Adrian Sampson

Associate Professor, Computer Science

Field Member, Electrical and Computer Engineering

Cornell University

Education

University of Washington
Ph.D., Computer Science and Engineering
2009–2015
Advisors: Luis Ceze and Dan Grossman
Dissertation: Hardware and Software for Approximate Computing

Harvey Mudd College
Bachelor of Science with High Distinction, Computer Science
2005–2009
Advisor: Geoff Kuenning

Conference Publications

“Lightweight, Modular Verification for WebAssembly-to-Native Instruction Selection.” Alexa VanHattum, Monica Pardeshi, Chris Fallin, Adrian Sampson, and Fraser Brown. To appear in ASPLOS 2024.

“Modular Hardware Design with Timeline Types.” Rachit Nigam, Pedro Henrique Azevedo de Amorim, and Adrian Sampson. In PLDI 2023.

“Stepwise Debugging for Hardware Accelerators.” Griffin Berlstein, Rachit Nigam, Chris Gyurgyik, and Adrian Sampson. In ASPLOS 2023.

“Verifying Dynamic Trait Objects in Rust.” Alexa Vanhattum, Daniel Schwartz-Narbonne, Nathan Chong, and Adrian Sampson. In ICSE SEIP 2022.

“Compiler-Driven Simulation of Reconfigurable Hardware Accelerators.” Zhijing Li, Adrian Sampson, Yuwei Ye, and Stephen Neuendorffer. In HPCA 2022.

“Software-Defined Vector Processing on Manycore Fabrics.” Philip Bedoukian, Neil Adit, Edwin Peguero, and Adrian Sampson. In MICRO 2021.

“Reticle: A Virtual Machine for Programming Modern FPGAs.” Luis Vega, Joseph McMahan, Adrian Sampson, Dan Grossman, and Luis Ceze. In PLDI 2021.

“Vectorization for Digital Signal Processors via Equality Saturation.” Alexa VanHattum, Rachit Nigam, Vincent T. Lee, James Bornholt, and Adrian Sampson. In ASPLOS 2021.

“A Compiler Infrastructure for Accelerator Generators.” Samuel Thomas, Rachit Nigam, Zhijing Li, and Adrian Sampson. In ASPLOS 2021.

“Geometry Types for Graphics Programming.” Dietrich Geisler, Irene Yoon, Aditi Kabra, Horace He, Yinnon Sanders, and Adrian Sampson. In OOPSLA 2020.

“A Synthesis-Aided Compiler for DSP Architectures (WiP Paper).” Alexa VanHattum, Rachit Nigam, Vincent T. Lee, James Bornholt, and Adrian Sampson. In LCTES 2020.

“Predictable Accelerator Design with Time-Sensitive Affine Types.” Rachit Nigam, Sachille Atapattu, Samuel Thomas, Zhijing Li, Ted Bauer, Yuwei Yi, Apurva Koti, Adrian Sampson, and Zhiru Zhang. In PLDI 2020.

“EVA²: Exploiting Temporal Redundancy in Live Computer Vision.” Mark Buckler, Philip Bedoukian, Suren Jayasuriya, and Adrian Sampson. In ISCA 2018.

“Programming Language Support for Natural Language Interaction.” Alex Renda, Harrison Goldstein, Sarah Bird, Chris Quirk, and Adrian Sampson. In SysML 2018.

“Static Stages for Heterogeneous Programming.” Adrian Sampson, Kathryn S McKinley, and Todd Mytkowicz. In OOPSLA 2017. Artifact evaluated. Distinguished Artifact Award.

“Reconfiguring the Imaging Pipeline for Computer Vision.” Mark Buckler, Suren Jayasuriya, and Adrian Sampson. In ICCV 2017.

“Let’s Fix OpenGL.” Adrian Sampson. In SNAPL 2017.

“Probability Type Inference for Flexible Approximate Programming.” Brett Boston, Adrian Sampson, Dan Grossman, and Luis Ceze. In OOPSLA 2015.

“Hardware–Software Co-Design: Not Just a Cliché.” Adrian Sampson, James Bornholt, and Luis Ceze. In SNAPL 2015.

“SNNAP: Approximate Computing on Programmable SoCs via Neural Acceleration.” Thierry Moreau, Mark Wyse, Jacob Nelson, Adrian Sampson, Hadi Esmaeilzadeh, Luis Ceze, and Mark Oskin. In HPCA 2015.

“Monitoring and Debugging the Quality of Results in Approximate Programs.” Michael Ringenburg, Adrian Sampson, Isaac Ackerman, Luis Ceze, and Dan Grossman. In ASPLOS 2015.

“Expressing and Verifying Probabilistic Assertions.” Adrian Sampson, Pavel Panchekha, Todd Mytkowicz, Kathryn S McKinley, Dan Grossman, and Luis Ceze. In PLDI 2014. Artifact evaluated.

“Approximate Storage in Solid-State Memories.” Adrian Sampson, Jacob Nelson, Karin Strauss, and Luis Ceze. In MICRO 2013. Expanded version appears in ACM TOCS.

“Neural Acceleration for General-Purpose Approximate Programs.” Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, and Doug Burger. In MICRO 2012. Versions appear in MICRO Top Picks and CACM Research Highlights.

“Automatic Discovery of Performance and Energy Pitfalls in HTML and CSS.” Adrian Sampson, Călin Caşcaval, Luis Ceze, Pablo Montesinos, and Dario Suarez Gracia. In IISWC 2012.

“Architecture Support for Disciplined Approximate Programming.” Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, and Doug Burger. In ASPLOS 2012.

“EnerJ: Approximate Data Types for Safe and General Low-Power Computation.” Adrian Sampson, Werner Dietl, Emily Fortuna, Danushen Gnanapragasam, Luis Ceze, and Dan Grossman. In PLDI 2011.

“Composable Specifications for Structured Shared-Memory Communication.” Benjamin Wood, Adrian Sampson, Luis Ceze, and Dan Grossman. In OOPSLA 2010.

“On-line Distributed Traffic Grooming.” R. Jordan Crouser, Brian Rice, Adrian Sampson, and Ran Libeskind-Hadas. In ICC 2008.

Workshop Publications

“A Toolkit for Designing Hardware DSLs.” Griffin Berlstein, Rachit Nigam, Chris Gyurgyik, and Adrian Sampson. In WOSET 2021 (co-located with ICCAD).

“Online Verification of Commutativity.” Aditi Kabra, Dietrch Geisler, and Adrian Sampson. In TAPAS 2020 (co-located with SPLASH).

“Optimizing JPEG Quantization for Classification Networks.” Zhijing Li, Christopher De Sa, and Adrian Sampson. In ReCoML 2020 (co-located with MLSys).

“LambdaLab: An Interactive λ-Calculus Reducer for Learning.” Daniel Sainati and Adrian Sampson. In SPLASH-E 2018.

“Debugging Probabilistic Programs.” Chandrakana Nandi, Dan Grossman, Adrian Sampson, Todd Mytkowicz, and Kathryn S McKinley. In MAPL 2017 (co-located with PLDI).

“Rethinking the Camera Pipeline for Computer Vision.” Mark Buckler, Suren Jayasuriya, and Adrian Sampson. In WAX 2017 (co-located with ASPLOS).

“The Case for Compulsory Approximation.” Adrian Sampson. In WAX 2016 (co-located with ASPLOS).

“Approximating to the Last Bit.” Thierry Moreau, Adrian Sampson, Luis Ceze, and Mark Oskin. In WAX 2016 (co-located with ASPLOS).

“REACT: A Framework for Rapid Exploration of Approximate Computing Techniques.” Mark Wyse, Andre Baixo, Thierry Moreau, Bill Zorn, James Bornholt, Adrian Sampson, Luis Ceze, and Mark Oskin. In WAX 2015 (co-located with PLDI).

“Two Approximate-Programmability Birds, One Statistical-Inference Stone.” Adrian Sampson. In APPROX 2014 (co-located with PLDI).

“Tuning Approximate Computations with Constraint-Based Type Inference.” Brett Boston, Adrian Sampson, Dan Grossman, and Luis Ceze. In WACAS 2014 (co-located with APLOS).

“Approximate Semantics for Wirelessly Networked Applications.” Benjamin Ransford, Adrian Sampson, and Luis Ceze. In WACAS 2014 (co-located with ASPLOS).

“Profiling and Autotuning for Energy-Aware Approximate Programming.” Michael F. Ringenburg, Adrian Sampson, Luis Ceze, and Dan Grossman. In WACAS 2014 (co-located with ASPLOS).

“Design Tradeoffs of Approximate Analog Neural Accelerators.” Renée St. Amant, Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Arjang Hassibi, and Doug Burger. In NIAC 2013.

“Addressing Dark Silicon Challenges with Disciplined Approximate Computing.” Hadi Esmaeilzadeh, Adrian Sampson, Michael Ringenburg, Dan Grossman, Luis Ceze, and Doug Burger. In DaSi 2012 (co-located with ISCA).

“Towards Neural Acceleration for General-Purpose Approximate Computing.” Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, and Doug Burger. In WEED 2012 (co-located with ISCA).

“Greedy Coherence.” Emily Fortuna, Brandon Lucia, Adrian Sampson, Benjamin Wood, and Luis Ceze. In HPPC 2011 (co-located with MICRO).

Other Publications

“Very Large Scale Disintegration.” Adrian Sampson. In the Wild and Crazy Ideas (WACI) session at ASPLOS 2023.

“Performance Left on the Table: An Evaluation of Compiler Auto-Vectorization for RISC-V.” Neil Adit and Adrian Sampson. In IEEE Micro.

“Exploiting Errors for Efficiency: A Survey from Circuits to Applications.” Phillip Stanley-Marbell, Armin Alaghi, Michael Carbin, Eva Darulova, Lara Dolecek, Andreas Gerstlauer, Ghayoor Gillani, Djordje Jevdjic, Thierry Moreau, Mattia Cacciotti, Alexandros Daglis, Natalie D. Enright Jerger, Babak Falsafi, Sasa Misailovic, Adrian Sampson, and Damien Zufferey. In ACM Computing Surveys 53(3), 2020.

“A Taxonomy of General Purpose Approximate Computing Techniques.” Thierry Moreau, Joshua San Miguel, Mark Wyse, James Bornholt, Armin Alaghi, Luis Ceze, Natalie Enright Jerger, and Adrian Sampson. In IEEE Embedded Systems Letters.

“Approximate Computing: Unlocking Efficiency with Hardware–Software Co-Design.” Luis Ceze and Adrian Sampson. In GetMobile, July 2016.

Hardware and Software for Approximate Computing. Ph.D. dissertation.

“Approximate Computing: Making Mobile Systems More Efficient.” Thierry Moreau, Adrian Sampson, and Luis Ceze. In IEEE Pervasive Computing, April/June 2015.

“ACCEPT: A Programmer-Guided Compiler Framework for Practical Approximate Computing.” Adrian Sampson, André Baixo, Benjamin Ransford, Thierry Moreau, Joshua Yip, Luis Ceze, and Mark Oskin. In Technical report UW-CSE-15-01 1..

“Neural Acceleration for General-Purpose Approximate Programs.” Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, and Doug Burger. In CACM Research Highlights, January 2015. Highlights from the MICRO 2012 paper.

“Approximate Storage in Solid-State Memories.” Adrian Sampson, Jacob Nelson, Karin Strauss, and Luis Ceze. In ACM Transactions on Computer Systems, September 2014. Expanded version of the MICRO 2013 paper.

“EnerJ, the Language of Good-Enough Computing.” Adrian Sampson, Luis Ceze, and Dan Grossman. In IEEE Spectrum, October 2013.

“Dense Approximate Storage in Phase-Change Memory.” Jacob Nelson, Adrian Sampson, and Luis Ceze. In the Ideas & Perspectives session at ASPLOS 2011.

Patents

US20200410352A1: “System and methods for processing spatial data.” Mark Buckler and Adrian Sampson. Filed September 15, 2020.

US10735675B2: “Configurable image processing system and methods for operating a configurable image processing system for multiple applications.” Mark Buckler, Adrian Sampson, and Suren Jayasuriya. Filed April 13, 2018.

US9021313B2: “Priority-assignment interface to enhance approximate computing.” Karin Strauss, Adrian Sampson, and Luis Ceze. Filed November 28, 2012.

US20160063390A1: “Probabilistic Assertions and Verifying Them.” Todd Mytkowicz, Kathryn S. McKinley, and Adrian Sampson. Filed September 3, 2014.

US9412466B2: “Approximate multi-level cell memory operations.” Karin Strauss, Doug Burger, Luis Ceze, and Adrian Sampson. Filed September 25, 2014.

US8510237B2: “Machine learning method to identify independent tasks for parallel layout in web browsers.” Călin Caşcaval, Adrian Sampson, and Bin Wang. Filed July 13, 2011.

Invited Talks

October 16, 2023: “The Next 700 Accelerator Design Languages.” UIUC Compiler Seminar.

October 1, 2022: “I Survived Tenure, and So Can You!” JOBS workshop at MICRO 2022.

December 9, 2021: “The Next 700 Accelerator Design Languages.” Berkeley Programming Systems Seminar.

October 21, 2021: “Languages & Compilers for Hardware Acceleration.” Sydney System Research Talk Series.

September 27, 2021: “The Next 700 Accelerator Design Languages.” Cornell Computer Science Colloquium.

September 2, 2021: “Toward a Predictable System Stack for Accelerator Design.” Stanford Agile Hardware Center.

July 27, 2021: “Calyx: Your DSL-to-Hardware Compiler Construction Kit.” Schloss Dagstuhl, Seminar 21302: Approximate Systems.

April 13, 2021: “Demystifying Grad School” panel moderator. Young Architect Workshop (YArch) 2021. Video.

December 1, 2020: “Toward a Predictable System Stack for Reconfigurable Computing.” University of California, Santa Cruz Hardware Systems Collective Seminar. Video.

November 18, 2020: “Graphics Programming Needs You.” University of Rochester, CSC 572/292. Slides.

October 26, 2020: “Toward a Predictable System Stack for Reconfigurable Computing.” HLD Reading Group, Intel.

October 2, 2020: “Languages and Compilers for Accelerator Design.” University of Massachusetts Amherst. Video.

June 17, 2020: “Ask Me Anything” with Margaret Martonosi. PLDI 2020. Video.

May 31, 2020: “Predictable Accelerator Design.” CHIPKIT Tutorial on Agile Research Test Chips at ISCA 2020. Video.

May 22, 2020: “Accelerator Design Languages.” University of Wisconsin–Madison, Computer Sciences Department. Video.

February 28, 2020: “Predictable Accelerator Design.” UCLA Center for Domain-Specific Computing.

February 3, 2020: “Reconfigurability Through a Language Lens.” Facebook Boston.

August 9, 2019: Panel: How to Apply to Graduate School. Cornell, Maryland, Max Planck Pre-Doctoral Research School 2019.

August 6, 2019: “Designing Programming Languages for Heterogeneous Hardware.” Cornell, Maryland, Max Planck Pre-Doctoral Research School 2019.

June 23, 2019: Panel: Charting Your Path. Programming Languages Mentoring Workshop at PLDI 2019.

June 23, 2019: “Designing Languages for Designing Hardware.” Programming Languages Mentoring Workshop at PLDI 2019. Slides. Video.

June 22, 2019: “FPGAs Have the Wrong Abstraction.” Open mic night at FCRC 2019. Slides. Notes.

April 5, 2019: “Designing Custom Hardware Accelerators with Types.” Colloquium, Department of Computer Science, Williams College.

February 14, 2019: “Designing Systems with Types.” Colloquium, School of Arts, Media + Engineering, Arizona State University. Video.

October 14, 2017: “Approximate Computing Is Dead; Long Live Approximate Computing.” Workshop on Negative Outcomes, Post-Mortems, and Experiences (NOPE), at MICRO 2017. Notes.

December 1, 2015: “Probabilistic Programming.” Schloss Dagstuhl, Seminar 15491: Approximate and Probabilistic Computing: Design, Coding, Verification. Notes.

Research Positions

Associate Professor
Cornell University — Department of Computer Science
2022–

Visiting Researcher
Google — SystemsResearch@Google (SRG)
2022–2023

Assistant Professor
Cornell University — Department of Computer Science
2016–2022

Visiting Researcher
Microsoft Research — Research in Software Engineering (RiSE)
2015–2016

Research Intern
Microsoft Research — Research in Software Engineering (RiSE)
2013

Research Intern
Microsoft Research — Extreme Computing Group (XCG)
2012

Research Intern
Qualcomm, Inc. — Bay Area R&D
2010

Graduate Researcher
University of Washington
2009–2015

Undergraduate Researcher
Harvey Mudd College — NSF REU Program
2007

Honors

Distinguished Artifact Award, ASPLOS 2024

Distinguished Artifact Award, ASPLOS 2023

Google Research Scholar Program award, 2022

IEEE TCCA Young Computer Architect Award, 2021

NSF CAREER award, 2019

Cornell College of Engineering Ralph S. Watts ’72 Excellence in Teaching Award, 2018

Distinguished Artifact Award, OOPSLA 2017

Google Faculty Research Award, 2016

UW CSE William Chan Memorial Dissertation Award, 2015

Best presentation, first UW Computer Science & Engineering Symposium (CSES 2015)

Paper from MICRO 2013 invited for fast-track inclusion in ACM TOCS

Paper from MICRO 2012 selected for CACM research highlights

Google Ph.D. Fellowship in Computer Architecture (2013–2015)

Qualcomm Innovation Fellowship (2013–2014)

Paper from MICRO 2012 selected for IEEE Micro’s Top Picks from the Computer Architecture Conferences, 2013

Best lightning session presentation, MICRO 2012

Facebook Ph.D. Fellowship (2012–2013)

University of Washington Hacherl Graduate Fellowship in Computer Science and Engineering (2009–2010)

Hertz Foundation Fellowship Finalist (2009)

Harvey Mudd College (2009):

Students

Ph.D.

Ayaka Yorihiro, 2023–

Susan Garry, 2023–

Benjamin Carleton, 2023–

Priya Srikumar, 2023

Anshuman Mohan, 2022–

Oliver Daids, 2021–

Griffin Berlstein, 2021–

Zhijing Li, 2019–2021

Sachille Atapattu, 2018–2021

Neil Adit, 2018–

Alexa VanHattum, 2018–2023
Dissertation: Lightweight Formal Methods for Correct, Efficient Systems Programming.
Now at Wellesley College.

Rachit Nigam, 2018–

Dietrich Geisler, 2018–

Edwin Peguero, 2018–2021

Drew Zagieboylo, 2017

Philip Bedoukian, 2017–2023
Dissertation: Logical Accelerators on Manycore Processors.

Mark Buckler, 2016–2019
Dissertation: Holistic Optimization of Embedded Computer Vision Systems.
Now at Amazon.

Master of Engineering

Stephen Verderame, 2023–

Justin Ngai, 2023

David Chen, 2022–2023

Yunhe Shao, 2021–2022

Michael Xiong, 2021–2022

Alaia Solko-Breslin, 2021–2022

Kenneth Li, 2021

Evan Adler, 2020

Henry Liu, 2019–2020

James Chen, 2019

Eric Mei, 2019

Alex Wong, 2019

Arthur Wang, 2018

Shiyu Wang, 2018

Evan Su, 2018

Daniel Sainati, 2018

Eric Lin, 2017

Mingyang Li, 2017

Taehoon Lee, 2017

Moshe Klebanov, 2017

Richie Henwood, 2017

Master of Science

John Rubio, 2022–

Jonathan Tran, 2020–

Ted Bauer, 2020

Undergraduate

Elias Castro, 2023–

Kaden Lei, 2023–

Basant Khalil, 2023

Ethan Gabizon, 2023–

Edmund Lam, 2023–

Susan Garry, 2022–2023

Nathaniel Navarro, 2022–

Meredith Hu, 2022–

Mateo Guynn, 2022–

Caleb Kim, 2022–

Evan Williams, 2022

Jan-Paul Vincent, 2022

Pai Li, 2022–

Crystal Hu, 2022

Mia Daniels, 2022–

Haoxuan Chen, 2021

Boao (Mark) Dong, 2021

Richard Wang, 2021

David Siher, 2021–2022

Jasper Liang, 2021–2022

YoungSeok (Alex) Na, 2021–2022

Andrii Iermolaiev, 2021

Alma Thaler, 2021

Andrei Shpilenok, 2021

Iain Pile, 2021

Karen Zhang, 2020–2021

Chris Gyurgyik, 2020–2021

YooNa Chang, 2020–2021

Akshat Singh, 2020

Paul Joo, 2020–2021

Yuyi He, 2020

Kofi Efah, 2020

Michelle Chao, 2020

Andrew Pareles, 2020

Evan Adler, 2020

Jacob Delgado-López, 2020
University of Puerto Rico

Maya Ifekauche, 2020
Auburn University

Patrick LaFontaine, 2020–2021

Yasmin Sarita, 2020

Katy Voor, 2019–2020

Palini Ramnarayan, 2019–2020

Kimberly Baum, 2019–2020

Edan Mobed, 2019

Yuwei (Vivi) Ye, 2019–2021

Ben Gillott, 2019–2020

Samuel Thomas, 2019–2021

Apurva Koti, 2019–2020

Kenneth Fang, 2019–2020

Horace He, 2018–2020
Honorable mention, 2020 CRA Outstanding Undergraduate Researcher Awards

Yinnon Sanders, 2018–2019

Aditi Kabra, 2018–2019

Jenna Choi, 2018–2019

Ted Bauer, 2018–2019

Euisun (Irene) Yoon, 2018–2019
Honorable mention, 2019 CRA Outstanding Undergraduate Researcher Awards

Joshua Diaz, 2017–2018

Tyler Etzel, 2017–2018

Alex Renda, 2017–2018

Yiteng Guo, 2017–2018

Harry Goldstein, 2017–2018

Omar Abdelaziz, 2016–2017

Chirag Bharadwaj, 2016–2017

Undergraduate Researchers at UW

I worked with these B.S. students while I was a graduate student at the University of Washington.

Joshua Yip, 2014

Luyi Liu, 2014

Chengfeng Shi, 2014

Brett Boston, 2013–2015
B.S. Honors Thesis Runner-up, 2015 CRA Outstanding Undergraduate Researcher Awards
Winner, 2015 UW CSE Undergraduate Honors Thesis Award

Wenjie (Marissa) He, 2013–2015

Finn Parnell, 2011–2012
B.S. Honors Thesis

Danushen Gnanapragasam, 2010–2011

Teaching

Cornell University:

Teaching Assistant, University of Washington:

Tutor, University of Washington, 2009–2014: CSE 303 (Software Development), 311/312 (Foundations of Computing), 322 (Formal Models), 331 (Software Engineering), 332 (Data Structures), 351 (The Hardware/Software Interface)

Service

NSF panel member, CCF division (2023)

ACM SIGARCH Board of Directors (July 1, 2023–June 30, 2025)

ASPLOS 2023: Poster Session Chair

NSF panel member (twice in 2022)

ISCA 2022: Social Media Chair

SIGPLAN Information Director and PL Perspectives co-editor, 2021–

ASPLOS 2022: WACI chair

SIGPLAN Long-Term Mentoring Committee (SIGPLAN-M) Operations Team, 2020–2021

Judge, JOBS workshop at MICRO 2020

NSF panel member, CCF division (2020)

ISCA 2021: Publicity & Social Media Chair

PLMW @ PLDI 2020: Co-organizer

ASPLOS 2020: WACI co-chair

August 2019: Facilitator, JUMP e-workshop on domain-specific languages

ISCA 2019: Social Media Chair

PLDI 2018: Publicity Chair

ACM SIGARCH Social Media Editor (2017–)

PLDI 2017: Publicity Co-Chair

ISCA 2017: Registration Chair

CGO 2017: Workshops/Tutorials Chair

NSF panel member, CCF division (2016)

Cornell University, Computing and Information Science:

Cornell University, Computer Science:

Cornell University:

University of Washington, Computer Science and Engineering:

Review Committees

ASPLOS 2025: Program committee co-chair

ISCA 2024: Program committee member

ASPLOS 2024: Program committee vice chair

YArch 2023: Program committee member

ASPLOS 2023: Program committee member

YArch 2022: Program committee member

ICCD 2021: Special session reviewer

ASPLOS 2022: Program committee member

HPCA 2022: External review committee member

OOPSLA 2021: External review committee member

LATTE 2021: Organizer

YArch 2021: Program committee member

ISCA 2021: Program committee member

IEEE Micro Top Picks 2021: Selection committee member

ASPLOS 2021: Program committee member

MICRO 2020: External review committee member

YArch 2020: Program committee member

OOPSLA 2020: Review committee member

ISCA 2020: External review committee member

PLDI 2020: Program committee member

ASPLOS 2020: Program committee member

ISCA 2019: Program committee member

YArch 2019: Program committee member

ASPLOS 2019: Program committee member

MICRO 2018: Program committee member

WAX 2018: Organizer

SELSE 2018: Program committee member

ISCA 2018: Program committee member

OOPSLA 2018: Program committee member

HPCA 2018: External review committee member

ASPLOS 2018: External review committee member

WAX 2017: Organizer, program committee member

MICRO 2017: External review committee member

Onward! 2017: Program committee member

ISCA 2017: Program committee member

ASPLOS 2017: Program committee member

CGO 2017: Program committee member

MASS 2016: Program committee member

TinyToCS Vol. 4: Program committee member

WAX 2016: Organizer, program committee member

SELSE 2016: Review committee member

ISCA 2016: External review committee member

PLDI 2016: Program committee member

WAX 2015: Organizer, program committee member

WACAS 2014: Organizer, program committee member

PLDI 2014: Artifact evaluation committee member

OOPSLA 2014: Artifact evaluation committee member

Ph.D. Committees

Nitika Saran. Advisor: Hakim Weatherspoon.

Matt Hofmann. Advisor: Zhiru Zhang.

Niansong Zhang. Advisor: Zhiru Zhang.

Suraaj Sureshkannan. Advisor: Andrew Myers.

Hongzheng Chen. Advisor: Zhiru Zhang.

Noam Zilberstein. Advisor: Alexandra Silva.

Jiajie Li. Advisor: Zhiru Zhang.

Drew Zagieboylo. Advisor: Andrew Myers. Defended 2023.

Nicolai Oswald, University of Edinburgh. Advisor: Vijay Nagarajan. Defended 2023.

Derin Ozturk. Advisor: Elizabeth Farrell Helbling.

Zachary Susag. Advisor: Justin Hsu.

Karuna Grewal. Advisor: Justin Hsu.

Victor Giannakouris. Advisor: Immanuel Trummer.

Shubham Chaudhary. Advisor: Robbert Van Renesse and Lorenzo Alvisi.

Jiajie Li. Advisor: Zhiru Zhang.

Yueying (Lisa) Li. Advisor: Christina Delimitrou and Ed Suh.

Andrew Butt. Advisor: Zhiru Zhang.

Abhishek Vijaya Kumar. Advisor: Rachee Singh.

Qizhe Cai. Advisor: Rachit Agarwal.

Nicholas Cebry. Advisor: Chris Batten.

Preslav Ivanov. Advisor: Chris Batten.

Wen-Ding Li. Advisor: Dexter Kozen.

Mark Moeller. Advisor: Nate Foster and Alexandra Silva.

Michael Roberts. Advisor: Dexter Kozen. Defended 2022.

Luis Vega, University of Washington. Advisor: Luis Ceze and Dan Grossman. Defended 2022.

Socrates Wong. Advisor: José Martínez.

Ariel Kellison. Advisor: David Bindel.

Shaojie Xiang. Advisor: Zhiru Zhang.

Yanghui Ou. Advisor: Chris Batten.

A.F. Cooper. Advisor: Chris De Sa.

Kevin Negy. Advisor: Emin Gün Sirer.

Peitian Pan. Advisor: Chris Batten.

Yi Jiang. Advisor: José Martínez.

Yuwei Hu. Advisor: Zhiru Zhang.

Lin Cheng. Advisor: Chris Batten. Defended 2022.

Tuan Ta. Advisor: Chris Batten.

Yuan Zhou. Advisor: Zhiru Zhang. Defended 2021.

Maofan (Ted) Yin. Advisor: Emin Gün Sirer. Defended 2021.

Wil Thomason. Advisor: Hadas Kress-Gazit. Defended 2021.

Yi-Hsiang (Sean) Lai. Advisor: Zhiru Zhang. Defended 2021.

Gai Liu. Advisor: Zhiru Zhang. Defended 2018.

Melanie Kambadur, Columbia University. Advisor: Martha Kim. Defended 2016.