Tomer Galanti

Assistant Professor, Texas A&M CSE · Deep Learning & LLMs

galanti@tamu.edu · Office: 325 PETR, TAMU

Short bio

Tomer Galanti is an Assistant Professor of Computer Science and Engineering at Texas A&M University. His research studies the foundations of reusable structure: how learning systems discover representations that transfer, recover executable programs from data, and turn repeated reasoning into reliable computation. Prior to joining Texas A&M, he was a postdoctoral associate at MIT's Center for Brains, Minds & Machines with Tomaso Poggio. He spent the summer of 2021 at Google DeepMind and the summer of 2026 at Apple Machine Learning Research (MLR). He received his Ph.D. from Tel Aviv University, advised by Lior Wolf.

Teaching

Special Topics in Recent Developments in Deep Learning and Large Language Models
Texas A&M University, Fall 2024, Fall 2025, Fall 2026

Introduction to Machine Learning
Texas A&M University, Spring 2025, Spring 2026

Statistical Learning Theory and its Applications
Massachusetts Institute of Technology, Fall 2023

Statistical Learning Theory and its Applications
Massachusetts Institute of Technology, Fall 2022

Deep Convolutional Neural Networks
Tel Aviv University, Spring 2020

Deep Convolutional Neural Networks
Tel Aviv University, Spring 2019