Autonomous Inverted Helicopter Flight via Reinforcement Learning. - Andrew Y. Ng; Adam Coates 002; Mark Diel; Varun Ganapathi; Jamie Schulte; Ben Tse; Eric Berger; Eric Liang (ISER, 2004)

Location-based image retrieval for urban environments. - Jerry Zhang; Aaron Hallquist; Eric Liang; Avideh Zakhor (ICIP, 2011)

Structuring a sharded image retrieval database. - Eric Liang; Avideh Zakhor (Multimedia Content and Mobile Devices, 2013)

Generalized scale independence through incremental precomputation. - Michael Armbrust; Eric Liang; Tim Kraska; Armando Fox; Michael J. Franklin; David A. Patterson 001 (SIGMOD Conference, 2013)

SparkR: Scaling R Programs with Spark. - Shivaram Venkataraman; Zongheng Yang; Davies Liu; Eric Liang; Hossein Falaki; Xiangrui Meng; Reynold Xin; Ali Ghodsi 002; Michael J. Franklin; Ion Stoica; Matei Zaharia (SIGMOD Conference, 2016)

Ray: A Distributed Framework for Emerging AI Applications. - Philipp Moritz; Robert Nishihara; Stephanie Wang; Alexey Tumanov; Richard Liaw; Eric Liang; William Paul; Michael I. Jordan; Ion Stoica (CoRR, 2017)

Ray RLLib: A Composable and Scalable Reinforcement Learning Library. - Eric Liang; Richard Liaw; Robert Nishihara; Philipp Moritz; Roy Fox; Joseph Gonzalez 001; Ken Goldberg; Ion Stoica (CoRR, 2017)

Benchmarks for reinforcement learning in mixed-autonomy traffic. - Eugene Vinitsky; Aboudy Kreidieh; Luc Le Flem; Nishant Kheterpal; Kathy Jang; Cathy Wu 002; Fangyu Wu 003; Richard Liaw; Eric Liang; Alexandre M. Bayen (CoRL, 2018)

RLlib: Abstractions for Distributed Reinforcement Learning. - Eric Liang; Richard Liaw; Robert Nishihara; Philipp Moritz; Roy Fox; Ken Goldberg; Joseph Gonzalez 001; Michael I. Jordan; Ion Stoica (ICML, 2018)

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)

Tune: A Research Platform for Distributed Model Selection and Training. - Richard Liaw; Eric Liang; Robert Nishihara; Philipp Moritz; Joseph E. Gonzalez; Ion Stoica (CoRR, 2018)

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. - Daniel Ho; Eric Liang; Xi Chen 022; Ion Stoica; Pieter Abbeel (ICML, 2019)

Neural packet classification. - Eric Liang; Hang Zhu; Xin Jin 008; Ion Stoica (SIGCOMM, 2019)

Selectivity Estimation with Deep Likelihood Models. - Zongheng Yang; Eric Liang; Amog Kamsetty; Chenggang Wu 001; Yan Duan; Xi Chen 022; Pieter Abbeel; Joseph M. Hellerstein; Sanjay Krishnan; Ion Stoica (CoRR, 2019)

Deep Unsupervised Cardinality Estimation. - Zongheng Yang; Eric Liang; Amog Kamsetty; Chenggang Wu 001; Yan Duan; Xi Chen 022; Pieter Abbeel; Joseph M. Hellerstein; Sanjay Krishnan; Ion Stoica (Proc. VLDB Endow., 2019)

IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks. - Michael Luo; Jiahao Yao; Richard Liaw; Eric Liang; Ion Stoica (ICLR, 2020)

Variable Skipping for Autoregressive Range Density Estimation. - Eric Liang; Zongheng Yang; Ion Stoica; Pieter Abbeel; Yan Duan; Xi Chen 022 (ICML, 2020)

Hoplite: Efficient Collective Communication for Task-Based Distributed Systems. - Siyuan Zhuang; Zhuohan Li 001; Danyang Zhuo; Stephanie Wang; Eric Liang; Robert Nishihara; Philipp Moritz; Ion Stoica (CoRR, 2020)

Distributed Reinforcement Learning is a Dataflow Problem. - Eric Liang; Zhanghao Wu; Michael Luo; Sven Mika; Ion Stoica (CoRR, 2020)

NeuroCard: One Cardinality Estimator for All Tables. - Zongheng Yang; Amog Kamsetty; Sifei Luan 001; Eric Liang; Yan Duan; Xi Chen 022; Ion Stoica (Proc. VLDB Endow., 2020)

RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem. - Eric Liang; Zhanghao Wu; Michael Luo; Sven Mika; Joseph E. Gonzalez; Ion Stoica (NeurIPS, 2021)

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)

Hoplite: efficient and fault-tolerant collective communication for task-based distributed systems. - Siyuan Zhuang; Zhuohan Li 001; Danyang Zhuo; Stephanie Wang; Eric Liang; Robert Nishihara; Philipp Moritz; Ion Stoica (SIGCOMM, 2021)

Scalable Reinforcement Learning Systems and their Applications - Eric Liang (2021)

Exoshuffle: Large-Scale Shuffle at the Application Level. - Frank Sifei Luan; Stephanie Wang; Samyukta Yagati; Sean Kim; Kenneth Lien; SangBin Cho; Eric Liang; Ion Stoica (CoRR, 2022)

Predicting Pedestrian Crosswalk Behavior Using Convolutional Neural Networks. - Eric Liang; Mark Stamp 001 (CoRR, 2022)

ExoFlow: A Universal Workflow System for Exactly-Once DAGs. - Siyuan Zhuang; Stephanie Wang; Eric Liang; Yi Cheng; Ion Stoica (OSDI, 2023)

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)

Exoshuffle-CloudSort. - Frank Sifei Luan; Stephanie Wang; Samyukta Yagati; Sean Kim; Kenneth Lien; Isaac Ong; Tony Hong; SangBin Cho; Eric Liang; Ion Stoica (CoRR, 2023)

The Streaming Batch Model for Efficient and Fault-Tolerant Heterogeneous Execution. - Frank Sifei Luan; Ziming Mao; Ron Yifeng Wang; Charlotte Lin; Amog Kamsetty; Hao Chen; Cheng Su; Balaji Veeramani; Scott Lee; SangBin Cho; Clark Zinzow; Eric Liang; et al. (CoRR, 2025)