Organization profile
Organization profile
The Institute for Applied AI Research at Ben-Gurion University advances cutting-edge research in artificial intelligence, with a mission to translate scientific breakthroughs into deployable solutions that create measurable impact. At the Applied AI Institute, our goal is to leverage cutting-edge artificial intelligence to address real-world challenges and foster innovation across a range of fields; from healthcare to finance, we are committed to creating solutions that have a tangible impact on society. The institute explores core challenges in AI and Machine Learning and includes 20 scientists with diverse expertise spanning modern ML and deep learning (optimization, representation learning, self-supervision), natural language processing (multilingual NLP, information extraction, text generation, clinical/legal NLP), computer vision and multimodal learning, recommender systems and information retrieval, trustworthy and explainable AI (fairness, privacy, robustness, auditability), sequential decision-making and reinforcement learning, time-series modeling and forecasting, graph and causal learning, and data-centric AI/MLOps. We cultivate deep, long-term partnerships with industry through joint research programs and co-led projects, including shared testbeds and datasets, co-authored publications, and ongoing mentorship and internships that keep our collaborations scientifically rigorous and practically relevant.
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Collaborations and top research areas from the last five years
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Profiles
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Omri Azencot
- Institute for Applied AI Research - Senior Lecturer
- Statistics and Data Analysis Program - Member
Person: Academic
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Yehuda Dar
- Institute for Applied AI Research - Senior Lecturer
- Statistics and Data Analysis Program - Member
Person: Academic
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Research output
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AI-driven methodology for mining scientific literature and extracting databases: A case study on a chemical process
Sror, G., Etzyoni, G., Fire, M., Berkovich, R., Rokach, L. & Herskowitz, M., 1 May 2026, In: Energy and AI. 24, 100741.Research output: Contribution to journal › Article › peer-review
Open Access -
Automatically Reviewing Movie Plots with LLMs: (Short Paper)
Kaplan, M., Shmilovici, A. & Last, M., 1 Jan 2026, Cyber Security, Cryptology, and Machine Learning - 9th International Symposium, CSCML 2025, Proceedings. Akavia, A., Dolev, S., Lysyanskaya, A. & Puzis, R. (eds.). Springer Science and Business Media Deutschland GmbH, p. 347-357 11 p. (Lecture Notes in Computer Science; vol. 16244 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Blunder prediction in chess
Rokach, Y. & Shapira, B., 1 Feb 2026, In: Applied Intelligence. 56, 4, 92.Research output: Contribution to journal › Article › peer-review
Open Access
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Toward real-world unsupervised multifactor sequential disentanglement of multi-modal information
Azencot, O. (PI)
1/01/25 → 31/12/29
Project: Research
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Interactive and Compositional Semantic Parsing for Complex Domains
Elhadad, M. (PI)
1/01/24 → 31/12/27
Project: Research
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