Nitay Calderon (Technion), Ph.D. student
Nitay’s research focuses on Natural Language Generation, Domain Adaptation and Causal Inference. Particularly, he develops causally-inspired models to enhance the interpretability and generalization of NLP models. He also develops NLP models for suicide detection.
Alex Chapanin (Technion), Ph.D. student
Alex works on the intersection of explainability, causality, and NLP. He develops methods for estimating the causal effect of high-level concepts on language models.
Rotem Dror (Haifa University), Assistant Professor
Rotem’s research involves developing statistically sound methodologies for empirical investigation and evaluation. Rotem is a co-organizer of DMLR (Data-centric Machine Learning Research Workshop) at ICML 2023 and was a Student Chair for the Student Research Workshop at ACL 2020. Rotem is also a co-organizer for the Eval4NLP workshop that is co-located with AACL 2023.
Amir Feder (Columbia University, Google Research), Postdoctoral researcher
Amir develops methods that integrate causality into NLP. In particular, he builds causally-driven algorithms that improve the reliability of NLP systems, and facilitate scientific exploration of text data. He was the lead organizer of the NLP and Causal Inference (CI+NLP) workshop at EMNLP 2021, and the tutorial on Causality for NLP at EMNLP 2022. He has also co-organized the Spurious Correlations, Invariance and Stability (SCIS) Workshop at ICML 2023.
Ariel Goldstein (The Hebrew University) Assistant Professor
Ariel explores the relation between Large Language Models and human brain activity during real-life events.
Anna Korhonen (University of Cambridge), Professor
Anna co-directs the Language Technology Laboratory (LTL) and directs the Centre for Human-Inspired Artificial Intelligence (CHIA). Her research is centered around NLP and how to develop, adapt and apply computational techniques to meet the needs of real-life applications. Many of her projects are interdisciplinary and involve data science collaboration with researchers in other fields (e.g., biomedicine, clinical and cognitive sciences). She has served on the ACL executive board, has acted as a program co-chair for ACL, and has co-organized over 20 ACL workshops.
Shir Lissak (Technion), Ph.D. student
Shir develops methodologies for improving suicide risk detection and under standing across diverse populations. Her methods are based on diverse data collection efforts, implemented through hospitals, crowd-sourcing, and social media.
Yaakov Ophir (Ariel University, University of Cambridge), Lecturer
Yaakov’s research centers on psychopathology in the age of digital technology and big data (e.g., AI-based suicide prevention, virtual reality therapies, and screen-use outcomes) and the scientific validity of Attention Deficit Hyperactivity Disorder.
Ilanit Sobol (Technion), MSc. student
Ilanit’s research leverages algorithms and LLMs to study psychological and social aspects of human behavior, emphasizing suicide ideation.
Lotem Peled-Cohen (Technion), Ph.D. student
Lotem's research delves into the human aspects of language, focusing on non-literal communication as well as the effects of neuro-degenerative diseases, such as Alzheimer's and dementia, on linguistic human behavior. Lotem co-authored a book on statistical significance in Natural Language Processing.
Roi Reichart (Technion), Associate Professor
Roi directs the NLP group of the Data and Decision Sciences Faculty of the Technion, Israel Institute of Technology, and is the co-editor in chief of the Transactions of the Association for Computational Linguistics (TACL). He develops robust methods for natural language learning across domains and languages, casaully-inspired methods for NLP (e.g. for model interpretation and robust learning) and language-based models for scientific problems in psychology, psychiatry and neuroscience. Roi has co-organized over 10 ACL workshops.
Refael Tikochinski (Technion), Ph.D. student
Refael’s research combines NLP and neuroscience. His work focuses on how the human brain incorporates context into language processing.
Mor Ventura (Technion), MSc. student
Mor’s research focuses on controlled generation and cultural aspects of Text-to-Image models.