Olivia Hsu
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Postdoctoral Researcher Department of Computer Science Stanford University Office: E454 CoDA owhsu [at] stanford [dot] edu Curriculum Vitae |
Update November 3, 2025
I’m thrilled to share that I’ll be joining Carnegie Mellon University as an Assistant Professor in Electrical and Computer Engineering (ECE) and, by courtesy, the Computer Science Department (CSD) starting Summer/Fall 2026.
I’m actively recruiting Ph.D. students this upcoming cycle! Please apply through the CMU ECE or CSD Ph.D. programs and mention my name in your application so it reaches me.
I am a computer science postdoc at Stanford University and an incoming assistant professor at Carnegie Mellon University. Previously, I received my PhD from Stanford University, advised by Professors Kunle Olukotun and Fredrik Kjolstad. I currently work on mapping and compiling sparse applications to domain-specific hardware, architectures, and accelerators. My research interests also broadly include computer architecture, computer and programming systems, compilers, programming models and languages, and digital circuits/VLSI.
I graduated from the University of California, Berkeley in 2019 with a degree in Electrical Engineering and Computer Science (EECS). At Berkeley, I was fortunate enough to be advised by Professor Vladimir Stojanovic and work with Panagiotis Zarkos on novel applications of silicon-photonics.
Publications (Refereed)
Workshops (Non-archival)
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Adaptive Self-improvement LLM Agentic System for ML Library Development Genghan Zhang, Weixin Liang, Olivia Hsu, and Kunle Olukotun to appear in International Conference on Machine Learning (ICML) Workshop on Efficient Systems for Foundation Models (ES-FoMo), July 2025 |
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Adaptive Self-improvement LLM Agentic System for ML Library Development Genghan Zhang, Weixin Liang, Olivia Hsu, and Kunle Olukotun International Conference on Learning Representations (ICLR) Workshop on Reasoning and Planning for LLMs, May 2025 |
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Adaptive Self-improvement LLM Agentic System for ML Library Development Genghan Zhang, Weixin Liang, Olivia Hsu, and Kunle Olukotun Deep Learning for Code (DL4C) Workshop at International Conference on Learning Representations (ICLR), May 2025 Spotlight: Best Paper Award |
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Challenges with Hardware-Software Co-design for Sparse Machine Learning on Streaming Dataflow Rubens Lacouture, Olivia Hsu, Kunle Olukotun, and Fredrik Kjolstad Workshop on Programming Languages and Architecture (PLARCH) co-located with FCRC/ISCA/PLDI 2023, June 2023 |
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Designing a Dataflow Hardware Accelerator with an Abstract Machine Olivia Hsu, Maxwell Strange, Kunle Olukotun, Mark Horowitz, and Fredrik Kjolstad Workshop on Languages, Tools, and Techniques for Accelerator Design (LATTE) co-located with ASPLOS 2023, March 2023 |
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Talks
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Portable Compilation of the Unified IR August 2025 Portal Center Research Retreat | |
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From Language to Silicon: Programming Systems for Sparse Accelerators January to April 2025 University of California, Santa Barbara University of Maryland, College Park Carnegie Mellon University University of Wisconsin-Madison Massachusetts Institute of Technology University of California, Berkeley University of Washington Cornell University and Cornell Tech Princeton University University of Michigan University of Texas at Austin Columbia University |
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AHA Tutorial November 2024 MICRO 2024 | |
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Mapping Sparse Applications to Accelerated Computing Systems June 2024 PLDI 2024: Sparse Workshop |
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Mapping sparse applications to accelerated computing systems April 2024 Carnegie Mellon University (CMU) Systems Design and Implementation (SDI) Seminar | |
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The Sparse Abstract Machine April 2024 Stanford and U-Tokyo Workshop: Agile and low-cost HW design workshop for domain-specific computing era | |
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Architectural and compiler support for accelerating embedding operations on general purpose processors February 2024 Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (MIT CSAIL) | |
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Beyond the Sparse Abstract Machine: Mapping sparse applications to accelerated computing systems December 2023 UC Santa Barbara Computer Science Department Colloquium | |
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The Sparse Abstract Machine June 2023 PLDI 2023: Compilation Techniques for Sparse Tensor Algebra (CTSTA) | |
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Sparse Abstract Machine and Dataflow Hardware November 2022 NVIDIA Tutorial on Sparse Tensor Algebra Compilation | |
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The Sparse Abstract Machine: Sparse Tensor Algebra as Dataflow Graphs October 2022 University of Washington: SAMPL Lunch Talk | |
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The Sparse Abstract Machine: Sparse Tensor Algebra as Dataflow Graphs September 2022 Samsung Semiconductor System Architecture Lab (SAL) | |
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The Sparse Abstract Machine: Sparse Tensor Algebra as Dataflow Graphs August 2022 AHA Agile Hardware Project Retreat | |
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Compilation of Sparse Array Programming Models April 2022 Google Brain: ML compilation seminar | |
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Compilation of Sparse Array Programming Models April 2022 University of California, Santa Cruz: LSD Seminar |
Teaching
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CS 143: Compilers Spring 2023-2024, Stanford University |
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CS 149: Parallel Computing Autumn 2021, Stanford University |
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Afro Fem Coders: Intro to Python Oct 2020-2021, Afro Fem Coders |
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Decal EE 198: Hands-on PCB Engineering Fall 2018, University of California, Berkeley |
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EECS 16A: Designing Information Devices and Systems Fall 2016-2017, University of California, Berkeley |
Press
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Olivia Hsu to give speech at national IEEE-HKN virtual graduation celebration Berkeley EECS News |
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Ph.D. Candidate at Stanford University Named IEEE-HKN Outstanding Student of the Year for 2019 The Bridge |
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Women's History in EECS Berkeley EECS Newsletter |
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Arthur M. Hopkin Award Berkeley EECS |