Stephanie Wang

Hello! I am an assistant professor in computer science at the University of Washington and co-director of the SyFI Lab (Systems for Future Intelligence). If you are interested in distributed systems, systems for machine learning and data processing, programming languages, and/or how these topics fit together, please apply to the Allen School at UW and mention my name in your application.

My research focuses on building flexible, efficient, and large-scale systems for machine learning. Our group builds open-source systems for applications such as LLM training and inference with the goal of maximizing performance for current workloads while also enabling future workloads.

I am an original author of Ray (Ray Core and Ray Data), which has been used to train ChatGPT, serve high-performance LLMs, and break the CloudSort 100TB record. I continue to develop the Ray ecosystem as member of the Ray TSC and as a software engineer at Anyscale, where I am currently working on Ray Direct Transport (RDT), an accelerator-native dataplane in Ray.

smwang@cs.washington.edu  /  CV  /  GitHub  /  Google Scholar  /  LinkedIn

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Publications

DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling


Yi Pan, Yile Gu, Jinbin Luo, Yibo Wu, Ziren Wang, Hongtao Zhang, Ziyi Xu, Shengkai Lin, Baris Kasikci, Stephanie Wang.
MLSys 2026.

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval


Chien-Yu Lin, Keisuke Kamahori, Yiyu Liu, Xiaoxiang Shi, Madhav Kashyap, Yile Gu, Rulin Shao, Zihao Ye, Kan Zhu, Rohan Kadekodi, Stephanie Wang, Arvind Krishnamurthy, Luis Ceze, Baris Kasikci.
MLSys 2026.
paper

Programmable and Adaptive Scheduling for Distributed Systems


Yuyao Wang, Xiangfeng Zhu, Ratul Mahajan, Stephanie Wang.
HotNets 2025.
paper

Piper: Towards Flexible Pipeline Parallelism for PyTorch


Megan Frisella, Arvin Oentoro, Xiangyu Gao, Gilbert Bernstein, Stephanie Wang.
PACMI 2025.
paper

Nanoflow: Towards optimal large language model serving throughput


Kan Zhu, Yilong Zhao, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Yufei Gao, Qinyu Xu, Tian Tang, Zihao Ye, Chien-Yu Lin, Ziren Wang, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci.
OSDI 2025.
paper

FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving


Zihao Ye, Lequn Chen, Ruihang Lai, Wuwei Lin, Yineng Zhang, Stephanie Wang, Tianqi Chen, Baris Kasikci, Vinod Grover, Arvind Krishnamurthy, Luis Ceze.
MLSys 2025.
paper

Towards ML System Extensibility


Weixin Deng, Andy Ruan, Megan Frisella, Kai-Hsun Chen, SangBin Cho, Jack Tigar Humphries, Rui Qiao, Stephanie Wang.
HotOS 2025.
paper

Datacomp-lm: In search of the next generation of training sets for language models


Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar.
NeurIPS 2024.
paper

Logical Memory Pools: Flexible and Local Disaggregated Memory


Emmanuel Amaro, Stephanie Wang, Aurojit Panda, Marcos K. Aguilera.
HotNets 2023.
paper

Exoshuffle: An Extensible Shuffle Architecture


Frank Sifei Luan, Stephanie Wang, Samyukta Yagati, Sean Kim, Kenneth Lien, Isaac Ong, Tony Hong, SangBin Cho, Eric Liang, Ion Stoica.
SIGCOMM 2023.
paper

ExoFlow: A Universal Workflow System for Exactly-Once DAGs


Siyuan Zhuang, Stephanie Wang, Eric Liang, Yi Cheng, Ion Stoica.
OSDI 2023.
paper / talk / slides

ESCHER: Expressive Scheduling with Ephemeral Resources


Romil Bhardwaj, Alexey Tumanov, Stephanie Wang, Richard Liaw, Philipp Moritz, Robert Nishihara, Ion Stoica.
SoCC 2022.
paper

Rearchitecting in-memory object stores for low latency


Danyang Zhuo, Kaiyuan Zhuang, Zhuohan Li, Siyuan Zhuang, Stephanie Wang, Ang Chen, Ion Stoica.
VLDB 2022.
paper

Hoplite: Efficient and Fault-Tolerant Collective Communication for Task-Based Distributed Systems


Siyuan Zhuang, Zhuohan Li, Danyang Zhuo, Stephanie Wang, Eric Liang, Robert Nishihara, Philipp Moritz, Ion Stoica.
SIGCOMM 2021.
paper

In Reference to RPC: It's Time to Add Distributed Memory


Stephanie Wang, Benjamin Hindman, Ion Stoica.
HotOS 2021.
paper / talk / slides

Ownership: A Distributed Futures System for Fine-Grained Tasks


Stephanie Wang, Eric Liang, Edward Oakes, Benjamin Hindman, Frank Sifei Luan, Audrey Cheng, Ion Stoica.
NSDI 2021.
paper / talk / slides / artifact

Practical Volume-Based Attacks on Encrypted Databases


Rishabh Poddar*, Stephanie Wang*, Jianan Lu, Raluca Ada Popa.
EuroS&P 2020.
paper

Lineage Stash: Fault Tolerance Off the Critical Path


Stephanie Wang, John Liagouris, Robert Nishihara, Philipp Moritz, Ujval Misra, Alexey Tumanov, Ion Stoica.
SOSP 2019. Distinguished Artifact Award.
paper / talk / slides / artifact

Ray: A Distributed Framework For Emerging AI Applications


Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I Jordan, Ion Stoica.
OSDI 2018.
paper

Verifying a High-Performance Crash-Safe File System Using a Tree Specification


Haogang Chen, Tej Chajed, Alex Konradi, Stephanie Wang, Atalay İleri, Adam Chlipala, M. Frans Kaashoek, Nickolai Zeldovich.
SOSP 2017.
paper

Real-Time Machine Learning: The Missing Pieces


Robert Nishihara, Philipp Moritz, Stephanie Wang, Alexey Tumanov, William Paul, Johann Schleier-Smith, Richard Liaw, Mehrdad Niknami, Michael I Jordan, Ion Stoica.
HotOS 2017.
paper




Forked from Leonid Keselman.