Rajeev Alur

Overview

Rajeev Alur is the Zisman Family Professor and Director of the ASSET Center for Trustworthy AI at the University of Pennsylvania. His career spans groundbreaking work in formal methods, cyber-physical systems, and programming languages.

• PhD from Stanford University (1991)
• Bachelor's degree from IIT Kanpur (1987)

Research Interests

His research focuses on ensuring safety and trustworthiness in AI systems, particularly autonomous systems like self-driving cars and medical devices. Key areas include:

• Neurosymbolic integration
• Temporal logic in reinforcement learning
• Verification of neural network controllers
• Trustworthy machine learning
• Extending formal methods to modern AI

Recent Publications

Rajeev's recent work (2023-2025) emphasizes compositional verification, neurosymbolic learning, and secure microservice architectures. Notable trends include:

• Combining formal specifications with deep learning
• Scalable verification techniques for neural networks
• Relational query synthesis
• Application to autonomous systems with neural perception
• Chordal sparsity models for efficient analysis

Scientific Recognition

• Alonzo Church Award (2016)
• Knuth Prize (2024)
• EATCS Award (2025)
• ACM/IEEE Fellow

Advising & Grants

He has advised 30+ PhD students now in academia (Georgia Tech, UCSD, etc.) and industry. As lead PI of the NSF Expeditions project ExCAPE, he drove program synthesis research. Currently serves as General Chair for FLoC 2026.

Labs & Teams

Directs the ASSET Center and collaborates with Penn's PRECISE Center and PL Club. His work integrates with industry verification tools at Amazon, Microsoft, and Google.