Aditya Grover

Aditya Grover is an Assistant Professor in the Department of Computer Science at the University of California, Los Angeles (UCLA), where he conducts research at the intersection of probabilistic machine learning and artificial intelligence.

His research focuses on developing foundational methods for unsupervised representation learning and sequential decision making, with significant contributions to generative AI including multimodal model personalization and in-context learning frameworks. His work bridges theoretical machine learning with practical applications in climate forecasting and conversational AI systems.

Dr. Grover's publications demonstrate expertise in geometric deep learning and efficient generative modeling, with his 2021 NeurIPS paper on manifold-based generative flows representing a key contribution to the field. His research has been featured in leading scientific publications including Nature and Science magazine, highlighting real-world impact in weather prediction and AI response optimization.

His scientific achievements have been recognized through numerous prestigious awards:

• AI2050 Early Career Fellowship (2024)
• Forbes 30 Under 30 - Science (2023)
• Samsung AI Researcher of the Year Award (2022)
• NeurIPS Outstanding Paper Award (2021)
• ACM SIGKDD Doctoral Dissertation Award (2021)
• Gores Award for teaching excellence at Stanford (2020)
• Google-Simons Research Fellowship (2020)
• Centennial Award (2020)
• Lieberman Fellowship (2019-20)

He currently holds the 2023 Amazon Research Award for his project "Personalizing Multimodal Generative Models via In-Context Preference Modeling," which advances the frontier of user-adaptive AI systems. While no student advising information is publicly available, his research collaborations with Amazon and media coverage through 2025 indicate active ongoing research programs.