Awni Altabaa
Kline Tower, Office 1117
219 Prospect St
New Haven, CT 06511
Hi! Welcome to my homepage.
My name is Awni. I am a PhD student in the Department of Statistics & Data Science at Yale University studying the foundations of machine learning. My wonderful advisor is Prof. John Lafferty.
My research interests lie broadly in the intersection of machine learning, statistics, and computer science. More specifically, my research aims to study questions of the following flavor:
- What are the architectural mechanisms and inductive biases necessary for efficient learning and strong generalization in different domains?
- What are the fundamental theoretical limits of what is or is not possible to learn under different learning paradigms?
- To what degree can neural networks learn functions and algorithms that can generalize compositionally to out-of-distribution inputs?
Our work tackles these questions through complementary empirical investigation and theoretical analysis. My current research focus is on algorithmic generalization and reasoning in machine learning models.
selected publications
- The Relational Bottleneck as an Inductive Bias for Efficient AbstractionTrends in Cognitive Science (TICS), 2024
- Decentralized Multi-Agent Reinforcement Learning for Continuous-Space Stochastic Games2023 IEEE American Control Conference (ACC), Mar 2023