The ICINAi community
Our steering group brings together researchers across institutions, disciplines, and sectors to help shape ICINAi’s scientific direction and shared infrastructure.
Scientific leadership
Researchers helping guide the consortium’s priorities, programs, and standards.
Northeastern University
David Bau is an assistant professor at Northeastern University and director of the National Deep Inference Fabric. His research studies emergent internal mechanisms in large neural networks across language and vision, including causal tracing, model editing, and shared interpretability infrastructure.
Tel Aviv University
Mor Geva is an assistant professor in the School of Computer Science and AI at Tel Aviv University. Her research opens up the inner workings of large language models to improve their transparency, control, and reasoning.
Technion – Israel Institute of Technology
Yonatan Belinkov is an associate professor at the Technion. He develops probing, causal-analysis, and evaluation methods for understanding what language models represent and how their internal computations produce behavior.
Brown University · Google DeepMind
Ellie Pavlick is an associate professor at Brown University and a research scientist at Google DeepMind. She studies conceptual representations, language, reasoning, and learning, often by comparing the behavior of humans and language models.
Stanford University
Christopher Potts is a professor of linguistics at Stanford University, with a courtesy appointment in computer science. His research connects compositionality, causal abstraction, interpretability, information retrieval, and foundation-model programming.
University of Toronto · Vector Institute · Anthropic
Roger Grosse is a professor at the University of Toronto, a Vector Institute faculty member, and a researcher at Anthropic. His work spans mechanistic interpretability, alignment science, neural-network optimization, and representation learning.
Boston University
Aaron Mueller is an assistant professor of computer science at Boston University. His lab studies how concepts are learned and represented in language models, developing tools for circuit discovery, interpretability, and model control.
Boston University
Naomi Saphra is an assistant professor in Computing & Data Sciences at Boston University. Her research examines language-model training dynamics, how structure emerges during learning, and what those processes reveal about generalization and interpretability.
Weizmann Institute of Science
Tamar Rott Shaham is an assistant professor of computer science and applied mathematics at the Weizmann Institute. She develops automated tools to discover and explain model operations, then uses those insights to control model behavior.
University of Utah
Ana Marasović is an assistant professor in the Kahlert School of Computing at the University of Utah. Her work in natural language processing and human-centered AI develops more faithful explanations and evaluations of language models.
University of Edinburgh · University of Amsterdam
Ivan Titov is a professor at the University of Edinburgh and the University of Amsterdam. He studies trustworthy, robust, interpretable, and controllable language models and leads major European training and research programs in natural language processing.
New York University · Google
Tal Linzen is an associate professor at New York University and a staff research scientist at Google. His work connects language-model evaluation and interpretability with linguistics and cognitive science, especially the study of syntactic structure.
Northeastern University
Byron Wallace is a professor at Northeastern University and director of its BS in Artificial Intelligence program. His research develops machine-learning and natural-language-processing methods for health informatics, with particular attention to faithful explanations, biomedical evidence synthesis, and human–AI systems.
Bar-Ilan University
Yanai Elazar is an assistant professor of computer science and AI at Bar-Ilan University. He builds tools for a science of generative models, including methods for interpretability, data attribution, and rigorous evaluation.
University College London · Parallax
Mario Giulianelli is an associate professor of computational linguistics at University College London and a cofounder of Parallax. He combines behavioral evidence with analysis of internal mechanisms to make AI evaluation more rigorous and explanatory.
Parallax
Gabriele Sarti is a cofounder and technical director at Parallax. He develops white-box methods for context attribution, user modeling, deception detection, and model monitoring, alongside open-source libraries for language-model interpretability.
Simplex · Astera Institute
Eric J. Michaud is a research scientist at Simplex and the Astera Institute. He pursues empirical and conceptual accounts of learned computation, including work on sparse feature circuits, representation geometry, and mechanistic program synthesis.
Stanford University
Noah D. Goodman is a professor of psychology and computer science at Stanford University. His research uses probabilistic models to study language, cognition, and reasoning, including what language-model behavior reveals about internal representations and thought.
Carnegie Mellon University
Zachary Lipton is the Raj Reddy Associate Professor of Machine Learning at Carnegie Mellon University. His research examines the conceptual foundations of interpretability, robust and adaptive machine learning, natural language processing, and real-world decision systems.
LMU Munich
Hinrich Schuetze is professor and chair of computational linguistics at LMU Munich. His research spans statistical natural language processing, representation learning, lexical semantics, and the analysis of multilingual language models.
Tel Aviv University
Amir Globerson is a professor of computer science and AI at Tel Aviv University. He studies machine learning and natural language processing, including the theory of learned representations, attention, and interpretable reasoning.
University of Oxford
Fazl Barez is a senior researcher at the University of Oxford and leads the TSG Lab. His work connects interpretability, evaluation, model control, and machine unlearning with the technical foundations needed for effective AI governance.
EPFL
Robert West is an associate professor at EPFL, where he leads the Data Science and AI Lab. His work spans AI, natural language processing, and computational social science, including safe AI and structured human–AI collaboration.
Cambridge Boston Alignment Initiative
Emre Yavuz directs programs at the Cambridge Boston Alignment Initiative. He builds research communities and talent pathways for AI safety and biosecurity, connecting researchers through fellowships, training, and cross-institutional collaboration.
Researchers who have joined ICINAi as founding members.