| 2026 | AAAI | SVD-NO: Learning PDE Solution Operators with SVD Integral Kernels. | Noam Koren, Ralf J. J. Mackenbach, Ruud J. G. van Sloun, Kira Radinsky, Daniel Freedman |
| 2026 | AAAI | PDE-Driven Spatiotemporal Generative Modeling for Multilead ECG Synthesis. | Yakir Yehuda, Kira Radinsky |
| 2026 | ACL | Propaganda Signals in LLMs: Perspectival Divergence and Narrative Framing in the Russia-Ukraine War. | Ofir Shabat, Ido Guy, Kira Radinsky |
| 2025 | CIKM | GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning. | Dan Kalifa, Uriel Singer, Kira Radinsky |
| 2025 | CIKM | Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration. | Amitay Sicherman, Kira Radinsky |
| 2025 | KDD | Cross-Species Insights: Transforming Drug Efficacy from Rats to Humans Using Tissue-Specific Generative Models. | Sally Turutov, Kira Radinsky |
| 2024 | AAAI | Molecular Optimization Model with Patentability Constraint. | Sally Turutov, Kira Radinsky |
| 2024 | NAACL | Leveraging Prototypical Representations for Mitigating Social Bias without Demographic Information. | Shadi Iskander, Kira Radinsky, Yonatan Belinkov |
| 2024 | SIGIR | CIQA: A Coding Inspired Question Answering Model. | Mousa Arraf, Kira Radinsky |
| 2023 | ACL | Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection. | Shadi Iskander, Kira Radinsky, Yonatan Belinkov |
| 2023 | CIKM | GraphERT- Transformers-based Temporal Dynamic Graph Embedding. | Moran Beladev, Gilad Katz, Lior Rokach, Uriel Singer, Kira Radinsky |
| 2023 | CIKM | CFOM: Lead Optimization For Drug Discovery With Limited Data. | Natan Kaminsky, Uriel Singer, Kira Radinsky |
| 2023 | CIKM | Generating Optimized Molecules without Patent Infringement. | Sally Turutov, Kira Radinsky |
| 2023 | EMNLP | Clinical Contradiction Detection. | Dave Makhervaks, Plia Gillis, Kira Radinsky |
| 2023 | KDD | Self-supervised Classification of Clinical Multivariate Time Series using Time Series Dynamics. | Yakir Yehuda, Daniel Freedman, Kira Radinsky |
| 2023 | SIGIR | What If: Generating Code to Answer Simulation Questions in Chemistry Texts. | Gal Peretz, Mousa Arraf, Kira Radinsky |
| 2022 | AAAI | Learning to Rank Articles for Molecular Queries. | Galia Nordon, Aviram Magen, Ido Guy, Kira Radinsky |
| 2022 | AAAI | EqGNN: Equalized Node Opportunity in Graphs. | Uriel Singer, Kira Radinsky |
| 2022 | CIKM | Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction. | Roy Benjamin, Uriel Singer, Kira Radinsky |
| 2022 | NAACL | Temporal Attention for Language Models. | Guy D. Rosin, Kira Radinsky |
| 2022 | WSDM | Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly. | Dan Kalifa, Uriel Singer, Ido Guy, Guy D. Rosin, Kira Radinsky |
| 2022 | WSDM | Time Masking for Temporal Language Models. | Guy D. Rosin, Ido Guy, Kira Radinsky |
| 2021 | AAAI | ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning. | Tomer Golany, Daniel Freedman, Kira Radinsky |
| 2021 | CIKM | Multi-Property Molecular Optimization using an Integrated Poly-Cycle Architecture. | Guy Barshatski, Galia Nordon, Kira Radinsky |
| 2021 | ICML | 12-Lead ECG Reconstruction via Koopman Operators. | Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha |
| 2021 | KDD | Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization. | Guy Barshatski, Kira Radinsky |
| 2021 | WSDM | Event-Driven Query Expansion. | Guy D. Rosin, Ido Guy, Kira Radinsky |
| 2020 | AAAI | Improving ECG Classification Using Generative Adversarial Networks. | Tomer Golany, Gal Lavee, Shai Tejman-Yarden, Kira Radinsky |
| 2020 | AAAI | Chemical and Textual Embeddings for Drug Repurposing. | Galia Nordon, Levi Gottlieb, Kira Radinsky |
| 2020 | CIKM | tdGraphEmbed: Temporal Dynamic Graph-Level Embedding. | Moran Beladev, Lior Rokach, Gilad Katz, Ido Guy, Kira Radinsky |
| 2020 | ICML | SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification. | Tomer Golany, Kira Radinsky, Daniel Freedman |
| 2019 | AAAI | PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification. | Tomer Golany, Kira Radinsky |
| 2019 | AAAI | Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications. | Galia Nordon, Gideon Koren, Varda Shalev, Eric Horvitz, Kira Radinsky |
| 2019 | AAAI | Building Causal Graphs from Medical Literature and Electronic Medical Records. | Galia Nordon, Gideon Koren, Varda Shalev, Benny Kimelfeld, Uri Shalit, Kira Radinsky |
| 2019 | CIKM | Learning to Generate Personalized Product Descriptions. | Guy Elad, Ido Guy, Slava Novgorodov, Benny Kimelfeld, Kira Radinsky |
| 2019 | CoNLL | Generating Timelines by Modeling Semantic Change. | Guy D. Rosin, Kira Radinsky |
| 2019 | EMNLP | Cross-Cultural Transfer Learning for Text Classification. | Dor Ringel, Gal Lavee, Ido Guy, Kira Radinsky |
| 2019 | IJCAI | Node Embedding over Temporal Graphs. | Uriel Singer, Ido Guy, Kira Radinsky |
| 2019 | WWW | Learning Novelty-Aware Ranking of Answers to Complex Questions. | Shahar Harel, Sefi Albo, Eugene Agichtein, Kira Radinsky |
| 2019 | WWW | Generating Product Descriptions from User Reviews. | Slava Novgorodov, Guy Elad, Ido Guy, Kira Radinsky |
| 2019 | SIMULTECH | Explorations and Lessons Learned in Building an Autonomous Formula SAE Car from Simulations. | Dean Zadok, Tom Hirshberg, Amir Biran, Kira Radinsky, Ashish Kapoor |
| 2018 | CoNLL | Latent Entities Extraction: How to Extract Entities that Do Not Appear in the Text? | Eylon Shoshan, Kira Radinsky |
| 2018 | KDD | Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks. | Shahar Harel, Kira Radinsky |
| 2018 | WWW | The BIG Web Track Chairs' Welcome & Organization. | Evgeniy Gabrilovich, Kira Radinsky, Kuansan Wang |
| 2017 | CoNLL | Named Entity Disambiguation for Noisy Text. | Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy |
| 2017 | EMNLP | Learning Word Relatedness over Time. | Guy D. Rosin, Eytan Adar, Kira Radinsky |
| 2017 | SIGIR | Structuring the Unstructured: From Startup to Making Sense of eBay's Huge eCommerce Inventory. | Ido Guy, Kira Radinsky |
| 2013 | SIGIR | SIGIR 2013 workshop on time aware information access (#TAIA2013). | Fernando Diaz, Susan T. Dumais, Miles Efron, Kira Radinsky, Maarten de Rijke, Milad Shokouhi |
| 2013 | WSDM | Predicting content change on the web. | Kira Radinsky, Paul N. Bennett |
| 2013 | WSDM | Temporal web dynamics and its application to information retrieval. | Kira Radinsky, Fernando Diaz, Susan T. Dumais, Milad Shokouhi, Anlei Dong, Yi Chang |
| 2013 | WSDM | Mining the web to predict future events. | Kira Radinsky, Eric Horvitz |
| 2012 | WWW | Learning causality for news events prediction. | Kira Radinsky, Sagie Davidovich, Shaul Markovitch |
| 2012 | WWW | Modeling and predicting behavioral dynamics on the web. | Kira Radinsky, Krysta M. Svore, Susan T. Dumais, Jaime Teevan, Alex Bocharov, Eric Horvitz |
| 2012 | SIGIR | Time-sensitive query auto-completion. | Milad Shokouhi, Kira Radinsky |
| 2011 | WWW | A word at a time: computing word relatedness using temporal semantic analysis. | Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovich, Shaul Markovitch |
| 2011 | WSDM | Ranking from pairs and triplets: information quality, evaluation methods and query complexity. | Kira Radinsky, Nir Ailon |