Technion

Hadas Abraham

Research Area:
Hybrid Cloud

"I focused on enhancing the performance of automated Retrieval-Augmented Generation (RAG) across multiple domains."

Technion

Tomer Ashuach

Research Area:
RAG on LLMs (NLP)

"I'm using RAG and LangGraph with LLMs to automate the extraction of data-related risks from legal documents, providing a clear and concise assessment of these risks and their urgency."

Hebrew University of Jerusalem

Nitzan Barzilay

Research Area:
NLP

"I’m working on efficient benchmarking for RAG systems that allows trustworthy evaluation of many RAG configurations even on a limited budget."

Bar Ilan University

Itay Etelis

Research Area:
Hybrid Cloud

"I have been leveraging generative AI to develop an agentic AI connector. This project involves addressing the schema matching problem and implementing the necessary transformations."

Technion

Marah Ghoummaid

Research Area:
AI for Multi-Cloud Networking

"I’m working on leveraging AI and NLP techniques to improve and innovate features within multi-cloud networking tools."

Tel-Aviv University

Nimrod Harel

Research Area:
In-Context Learning (ICL)

"My research is about leveraging in-context learning (ICL) as a tool for compressing context within deep learning."

Technion

Reda Igabaria

Research Area:
Quality Technologies

"I’m working on developing an evaluation measurement for watsonx code assistant. Specifically, our work is about exploring the use of LLMs for code generation evaluation."

Hebrew University of Jerusalem

Itay Lavie

Research Area:
Decision Optimization

“I work on theoretical understanding of transformers in the context of combinatorial optimization.”

Technion

Ido Levy

Research Area:
AI

"During my internship in the AI department, I designed and developed a general web agent to solve complex tasks using an agentic workflow architecture."

Hebrew University

Gili Lior

Research Area:
NLP

"I work on developing self-improving and self-criticizing LLMs."

Hebrew University of Jerusalem

Noa Moriel

Research Area:
Biomedical foundational models for target discovery

"I set out to explore whether transcriptomic foundation models, like scGPT, truly learn biological relationships through pretraining, particularly actual gene regulatory connections."

Technion

Itay Nakash

Research Area:
Red-Teaming LLM Agents

"Through an approach called red teaming, I’m identifying vulnerabilities in LLM agents and uncovering potential risks to ensure we deliver safer, more reliable systems."

The Hebrew University of Jerusalem

Roni Schwartz

Research Area:
security AI

"I’m developing an optimization algorithm that uses scale manipulation within a graph model to reduce multiplication depth in fully homomorphic encryption (FHE) computations for LLMs that execute on encrypted data."

Tel Aviv University

Ben Shapira

Research Area:
Generative Modelling
for Drug Discovery

"I contributed to a computational biology research paper that focuses on developing a multi-domain model for drug discovery by fine-tuning the foundation model to learn interesting downstream tasks."

Ben-Gurion University

Noa Tal

Research Area:
NLP

"I'm generating data that simulates conversations of an analyst in a risk event chat using LLMs. I'm also evaluating the user's response to the answers received through the chat."

Ben-Gurion University

Avraham Yagudaev

Research Area:
Security

"I’m working on developing a comprehensive dataset of SQL queries to train a model to identify SQL injection vulnerabilities."

Tel Aviv University

Ido Amos

Research Area:
Generative Modeling for Drug Discovery

"During my internship at IBM, I focused on leveraging graph neural networks for the challenging task of drug discovery. This role gave me the unique opportunity to tackle the challenge of designing novel drugs with state-of-the-art computational methods, working alongside a fantastic team"

Ben-Gurion University

Ariel Blobstein

Research Area:
NLP

"I am working on generating synthetic data sets to be served as a training set for Large Language Models. I am generating data sets for various query languages using LLMs and syntax rules. "

Technion

Roy Elkabetz

Research Area:
Quantum

"I worked on single qubit pulsed quantum gate optimization using Machine Learning methods. I had a great time at IBM, the research topic was fascinating, and it has been awesome to experience how cutting-edge research in quantum computing takes part in IBM's products and applications."

Technion

Elazar Gershuni

Research Area:
Hybrid Cloud

"During my internship at IBM Research - Israel, my area of research has been the static analysis of software."

Technion

Noam Koren

Research Area:
Security

"I am an intern in the AI Privacy group. I am working on membership inference attacks for time series models."

Hebrew University

Osher Maayan

Research Area:
Hybrid Cloud

"During my internship in the Hybrid Cloud group, I built employed language models for cardinality estimation of complex queries, which are common in analytics and integration pipelines."

Hebrew University

Zohar Schwartzman-Nowik

Research Area:
Quantum

"During my internship, I am analyzing the performance of quantum error correction codes in the presence of realistic, physically inspired noise models."

Tel Aviv University

Nimrod Shabtay

Research Area:
Artificial Intelligence

"Working on scene understanding and visual question-answering with graphs and LLMs"

University of Oxford

Lucile Ter-Minassian

Research Area:
Causal Inference and Explainable Machine Learning

"During my time at IBM, I developed a tree-based model that identifies clusters where natural experiments occur. Our model can characterize overlap and estimate causal effects in an interpretable manner."

Hebrew University

Elkana Tovey

Research Area:
Secure Communication, Networking, Applied Cryptography

"I work on secure proxying for servers behind a firewall in Hybrid Cloud"

Hebrew University

Avihu Dekel

Research Area:
Deep Learning for Healthcare

"Working on pretraining multi-modal transformers in a self-supervised manner on structured data, MRI images, and genomic data from UK Biobank for improving downstream risk prediction tasks."

Hebrew University

Liran Shirizly

Research Area:
Quantum computing

"During my internship, I worked on modelling the experimental noisy dynamics of IBM's superconducting qubits."

Centrale Lille (France)

Rony Abecidan

Research Area:
Causal Inference, Machine Learning and Healthcare

"I am estimating how much events are unseen within a medical database so that we can correct causal estimations we could derive from it."

Technion

Antonio Abu Nassar

Research Area:
mutation analysis for automatic unit-level differential test generation

"At IBM, I work on introducing an additional tool for unit-level test generation, namely mutation analysis, and measuring its statistical advantage."

Bar Ilan University

Ori Ernst

Research Area:
Multi Document Summarization

"In my work, I try to automatically match between customer's security requirements and cloud standards using innovative NLP interpretability methods. IBM's work environment enables high - level research with great people and experts in their field."

University of Haifa

Marcelo Feighelstein

Research Area:
Automatic Recognition of Animal Emotions

"The goal of our project is to build an AI-based application able to interpret flow charts on images and answer questions based on such interpretation. As part of this project we built the first GraphQA dataset, including flow chart images, corresponding metadata and tailored Q&As for each graph, supplying an accuracy baseline for such Q&A interpretation task."

Technion

Itai Gat

Research Area:
Speech (IBM) Bias removal and generalization in multi-modal settings (Technion)

"I work on learning data representations that can separate the distinct, informative factors in speech signals such as the speaker information, textual content, etc. The goal is to enhance various speech classification tasks' generalization abilities when the number of labeled training examples is relatively small."

Technion

Rom Gutman

Research Area:
Causal Inference, Machine Learning and Healthcare

"I'm working on evaluation of calibration as a metric for Propensity score correctness."

University of Haifa

Ibrahim Jubran

Research Area:
Computer Vision, Machine / Deep Learning, and Compression of Big Data

"I am working on disease progression prediction and simulation in Mammography images."

Tel Aviv University

Yuval Kirstain

Research Area:
NLP

"I'm working on end-to-end dialog systems."

University of Haifa

Alexandra Kogan

Research Area:
Machine learning

"I use Machine Learning to identify possible future melanoma and kidney cancer patients"

Technion

Oleg Kolosov

Research Area:
Identity centric networking and edge systems

"I work on Provider-side network-aware optimization in the 5G environment."

Technion

Yotam Lifshitz

Research Area:
Quantum Information

"I work on Quantum Computing Summer Intern, focusing on quantum state tomography."

Technion

Michael Mirkin

Research Area:
AI and Cybersecurity

"I'm working on analytics over encrypted data using fully homomorphic encryption."

Technion

Oded Naor

Research Area:
Distributed systems and blockchains

"I work on Ceph, an open-source distributed storage platform."

Technion

Elisheva Shamash

Research Area:
Decision Optimization

"I enjoy working at IBM very much. The people are pleasant and helpful, and the developing possibilities seem interesting and plentiful."

Technion

Daniel Shats

Research Area:
Deep Learning & Computer Vision for Healthcare

"I am working with the Deep Learning & Computer Vision team to win a 3d kidney disease segmentation competition."

Technion

Kfir Toledo

Research Area:
Networking ,Cloud, Algorithms

"I work on Function Chain Transport Optimization in Hybrid Cloud."

Technion

Chen Zeira Zeno

Research Area:
Neural Networks, Bayesian Deep Learning, Machine Learning

"I am an intern in the AI in Healthcare group. I am working on the topic of multimodal learning using Supervised Contrastive Learning."

University of Haifa

Yuli Zeira

Research Area:
NLP

"I work on a project aiming to detect the state of a chatbot-client dialogue at an early stage of the conversation, using classic machine learning methods ad state-of-the-art methods as well."