Caroline Trippel

Caroline Trippel is an Assistant Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. Her research focuses on ensuring correctness and security in computer systems through formal methods, with particular emphasis on hardware verification, memory consistency models, and mitigating vulnerabilities like Spectre/Meltdown. She previously worked at Facebook’s FAIR SysML group before joining Stanford.

• Education:
• PhD in Computer Science, Princeton University
• BS in Computer Engineering, Purdue University

Her work has influenced the RISC-V ISA memory consistency model and produced tools like CheckMate, which automatically synthesizes hardware exploits for security verification. She explores privacy-preserving ML, ML-driven hardware optimizations (e.g., neural recommendation), and datacenter reliability. Her research has earned awards including the 2020 ACM SIGARCH Dissertation Award and NVIDIA Fellowship.

Key contributions include:

• Formal analysis of RISC-V memory models
• Exploitation synthesis frameworks (CheckMate)
• Hardware-software contracts for security
• Defenses against microarchitectural side-channel attacks

Current projects include:

• VeriCoder: LLM-enhanced RTL code verification
• Multi-μPATH synthesis for security validation
• Near-data processing (RecSSD) for recommendation systems