Research Through Local and Commercial Cloud Computing
Cloud computing has become a critical enabler of modern academic research, providing scalable computational power, advanced AI infrastructure, and access to vast data‑processing capabilities essential for developing and deploying large language models and other complex machine‑learning systems. These capabilities are particularly vital in data‑intensive fields such as medicine, bioinformatics, and interdisciplinary scientific domains that rely on high‑performance computing and collaborative digital environments.
At IDSAI, we have translated this technological potential into concrete academic impact. In recent years, we have implemented comprehensive support frameworks that allow researchers to experiment with and adopt cloud‑computing platforms as part of their scientific workflow. This strategic investment has already facilitated dozens of academic studies, many of which have been published in leading journals, generating groundbreaking insights and advancing research across a wide range of disciplines.
The table below highlights leading research projects that leveraged local and commercial cloud‑computing resources to achieve significant scientific impact.
| Researcher Name | Supervisor | Research Title | Link to publiaction |
|---|---|---|---|
| Assaf Morag | Prof. Eran Toch | DPAR: design and implementation of a Data-driven Password Recommendation System | https://arxiv.org/abs/2406.03423 |
| Yuval Goth | Prof. Yoni Belmaker & Dr. Yoav Ram | Indicator species based Early Warning Signals for Critical Transitions in Ecosystems | |
| Ehud Sussman | Dr. Judith Somekh | mutation anaylsis somekh lab | |
| Omri Suissa | Prof. Maayan Zhitomirsky-Geffet, Dr. Avshalom Elmalech | Around the GLOBE: Numerical Aggregation Question-Answering on Heterogeneous Genealogical Knowledge Graphs with Deep Neural Networks | https://arxiv.org/abs/2307.16208 |
| Grisha Weintraub | Prof. Ehud Gudes, Prof. Shlomi Dolev | Optimizing data lakes queries | https://ieeexplore.ieee.org/abstract/document/10342737 |
| Gil shamai | Prof. Ron Kimmel | Prognosis, response to therapy, and molecular profiling of cancer by computational analysis of histopathology images | |
| Sagi Marom | Dr. Tal Daniel | Monitoring cleaning interactions using deep learning | |
| Shir Bar | Prof. Roi Holzman and Dr. Shai Avidan | Detecting Rare, Fitness-Determining Behaviors in Underwater Video Data | https://www.sciencedirect.com/science/article/pii/S1574954123002248 |
| Shahar Kasirer | Prof. David Sprinzak | Elucidating the mechano-signaling feedback underlying pattern development and regeneration in the inner ear | https://www.sciencedirect.com/science/article/pii/S0955067424001236 |
| Sagi Timinsky | Prof. Hagit Messer-Yaron and Dr. Jonathan Ostrometzky | Rain Estimation Using Loosely Matched Stations | |
| Ev Zisselman Vainshtein | Dr. Aviv Tamar | Explore to Generalize in Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/20818 |
| Eran Zvuloni | Prof. Joachim A. Behar | Representation learning and digital biomarkers for improved diagnosis, risk prediction and personalized management of cardiac diseases | |
| Dana Azouri, Oz Granit, Michael Alburqeurque | Prof Itay mayrose, Prof Tal Pupko, Prof Ishay mansour | the tree reconstruction game: phylogenetic reconstruction using reinforment learning | https://academic.oup.com/mbe/article/41/6/msae105/7686977 |
| Jonathan Mandl | Prof. Yaron Orenstein | Predicting gene expression levels based on promoter sequences by deep learning | |
| Korin Reznikov | Prof. Nir Sapir | Predictive model of soaring-birds flocks’ migration by weather radars using image processing and machine learning methods | Automatic detection of migrating soaring bird flocks using weather radars by deep learning |
| Ariel Amsel | Dr. Gilad Katz | Few-Shot Neural Architectures Performance Prediction Using Reinforcement Learning | |
| Sharon Erlichman | Prof. Roee Diamant | Comparing Ship’s AIS Data with Acoustic Indications of Shipping Underwater Radiated Noise | |
| Adir Hilvert | Prof. Pnina Soffer | Graph-based process mining and predictions | |
| Ruth Arbiv | Prof. Avi Rosenfeld | Quantifying Explainable Artificial Intelligence | |
| Roi Peleg | Prof. Assaf Hoogi | Adaptive Normalization to Reduce Data Bias and Increase Algorithm Fairness | |
| Eden Shkuri | Prof. Assaf Hoogi | Joint text-image model for better prediction of lung cancer in high-risk and low-risk patients | |
| Shmuel Ozeri | Developing a deep learning algorithm for detection and classification of occult jaw lesions using 3D image analysis of Cone-Beam CT examinations | ||
| Benjamin (Benji) Azaria | Prof. Shraga Shoval, Dr. Shani Alkobi, Dr. Ron Hirschprung | A Machine Learning Approach to Estimate the Value of Privacy and Sensitivity of a Published Text | |
| Matan Seidel | Prof. Doron Puder | Word Maps and Word Measures | |
| Dror Berechya | Prof. Ulf Leonhardt | Using cloud resources to investigate the Lifshitz cosmology - a theory of dark energy | |
| Meir Goldenberg | Dr. Meir Goldenberg | Exploring large parameter spaces of novel heuristic search algorithms | |
| Prameek Kannan | Prof. Amiyaal Ilany | Exploring the relationship between host social networks and the microbiome metacommunity in a free-living rock hyrax population | |
| Lilach Herzog | Prof. Amiyaal Ilany | Segmentation and Clustering of Rock Hyrax Repertoire | |
| Netanel Halevy | Dr. David Sinefeld | Detection and analysis of errors in Torah scrolls using image processing and machine learning | |
| Nir Lotan | Dr. Einat Minkov | Social world knowledge modeling and applications | |
| Inbal Goldstein schekler | Dr. Nir Sapir | Detecting and exploring the migration of bird flocks by weather radars using image processing and deep learning methods | |
| Maytal Caspary toroker | Dr. Sean Pachmanov Dvir | iucc-computational-materials | |
| Jonathan Fhima | Prof. Joachim A. Behar | Deep Learning for cardiovascular disease prediction from digital fundus images | |
| Jeremy Levy | Prof. Joachim A. Behar | Domain generalization for obstructive sleep apnea diagnosis based on single channel oximetry | |
| Sharom Haimov | Prof. Joachim A. Behar | Transfer Learning from Adults to Children for the Analysis of Physiological Time Series | |
| Dr. Orly Lewis | Dr. Orly Lewis | The History of Anatomy: A Textual and Visual Research | |
| Reut Moshe | Developing computational methods to predict the effect of multiple mutations on protein-protein interactions | ||
| Idan Grosbard | Using deep learning algorithms to unravel the transformation of the mental representation of faces during real-life familiarization | ||
| Dr. Maya Bechler-Speicher | Dr. Maya Bechler-Speicher | Graph Trees with Attention | |
| Dr. Yonatan Harnik | Dr. Yonatan Harnik | Mining and analysis of chemical mechanisms from scientific literature using deep learning | |
| Nirit Trabelsi | Prof. Ora Furman-Schueler | Peptide-protein interactions: Improving protocols and machine learning | https://academic.oup.com/bioinformatics/article/41/3/btaf107/8075121 |
| Julia Varga | Prof. Ora Furman-Schueler | Generative models for peptide-protein docking | |
| Orly Avraham | Prof. Ora Furman-Schueler | Utilizing deep learning language models to predict protein quaternary structure | |
| Dr. Nir Keret | Dr. Nir Keret | Unlocking Prevalent Information in EHR Data - a Pairwise Pseudo-likelihood Approach to Cox Regression | https://www.tandfonline.com/doi/full/10.1080/01621459.2024.2427431 |
| Sergey Timinsky | Prof. Hagit Messer Yaron and Dr. Jonatan Ostrometzky | Rain Estimation Using Loosely Matched Stations | |
| Alon Feldman | Computer vision of air quality | ||
| Itay Dattner | Model Selection And Lack-Of-Fit Testing For Systems Of Ordinary Differential Equations | ||
| Korin Reznikov | Prof. Nir Sapir | Predictive model of soaring-birds flocks’ migration by weather radars using image processing and machine learning methods | https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.14161 |
| Sagi Marom | Prof. Roi Holzman and Prof. Moshe Kiflawi | Monitoring cleaning interactions using deep learning | |
| Dr. Osnat Mokryn | Dr. Osnat Mokryn | Learning and Generalizing Via Surprisal | |
| Hagar Chen | Prof. Yaron Orenstein | Inferring accurate protein-RNA binding models from high-throughput in vitro sequencing data | https://academic.oup.com/bfg/article-abstract/16/3/171/2555388 |
| Michal Rahimi | Prof. Yaron Orenstein | Improving CRISPR/Cas9 on-target efficiency and repair outcome prediction by epigenetics features and deep neural networks trained on endogenous data | |
| Yossi Zaguri | Dr. Lev Tal-Or | Advancing Time Domain Astronomy through Big Data Analytics: Streamlined Data Processing and Cloud-Based Catalog Generation | |
| Aviv Lazar | Dr. Naama Kopelman | Protein Design with Directed Evolution, guided by NLP model | |
| Yaron Trink | Prof. Tomer Kalisky | Characterizing the latent gene expression space of kidney tumors | https://www.sciencedirect.com/science/article/pii/S1476558618300265 |
| Tal Fiskus | Prof. Yaron Orenstein | Improve prediction of binding intensity between RBP and RNA | |
| Yuval Goldstein | Prof. Eran Toch & Dr. Yoni Birman | Analyzing Cost-Effectiveness Tradeoff in Sensitive Data Detection in the Cloud | |
| Alexander Goldberg | NA | Mapping Hebrew Manuscripts (MHM): Hebrew Manuscripts as a Source for Knowledge | |
| Ido Blass | NA | Deep Learning-Based Prediction and Interpretation of the Epigenetic Landscape in Mammalian Sex Determination and Disorders of Sex Development | |
| Dr. Oleksandr Laskorunskyi | Dr. Oleksandr Laskorunskyi | Mixed-Effects Physics-Informed Machine Learning for Monitoring and Controlling Complex Dynamical Systems | |
| Danielle Shrem | NA | I-motifs Prediction by Deep Neural Networks | |
| Ido Tziony | Prof. Yaron Orenstein | Genomic dataset partitioning to minimize test-train leakage with applications to CRISPR/CAS9 on- and off-target prediction | |
| David Shulman | Dr. Itai Dattner | Bridging Physics and Machine Learning: PGNN Applications in Interdisciplinary Research | |
| Noam Shimshoviz | Prof. Yaron Orenstein | Predicting the specific interactions between proteins and DNA/RNA | |
| Jonathan Mandl | Prof. Yaron Orenstein | Predicting gene expression levels based on promoter sequences by deep learning | |
| Antonio Zaitoun | Prof. Mor Peleg & Dr. Tomer Sagi | Automated Ontology Learning, Expansion, and Evaluation | https://ojs.aaai.org/index.php/AAAI-SS/article/view/31797 |
| Naga Venkata Sai Kumar Manapragada | Prof. Dr. Jonathan Natanian | ML-based Urban Microclimate-integrated Building Energy Modeling Approach | https://www.mdpi.com/2071-1050/17/7/3025 |
| Hagai Hamami | Prof. Joachim A. Behar | Analysis of continuous Holter ECG recordings and clinical data for the risk prediction, diagnosis, and management of ventricular tachyarrhythmias | |
| Lisa Attali | Prof. Joachim A. Behar | Multi-Disease Risk Prediction from Large-Scale 24-Hour Holter ECG Recordings and Associated Clinical Data Using Deep Learning | |
| Raphael Judkiewicz | Prof. Joachim Behar | Developing Video Foundation Models for Volumetric OCT Analysis to Enhance Ophthalmic Diagnostics | |
| Arkadi Piven | Prof. Ron Kimmel | Computational Pathology for Predicting Chemotherapy Benefit in Breast Cancer Patients | |
| Roy Velich | Prof. Ron Kimmel | Learning Geometric Operators | |
| Irina Rabaev | - | Handwritten Text Recognition in Hebrew | |
| Ido Tziony | Prof. Yaron Orenstein | Predicting CRISPR–Cas9 Repair Outcomes from High-Throughput Sequencing Data | |
| Evyatar Komarovsky | Prof. Yaron Orenstein | Cell-aware Deep Learning for Predicting RNA–Protein Binding Sites Across Cell Types | |
| Sapir Bar | Prof. Yaron Orenstein | Variant-Aware Prediction of CRISPR-Cas9 Off-Target Activity Using Deep Learning Models | |
| Yehuda Dicker | Prof. Yaron Orenstein | Advancing the Classification of RNA-Binding Proteins Using Genome-Wide High-Throughput Datasets | |
| Joanthan Mandl | Prof. Yaron Orenstein | Predicting RNA-seq coverage of synthetic yeast genomes | |
| Dor Shlomo Gozlan | Prof. Niv Papo | Computational modeling of protein functional landscape based on deep mutational scanning | |
| Noam Tzuri | Prof. Niv Papo | Utilizing combinatorial methods in protein engineering to design therapies agents | |
| Ido Aharon | Prof. Sarit Kraus | Explainability to Instructions: Rules as Self-Improvement for LLMs | |
| Orly Lewis | The Living Text: AI-Driven Systems for Audio-Visual Scholarship in Greco-Roman Medicine | ||
| Tehila Rachel Dahan | Prof. Kfir Y. Levy | Toward Scalable Asynchronous Optimization of Large Language Models under Data-Dependent Delays | |
| Tzilla Eshel | Determining Origins of Ancient Metals: Exploring the Potential of Machine Learning for Lead Isotope Analysis | ||
| Galit Agmon | FINE-TUNING MODELS FOR SENTENCE SEGMENTATION IN SPONTANEOUS SPEECH | ||
| Gal Sarid | Dr. Oren Glickman | Enhancing Long-Context Utilization in Large Language Models | |
| Tony Zaitoun | Prof. Mor Peleg | Evaluation of a Data Collection AI-Assistant for back Pain |