Aviral Kumar

Aviral Kumar is an Assistant Professor in the School of Computer Science at Carnegie Mellon University (CMU), jointly appointed in the Computer Science Department (CSD) and Machine Learning Department (MLD). He earned his PhD from UC Berkeley in 2023, where he received prestigious awards including the CV Ramamoorthy Distinguished Research Award, Apple PhD Fellowship, and Facebook PhD Fellowship. His research focuses on reinforcement learning (RL), particularly offline RL, scaling RL methods, and their intersection with foundation models. He leads the CMU AI & Reinforcement Learning (AIRe) lab, exploring core RL algorithms, robotics applications, and AI foundation models.

• Education: PhD in Computer Science from UC Berkeley (2023)

Research Interests:

• Reinforcement Learning
• Offline Reinforcement Learning
• Robotics
• Foundation Models

His lab emphasizes scalable RL techniques and real-world applications. Current advisees include Bhavya Kumar Agrawalla and Max Sobol Mark. Notable awards include the CV Ramamoorthy Distinguished Research Award for pioneering contributions to CS research.

Lab activities and future work focus on advancing RL for autonomous systems and integrating foundation models into decision-making frameworks. The lab recruits PhD students annually from CMU SCS programs (CS, ML, RI). Undergraduates and MS students can apply via a dedicated form for research opportunities.