Henggang Cui
|
Engineering Manager II
Latitude AI
cuihenggang (at) gmail (dot) com
|
|
|
About me
I am an Engineering Manager at Latitude AI.
I got my Ph.D. degree from Carnegie Mellon University, advised by
Greg Ganger.
Thesis
Exploiting Application Characteristics for Efficient System Support for Data-Parallel Machine Learning
[dissertation]
[slides]
Open-sourced Projects
[GeePS]:
GPU-specialized parameter server for GPU machine learning
[MLtuner-GeePS]:
GeePS with automatic tuning on learning rate, momentum, batch size, data staleness and more
[IterStore]:
High-performacne parameter server for iterative convergent machine learning
Publications
PBP: Path-based Trajectory Prediction for Autonomous Driving
[link]
[pdf]
Sepideh Afshar*, Nachiket Deo*, Akshay Bhagat, Titas Chakraborty, Yunming Shao, Balarama Raju Buddharaju, Adwait Deshpande, Henggang Cui
IEEE International Conference on Robotics and Automation (ICRA), 2024
Improving Motion Forecasting for Autonomous Driving with the Cycle Consistency Loss
[link]
[pdf]
Titas Chakraborty, Akshay Bhagat, Henggang Cui
NeurIPS Machine Learning for Autonomous Driving Workshop, 2022
Importance Is in Your Attention: Agent Importance Prediction for Autonomous Driving
[link]
[pdf]
Christopher Hazard, Akshay Bhagat, Balarama Raju Buddharaju, Zhongtao Liu, Yunming Shao, Lu Lu, Sammy Omari, Henggang Cui
CVPR Precognition Workshop, 2022
Ellipse Loss for Scene-Compliant Motion Prediction
[link]
[pdf]
Henggang Cui*, Hoda Shajari*, Sai Yalamanchi, Nemanja Djuric
IEEE International Conference on Robotics and Automation (ICRA), 2021
Uncertainty-Aware Vehicle Orientation Estimation for Joint Detection-Prediction Models
[link]
[pdf]
Henggang Cui, Fang-Chieh Chou, Jake Charland, Carlos Vallespi-Gonzalez, Nemanja Djuric
IEEE International Conference on Intelligent Transportation (ITSC), 2021
MultiXNet: Multiclass Multistage Multimodal Motion Prediction
[link]
Nemanja Djuric, Henggang Cui, Zhaoen Su, Shangxuan Wu, Huahua Wang, Fang-Chieh Chou, Luisa San Martin, Song Feng, Rui Hu, Yang Xu, Alyssa Dayan, Sidney Zhang, Brian C. Becker, Gregory P. Meyer, Carlos Vallespi-Gonzalez, Carl K. Wellington
IEEE Intelligent Transportation Systems (IV), 2021
Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization
[link]
[pdf]
[public impl]
Eason Wang*, Henggang Cui*, Sai Yalamanchi, Mohana Moorthy, Fang-Chieh Chou, Nemanja Djuric
SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
[link]
[pdf]
Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui, Vladan Radosavljevic, Thi Nguyen, Tzu-Kuo Huang, Matthew Niedoba, Jeff Schneider, Nemanja Djuric
IEEE Intelligent Transportation Systems (IV), 2020
Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions
[link]
[pdf]
Henggang Cui, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider, David Bradley, Nemanja Djuric
IEEE International Conference on Robotics and Automation (ICRA), 2020
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
[link]
[pdf]
Nemanja Djuric, Vladan Radosavljevic, Henggang Cui, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider
IEEE Winter Conference on Applications of Computer Vision (WACV), 2020
Improving Movement Prediction of Traffic Actors using Off-road Loss and Bias Mitigation
[link]
[pdf]
Matthew Niedoba, Henggang Cui, Kevin Luo, Darshan Hegde, Fang-Chieh Chou, Nemanja Djuric
NeurIPS Workshop on Machine Learning for Autonomous Driving (NeurIPS ML4AD workshop), 2019
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
[link]
[pdf]
[public impl]
Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou, Tsung-Han Lin, Thi Nguyen, Tzu-Kuo Huang, Jeff Schneider, Nemanja Djuric
IEEE International Conference on Robotics and Automation (ICRA), 2019
MLtuner: System Support for Automatic Machine Learning Tuning
[github]
Henggang Cui, Gregory R. Ganger, and Phillip B. Gibbons
[older PDL TR version] CMU Parallel Data Lab Technical Report 2016
[pdf]
[newer arxiv version] arXiv 1803.07445
[link]
[pdf]
Addressing the Straggler Problem for Iterative Convergent Parallel ML
[link]
Aaron Harlap, Henggang Cui, Wei Dai, Jinliang Wei,
Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
ACM Symposium on Cloud Computing (SoCC), 2016
GeePS: Scalable Deep Learning on Distributed GPUs with a GPU-Specialized Parameter Server
[link]
[pdf]
[github]
Henggang Cui, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, and Eric P. Xing
ACM European Conference on Computer Systems (EuroSys), 2016
Using Data Transformations for Low-latency Time Series Analysis
[link]
[pdf]
[full version]
Henggang Cui, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, and Gregory R. Ganger
ACM Symposium on Cloud Computing (SoCC), 2015
Managed Communication and Consistency for Fast Data-Parallel Iterative Analytics
[link]
Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, Henggang Cui, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
ACM Symposium on Cloud Computing (SoCC), 2015
Best Paper Award
Exploiting Iterative-ness for Parallel ML Computations
[link]
[pdf]
[github]
Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho,
Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
ACM Symposium on Cloud Computing (SoCC), 2014
Exploiting Bounded Staleness to Speed Up Big Data Analytics
[link]
[pdf]
Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee,
Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons,
Garth A. Gibson, and Eric P. Xing
USENIX Annual Technical Conference (ATC), 2014
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
[link]
[pdf]
Qirong Ho, James Cipar, Henggang Cui, Jin Kyu Kim, Seunghak Lee,
Phillip B. Gibbons, Garth A. Gibson, Gregory R. Ganger, and Eric P. Xing
Neural Information Processing Systems (NIPS), 2013
Optically Cross-Braced Hypercube: A Reconfigurable Physical Layer for
Interconnects and Server-Centric Datacenters
[link]
[pdf]
Henggang Cui, Danielle Rasooly, Moises R. N. Ribeiro, and Leonid Kazovsky
Optical Fiber Communication Conference (OFC), 2012
Scalable Data Center Multicast using Multi-class Bloom Filter
[link]
[pdf]
Dan Li, Henggang Cui, Yan Hu, Yong Xia, and Xin Wang
19th IEEE International Conference on Network Protocols (ICNP), 2011
Patents
Motion Prediction for Autonomous Devices
Nemanja Djuric, Henggang Cui, Thi Duong Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider, David McAllister Bradley
US20200272160A1
Object Motion Prediction and Autonomous Vehicle Control
Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider, Henggang Cui, Fang-Chieh Chou, Tzu-Kuo Huang
US20190049970A1
Processing a query using transformed raw data
Henggang Cui, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, Haris Volos
US20170322987A1
Talks
Exploiting Application Characteristics for Efficient System Support of Data-parallel Machine Learning
[slides]
Henggang Cui
CMU Ph.D. Thesis Defense,
Pittsburgh, PA, April 2017
GeePS: Scalable Deep Learning on Distributed GPUs with A GPU-specialized Parameter Server
[slides]
Henggang Cui, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, and Eric P. Xing
ACM European Conference on Computer Systems (EuroSys),
London, UK, April 2016
Using Data Transformations for Low-latency Time Series Analysis
[slides]
Henggang Cui, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, and Gregory R. Ganger
ACM Symposium on Cloud Computing (SoCC),
Kohala Coast, HI, August 2015
Exploiting Iterative-ness for Parallel ML Computations
[slides]
Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho,
Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
ACM Symposium on Cloud Computing (SoCC),
Seattle, WA, November 2014
Exploiting Bounded Staleness to Speed Up Big Data Analytics
[slides]
Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee,
Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons,
Garth A. Gibson, and Eric P. Xing
USENIX Annual Technical Conference (ATC),
Philadelphia, PA, June 2014
LazyTable: Distributed Machine Learning with the Stale Synchronous Parallel Model
[slides]
Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Abhimanu Kumar,
Seunghak Lee, Greg R. Ganger, Phil B. Gibbons, Garth A. Gibson, and Eric P. Xing
WIP Talk, ACM Symposium on Operating Systems Principles (SOSP),
Farmington, PA, November 2013
Public services
Program committee of Conference on Neural Information Processing Systems (NeurIPS) 2024.
Program committee of International Conference on Machine Learning (ICML) 2024.
Program committee of International Conference on Learning Representations (ICLR) 2024.
Program committee of Conference on Neural Information Processing Systems (NeurIPS) 2023.
Program committee of CVPR 2023 "Precognition: Seeing through the Future" Workshop.
Program committee of International Conference on Machine Learning (ICML) 2023.
Program committee of International Conference on Learning Representations (ICLR) 2023.
Program committee of ECCV 2022 "AVVision2022" Workshop.
Program committee of Conference on Neural Information Processing Systems (NeurIPS) 2022.
Program committee of ICML 2022 Workshop on Safe Learning for Autonomous Driving.
Program committee of CVPR 2022 "Precognition: Seeing through the Future" Workshop.
Reviewer of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022.
Program committee of International Conference on Machine Learning (ICML) 2022.
Program committee of International Conference on Learning Representations (ICLR) 2022.
Reviewer of IEEE International Conference on Robotics and Automation (ICRA) 2022.
Program committee of ICCV 2021 "AVVision2021" Workshop.
Reviewer of IEEE Robotics and Automation Letters (RA-L) 2021.
Program committee of Conference on Neural Information Processing Systems (NeurIPS) 2021.
Program committee of IJCAI 2021 "Autonomous Driving" Workshop.
Program committee of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-KDD) 2021.
Program committee of CVPR 2021 "Precognition: Seeing through the Future" Workshop.
Reviewer of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021.
Program committee of International Conference on Machine Learning (ICML) 2021.
Reviewer of IEEE Intelligent Vehicles Symposium (IV) 2021.
Reviewer of IEEE International Conference on Robotics and Automation (ICRA) 2021.
Reviewer of International Conference on Learning Representations (ICLR) 2021.
Program committee of NeurIPS 2020 "Machine Learning for Autonomous Driving" Workshop.
Program committee of The Web Conference (WWW) 2021.
Reviewer of IEEE Robotics and Automation Letters (RAL) 2020.
Program committee of ECCV 2020 "Autonomous Driving" Workshop.
Program committee of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-KDD) 2020.
Program committee of CVPR 2020 "Precognition: Seeing through the Future" Workshop.
Reviewer of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020.
Program committee of International Conference on Machine Learning (ICML) 2020.
Reviewer of IEEE Intelligent Vehicles Symposium (IV) 2020.
Reviewer of Cluster Computing (CC) 2020.
Program committee of The Web Conference (WWW) 2020.
Reviewer of IEEE International Conference on Robotics and Automation (ICRA) 2019.
Reviewer of IEEE Robotics and Automation Letters (RAL) 2019.
Reviewer of IEEE Big Data 2019.
Program committee of NeurIPS 2019 "Machine Learning for Autonomous Driving" Workshop.
Reviewer of Cluster Computing (CC) 2019.
Program committee of CVPR 2019 "Precognition: Seeing through the Future" Workshop.
Reviewer of IEEE Transactions on Network Science and Engineering (TNSE) 2018.
Program committee of ACM Symposium on Cloud Computing (SoCC) 2018.
Program committee of Computing Conference (CC) 2018.
Program committee of ACM Symposium on Cloud Computing (SoCC) 2017.
Teaching
Teaching assistant of Storage Systems (15746/18746), Spring 2015.
[link]
Teaching assistant of Storage Systems (15746/18746), Fall 2016.
[link]
Misc
Henggang Cui at [LinkedIn], [Google Scholar], [Github], [iNaturalist], [eBird].