Advisory Council. Dr. Gil is on the boards of the Semiconductor Industry Association (SIA), New York Academy of Sciences, New York Hall of Science, and Research!America. Dr. Gil received his Ph.D. in Electrical Engineering and Computer Science from MIT.

Aaron Ciechanover was born in Haifa, Israel in 1947. He is currently a Distinguished Research Professor in the Faculty of Medicine at the Technion - Israel Institute of Technology in Haifa, Israel. He received his M.Sc. (1971) and M.D. (1973) from the Hebrew University in Jerusalem. He then completed his national service (1973-1976) as a military physician and continued his studies to obtain a doctorate in biological sciences in the Faculty of Medicine at the Technion (D.Sc.; 1982). There, as a graduate student with Dr. Avram Hershko and in collaboration with Dr. Irwin A. Rose from the Fox Chase Cancer Center in Philadelphia, USA, they discovered that covalent attachment of ubiquitin to a target protein signals it for degradation. They deciphered the mechanism of conjugation, described the general proteolytic functions of the system, and proposed a model according to which this modification serves as a recognition signal for a specific downstream protease. As a post-doctoral fellow with Dr. Harvey Lodish at MIT, he continued his studies on the ubiquitin system and made additional important discoveries. Along the years, it has become clear that ubiquitin-mediated proteolysis plays major roles in numerous cellular processes, and aberrations in the system underlie the pathogenetic mechanisms of many diseases, among them certain malignancies and neurodegenerative disorders. Consequently, the system has become an important platform for drug development. Among the numerous prizes Ciechanover received are the 2000 Albert Lasker Award, the 2002 EMET Prize, the 2003 Israel Prize, and the 2004 Nobel Prize (in Chemistry, shared with Drs. Hershko and Rose). Among many academies, Ciechanover is a member of the Israeli National Academy of Sciences and Humanities, the European Molecular Biology Organization (EMBO), the American Academy of Arts and Sciences (Foreign Fellow), the American Philosophical Society, the National Academies of Sciences (NAS) and Medicine (NAM) of the USA (Foreign Associate), the Pontifical Academy of Sciences at the Vatican, the Chinese Academy of Sciences (CAS; Foreign Member), the Russian Academy of Sciences (Foreign Member), and the German Academy of Sciences (Leopoldina).

Noam Slonim is a Distinguished Engineer (DE) at IBM Research AI and the founder and Principal Investigator of Project Debater. Before that, he was an Associate Research Scholar in the Department of Physics at Princeton University. Prior to that, he did his PhD at the Interdisciplinary Center for Neural Computation (ICNC) at the Hebrew University of Jerusalem. Noam is mainly interested in practical applications of Language Models and Agentic AI workflows. He has over 25 years of experience in machine learning, AI, text analysis, and NLP, and now serves as the IBM Research lead for Language Models Utilization.

Dr. Gabriel Stanovsky is a senior lecturer (assistant professor) in the School of Computer Science and Engineering at the Hebrew University of Jerusalem, and a research scientist at the Allen Institute for AI (Ai2). He did his postdoctoral research at the University of Washington and Ai2 in Seattle, working with Prof. Luke Zettlemoyer and Prof. Noah Smith, and his PhD with Prof. Ido Dagan at Bar-Ilan University. He is interested in developing natural language processing models which deal with real-world texts and help answer multi-disciplinary research questions, in archeology, law, medicine, and more. His work has received awards at top-tier venues, including ACL, NAACL, and CoNLL, and recognition in popular journals such as Science and New Scientist, and the New York Times.

Ora Schueler-Furman’s research interest lies in understanding the basic molecular principles that govern protein interactions, and how these interactions allow the admirable complexity of biological systems. In particular, her group has focused on the modeling of weak peptide-mediated interactions that are easily manipulated by their context, and play crucial roles in regulatory decisions that are disturbed in cancer. These interactions allow us to ask challenging questions regarding the complexity of biological regulation, and channel the development and use of advanced Deep Learning approaches towards more complex structural questions. Ora Schueler-Furman is a leading figure in the field of peptide docking and peptide-mediated interactions. The labs’ state of the art peptide modeling protocols brought peptide docking into wide reach and stimulated applications and further development in the field, including the Deep Learning of structural features. Ora Schueler-Furman is a key figure in the Rosetta modeling community (member of the board), in the CAPRI protein docking community, and the Israel Society of Bioinformatics and Computational Biology (served as last president). Her bibliography includes >120 publications, cited >10,100x, with an h-index of 48 (according to Google Scholar). The major topics of interest of her group include: (1) Development and large-scale application of accurate protocols for peptide-protein docking (e.g., Rosetta FlexPepDock, PatchMAN, peptide docking using Alphafold2). (2) Structure-based identification and denovo design of peptide substrates (e.g., Rosetta FlexPepBind, peptide design using ProteinMPNN). Using a structural model of a substrate as starting point, the lab has designed a strong, sub-nanomolar, specific inhibitor of the B55 subunit of phosphatase PP2A (using ProteinMPNN). (3) Modeling flexible, multivalent interactions to study of signal integration strategies by multiple peptide-mediated interactions. (4) Detection of novel regulatory features from overconfident structural models generated by Deep Learning models. Scientific success and enthusiasm are maximized by recruiting people of diverse, mutually enriching backgrounds, providing the framework for research in a stimulating, encouraging, inclusive environment. The Furman lab maintains collaborations with many other labs to extend their approaches to a wide range of systems, enabling to identify specific features of a wide range of different regulatory systems, as well as to distill common principles. It is important to address both opportunities as well as dangers that can arise from the recent advances in protein design. To address this, Ora Schueler-Furman has been involved in and signed “Principles for the Responsible Development of AI for Biological Design”, a document that was formulated by the protein design community.

Gal Chechik is a Professor of computer science at Bar-Ilan University and a senior director of AI research at NVIDIA. His current research focuses on learning for reasoning and perception. In 2018, Gal joined NVIDIA to found and head nvidia's research in Israel. Prior to that, Gal was a staff research scientist at Google Brain and Google research developing large-scale algorithms for machine perception, used by millions daily. Gal earned his PhD in 2004 from the Hebrew University, and completed his postdoctoral training at Stanford CS department. Gal authored ~150 refereed publications, ~60 patents, including publications in Nature Biotechnology, Cell and PNAS. His work won awards at ICML and NeurIPS, for his research on learning vision-language representations and on geometric deep learning.

Prof. Lihi Zelnik-Manor is the Executive Vice President for Innovation and Industry Relations of the Technion - Israel Institute of Technology. Prof. Zelnik-Manor joined the Department of Electrical and Computer Engineering (ECE) at the Technion in 2007 and became a courtesy member at the Data and Decisions Faculty in 2023. She served as vice-dean of graduate studies in ECE between 2021-2023 and vice-dean for undergraduate students in 2014. Between 2018-2021 she was a Senior Director and the General Manager of Alibaba's R&D center in Israel, leading its establishment and growth into an end-to-end site delivering products with millions of users, based on state-of-the-art technology. Prior to that she was a visiting Associate Professor at CornellTech during its establishment years, and a Post-doctoral scholar at Caltech. Her main area of expertise is Computer Vision, in which she performs research as well as holds industry advisory roles. Prof Zelnik-Manor has done extensive community contribution, serving as General Chair of CVPR'21 and ECCV'22, Program Chair of CVPR'16, Associate Editor at TPAMI, served multiple times as Area Chair at CVPR, ECCV and was on the award committee of ACCV'18, CVPR'19 and CVPR'22. Looking forward she will serve as Program Chair of CVPR'27.

His previous roles in HU include: Head of the authority for experimental research students (2021), Dean, Faculty of Dental Medicine for 8 years (2013-2021), Head HU teaching and learning center (2012-2022), and Head MEITAL- inter university center for e-learning (2015-2023). Prof Palmon developed technologies promoting the diagnostic value of saliva for both local and systemic diseases. His work was supported along the years by various research agencies including the Israeli Science Foundation, United States-Israel Binational Science Foundation, German-Israel Science Foundation, Ministry of Sciences and Ministry of Health. In 2018 he founded a Hebrew University spin off company named Salignostics to translate this new knowledge into home use rapid diagnostic tests. Salignostics was the only Israeli company reached stage 3 in the NIH RADx covid-19 program*(only 28 companies worldwide reached this stage, only 3 outside of US) and has CE for both saliva based covid-19 test and saliva-based pregnancy test. Salignostics invention was chosen by Time magazine as one of the best inventions of 2023.

Prof. Michal Rosen-Zvi is the director of Healthcare and Life Sciences at IBM Research and an adjunct Computational Medicine Professor at the Hebrew University’s Faculty of Medicine. She is a senior manager in the IBM Research lab in Israel, where she leads the AI for Drug Discovery department. Michal holds a PhD in computational physics and completed her postdoctoral studies at UC Berkeley, UC Irvine, and the Hebrew University in the area of machine learning. She joined IBM Research in 2005 and has since led various projects in the area of machine learning in the biomedical domain, and been recognized for her contributions, e.g., to AI technologies in wafer production and contributions to partnerships with pharmaceutical companies such as Guerbet and Teva. Michal has published close to 70 peer-reviewed papers. She is a PLOS ONE editor, a member of the iScience Editorial Advisory Board, and an elected member of the Board of the Israeli Society for HealthTech.

Shila Ofek-Koifman is a Director for AI Language Technologies in IBM Research. She leads the AI area in the Israel Research Lab, where she is responsible for top-talent teams in the language, vision, and speech domains. Shila works with her teams to innovate, advance the state of the art, and publish in these fields in leading conferences, while also delivering advanced research to IBM products. In her global role, Shila co-leads the global Research strategy in Language Technologies, working with scientists around the globe to set the strategy for IBM Research in this space and drive collaboration and innovative work across global teams. She works closely with IBM product teams, focusing mostly on the watsonx product family while also engaging with customers. Shila’s areas of focus include large language models (LLMs) and agentic systems evaluation, document understanding, Retrieval-Augmented Generation (RAG) systems, and agentic AI. Throughout her 20 years in IBM, Shila has led many strategic efforts and drove teams to successful innovations that materialized and matured into differentiating research technologies delivered into IBM products. Over the years, she has received multiple IBM awards for her research work and contributions to the business.

MIT postdoc and Fulbright fellow specializing in applied math and AI within the Mechanical Engineering Department. A dedicated Technion AI researcher, recognized as the top-ranked lecturer for original courses in Nonlinear Dynamics and Machine Learning. Harvard Leadership Program alumnus and Forbes 30 Under 30 honoree. Serves as a Captain in the reserves and holds an esteemed officer position at Unit 8200 (the Israeli NSA). Distinguished participant of Unit 81's elite "Brakim" program and acknowledged as a distinguished scientist within the IDF, a select group featuring only three leading academics in the military. Previous experience as a Mechanical Engineer at Israel's Prime Minister's Office, holding B.Sc., M.Sc., and PhD degrees with Cum Laude honors, all earned at the Technion.

Prof. Roi Reichart is an Associate Professor and Schmidt Career Advancement Chair in Artificial Intelligence at the faculty of Data and Decisions Science of the Technion – Israel Institute of Technology. He is also a Co-editor in Chief of the Transactions of the Association for Computational Linguistics (TACL, MIT Press). He is active in the hi-tech industry, has served as a chief scientist for several start-ups and provided consultancy services and held visiting positions in others (among previous companies: Yahoo!, Gong.io, and Meta). Roi's research focuses on making the machine learning of NLP more robust, adaptive, interpretable and realistic for real-world data and practical applications. Additionally, over the last seven years his research group has been developing language-based, multi-modal computational models for scientific problems in areas that involve the human mind, such as psychology, psychiatry, neuroscience and decision making, and complementary algorithms for deriving causal inferences about the predictions of Large Language Models in order to draw scientific conclusions from their predictions.