![Caroline Trippel](https://profiles.stanford.edu/proxy/api/cap/profiles/227427/resources/profilephoto/350x350.1571797389329.jpg)
Caroline Trippel
Assistant Professor of Computer Science and of Electrical Engineering
Web page: https://cs.stanford.edu/people/trippel/
Bio
Caroline Trippel is an Assistant Professor in the Computer Science and Electrical Engineering Departments at Stanford University working in the area of computer architecture. Prior to starting at Stanford, Trippel spent nine months as a Research Scientist at Facebook in the FAIR SysML group. Her work focuses on promoting correctness and security as first-order computer systems design metrics (akin to performance and power). A central theme of her work is leveraging formal methods techniques to design and verify hardware systems in order to ensure that they can provide correctness and security guarantees for the applications they intend to support. Additionally, Trippel has been recently exploring the role of architecture in enabling privacy-preserving machine learning, the role of machine learning in hardware systems optimizations, particularly in the context of neural recommendation, and opportunities for improving datacenter and at-scale machine learning reliability.
Trippel's research has influenced the design of the RISC-V ISA memory consistency model both via her formal analysis of its draft specification and her subsequent participation in the RISC-V Memory Model Task Group. Additionally, her work produced a novel methodology and tool that synthesized two new variants of the now-famous Meltdown and Spectre attacks.
Trippel's research has been recognized with IEEE Top Picks distinctions, the 2020 ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Award, and the 2020 CGS/ProQuest® Distinguished Dissertation Award in Mathematics, Physical Sciences, & Engineering. She was also awarded an NVIDIA Graduate Fellowship (2017-2018) and selected to attend the 2018 MIT Rising Stars in EECS Workshop. Trippel completed her PhD in Computer Science at Princeton University and her BS in Computer Engineering at Purdue University.
Academic Appointments
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Assistant Professor, Computer Science
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Assistant Professor, Electrical Engineering
2023-24 Courses
- Computer Systems Architecture
EE 282 (Spr) - Introduction to Automated Reasoning
CS 257 (Aut) -
Independent Studies (11)
- Advanced Reading and Research
CS 499 (Aut, Win, Spr, Sum) - Advanced Reading and Research
CS 499P (Aut, Win, Spr) - Curricular Practical Training
CS 390A (Spr, Sum) - Curricular Practical Training
CS 390B (Sum) - Independent Project
CS 399 (Aut) - Independent Work
CS 199 (Spr) - Independent Work
CS 199P (Aut, Win, Spr) - Senior Project
CS 191 (Win) - Special Studies and Reports in Electrical Engineering
EE 391 (Aut, Win, Spr, Sum) - Special Studies or Projects in Electrical Engineering
EE 390 (Aut, Win, Spr, Sum) - Writing Intensive Senior Research Project
CS 191W (Win)
- Advanced Reading and Research
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Prior Year Courses
2022-23 Courses
- Computer Systems Architecture
EE 282 (Spr) - Introduction to Automated Reasoning
CS 257 (Aut)
2021-22 Courses
- Computer Systems Architecture
EE 282 (Spr) - Formal Methods for Computer Systems
CS 357S (Aut)
2020-21 Courses
- Computer Systems Architecture
EE 282 (Win) - Digital Systems Architecture
EE 180 (Spr) - Formal Methods for Computer Systems
CS 357S (Aut) - Introductory Research Seminar in Electrical Engineering
EE 301 (Aut)
- Computer Systems Architecture
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Saranyu Chattopadhyay, Timothy Chong, Rubens Lacouture, Alex Ozdemir, Athinagoras Skiadopoulos, Nathan Zhang, Mark Zhao -
Doctoral Dissertation Advisor (AC)
Yao Hsiao, Daniel Mendoza, Ioanna Vavelidou -
Orals Evaluator
Jack Humphries, Nathan Zhang -
Master's Program Advisor
Atem Aguer, Mameena Arromdee, Austin Brown, Halle Brown, Olivia Feng, Vyom Garg, Binxu Li, Wen Li, Nicole Mulvey, Michael Nath, Ellie Tanimura, Phuc Tran, Shruti Verma, Kory Yang -
Doctoral Dissertation Reader (NonAC)
Mark Zhao -
Doctoral (Program)
Samantha Archer, Colin Drewes, Yao Hsiao, Nicholas Mosier
All Publications
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RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation
ASSOC COMPUTING MACHINERY. 2022: 344-358
View details for DOI 10.1145/3503222.3507777
View details for Web of Science ID 000810486300025
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Axiomatic Hardware-Software Contracts for Security
ASSOC COMPUTING MACHINERY. 2022: 72-86
View details for DOI 10.1145/3470496.3527412
View details for Web of Science ID 000852702500006
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Opening Pandora's Box: A Systematic Study of New Ways Microarchitecture Can Leak Private Data
IEEE COMPUTER SOC. 2021: 347-360
View details for DOI 10.1109/ISCA52012.2021.00035
View details for Web of Science ID 000702275600026
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Porcupine: A Synthesizing Compiler for Vectorized Homomorphic Encryption
ASSOC COMPUTING MACHINERY. 2021: 375-389
View details for DOI 10.1145/3453483.3454050
View details for Web of Science ID 000723661700024
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TransForm: Formally Specifying Transistency Models and Synthesizing Enhanced Litmus Tests
IEEE COMPUTER SOC. 2020: 874–87
View details for DOI 10.1109/ISCA45697.2020.00076
View details for Web of Science ID 000617734800065