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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>Henggang Cui</title>
<link rel="stylesheet" type="text/css" href="./style.css">
<script>window["_GOOG_TRANS_EXT_VER"] = "1";</script></head>
<body>
<h1>Henggang Cui</h1>
<table cellspacing="5">
<tbody><tr>
<td>
<img src="./archive/photo/hcui.jpg" alt="Picture of Henggang Cui" width="228" height="228" />
</td>
<td>
<b>Engineering Manager II</b><br>
Latitude AI<br>
cuihenggang (at) gmail (dot) com <br>
<br>
<br>
</td>
<td>
</td>
<td>
<!--
<b>Office:</b><br>
No office any more<br>
<br>
-->
<!--
<b>Email:</b><br>
cuihenggang (at) gmail (dot) com <br>
-->
</td>
</tr>
<tr>
</tr>
</tbody></table>
<hr>
<h2> About me </h2>
<p>
I am an Engineering Manager at Latitude AI.
</p>
<p>
I got my Ph.D. degree from Carnegie Mellon University, advised by
<a href="http://www.ece.cmu.edu/~ganger/">Greg Ganger</a>.
</p>
<h2>Thesis</h2>
<span style="font-weight: bold;">
Exploiting Application Characteristics for Efficient System Support for Data-Parallel Machine Learning
[<a href="./archive/thesis/cui-thesis-dissertation.pdf">dissertation</a>]
[<a href="./archive/talk/cui-thesis-defense.pdf">slides</a>]
</span><br>
<h2>Open-sourced Projects</h2>
[<a href="https://github.com/cuihenggang/geeps">GeePS</a>]:
GPU-specialized parameter server for GPU machine learning
<br>
<br>
[<a href="https://github.com/cuihenggang/mltuner-geeps">MLtuner-GeePS</a>]:
GeePS with automatic tuning on learning rate, momentum, batch size, data staleness and more
<br>
<br>
[<a href="https://github.com/cuihenggang/iterstore">IterStore</a>]:
High-performacne parameter server for iterative convergent machine learning
<br>
<h2>Publications</h2>
<span style="font-weight: bold;">
<span style="font-weight: bold;">
PBP: Path-based Trajectory Prediction for Autonomous Driving
[<a href="https://arxiv.org/abs/2309.03750">link</a>]
[<a href="./archive/paper/[icra24]pbp.pdf">pdf</a>]
</span><br>
Sepideh Afshar*, Nachiket Deo*, Akshay Bhagat, Titas Chakraborty, Yunming Shao, Balarama Raju Buddharaju, Adwait Deshpande, <b>Henggang Cui</b>
<br>
<i>IEEE International Conference on Robotics and Automation (ICRA), 2024</i>
<br>
<br>
<span style="font-weight: bold;">
Improving Motion Forecasting for Autonomous Driving with the Cycle Consistency Loss
[<a href="https://arxiv.org/abs/2211.00149">link</a>]
[<a href="./archive/paper/[neurips22-ml4ad]cycle_loss.pdf">pdf</a>]
</span><br>
Titas Chakraborty, Akshay Bhagat, <b>Henggang Cui</b>
<br>
<i>NeurIPS Machine Learning for Autonomous Driving Workshop, 2022</i>
<br>
<br>
<span style="font-weight: bold;">
Importance Is in Your Attention: Agent Importance Prediction for Autonomous Driving
[<a href="https://arxiv.org/abs/2204.09121">link</a>]
[<a href="./archive/paper/[cvpr22-precognition]importance.pdf">pdf</a>]
</span><br>
Christopher Hazard, Akshay Bhagat, Balarama Raju Buddharaju, Zhongtao Liu, Yunming Shao, Lu Lu, Sammy Omari, <b>Henggang Cui</b>
<br>
<i>CVPR Precognition Workshop, 2022</i>
<br>
<br>
<span style="font-weight: bold;">
Ellipse Loss for Scene-Compliant Motion Prediction
[<a href="https://arxiv.org/abs/2011.03139">link</a>]
[<a href="./archive/paper/[icra21]ellipse_loss.pdf">pdf</a>]
</span><br>
<b>Henggang Cui*</b>, Hoda Shajari*, Sai Yalamanchi, Nemanja Djuric
<br>
<i>IEEE International Conference on Robotics and Automation (ICRA), 2021</i>
<br>
<br>
<span style="font-weight: bold;">
Uncertainty-Aware Vehicle Orientation Estimation for Joint Detection-Prediction Models
[<a href="https://arxiv.org/abs/2011.03114">link</a>]
[<a href="./archive/paper/[itsc21]flip_aware.pdf">pdf</a>]
</span><br>
<b>Henggang Cui</b>, Fang-Chieh Chou, Jake Charland, Carlos Vallespi-Gonzalez, Nemanja Djuric
<br>
<i>IEEE International Conference on Intelligent Transportation (ITSC), 2021</i>
<br>
<br>
<span style="font-weight: bold;">
MultiXNet: Multiclass Multistage Multimodal Motion Prediction
[<a href="https://arxiv.org/abs/2006.02000">link</a>]
</span><br>
Nemanja Djuric, <b>Henggang Cui</b>, 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
<br>
<i>IEEE Intelligent Transportation Systems (IV), 2021</i>
<br>
<br>
<span style="font-weight: bold;">
Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization
[<a href="https://arxiv.org/abs/2004.06247">link</a>]
[<a href="./archive/paper/[kdd20]dp_gan.pdf">pdf</a>]
[<a href="https://github.com/d-eremeev/SC-GAN">public impl</a>]
</span><br>
Eason Wang*, <b>Henggang Cui*</b>, Sai Yalamanchi, Mohana Moorthy, Fang-Chieh Chou, Nemanja Djuric
<br>
<i>SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020</i>
<br>
<br>
<span style="font-weight: bold;">
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
[<a href="https://arxiv.org/abs/1906.08469">link</a>]
[<a href="./archive/paper/[iv20]dp_vru.pdf">pdf</a>]
</span><br>
Fang-Chieh Chou, Tsung-Han Lin, <b>Henggang Cui</b>, Vladan Radosavljevic, Thi Nguyen, Tzu-Kuo Huang, Matthew Niedoba, Jeff Schneider, Nemanja Djuric
<br>
<i>IEEE Intelligent Transportation Systems (IV), 2020</i>
<br>
<br>
<span style="font-weight: bold;">
Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions
[<a href="https://arxiv.org/abs/1908.00219">link</a>]
[<a href="./archive/paper/[icra20]dp_kinematic.pdf">pdf</a>]
</span><br>
<b>Henggang Cui</b>, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider, David Bradley, Nemanja Djuric
<br>
<i>IEEE International Conference on Robotics and Automation (ICRA), 2020</i>
<br>
<br>
<span style="font-weight: bold;">
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
[<a href="https://arxiv.org/abs/1808.05819">link</a>]
[<a href="./archive/paper/[wacv20]dp_original.pdf">pdf</a>]
</span><br>
Nemanja Djuric, Vladan Radosavljevic, <b>Henggang Cui</b>, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider
<br>
<i>IEEE Winter Conference on Applications of Computer Vision (WACV), 2020</i>
<br>
<br>
<span style="font-weight: bold;">
Improving Movement Prediction of Traffic Actors using Off-road Loss and Bias Mitigation
[<a href="https://ml4ad.github.io/#papers">link</a>]
[<a href="./archive/paper/[neurips19-ml4ad]dp_offroad.pdf">pdf</a>]
</span><br>
Matthew Niedoba, <b>Henggang Cui</b>, Kevin Luo, Darshan Hegde, Fang-Chieh Chou, Nemanja Djuric
<br>
<i>NeurIPS Workshop on Machine Learning for Autonomous Driving (NeurIPS ML4AD workshop), 2019</i>
<br>
<br>
<span style="font-weight: bold;">
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
[<a href="https://arxiv.org/abs/1809.10732">link</a>]
[<a href="./archive/paper/[icra19]dp_multimodal.pdf">pdf</a>]
[<a href="https://github.com/nutonomy/nuscenes-devkit/blob/master/python-sdk/nuscenes/prediction/models/mtp.py">public impl</a>]
</span><br>
<b>Henggang Cui</b>, Vladan Radosavljevic, Fang-Chieh Chou, Tsung-Han Lin, Thi Nguyen, Tzu-Kuo Huang, Jeff Schneider, Nemanja Djuric
<br>
<i>IEEE International Conference on Robotics and Automation (ICRA), 2019</i>
<br>
<br>
<span style="font-weight: bold;">
MLtuner: System Support for Automatic Machine Learning Tuning
[<a href="https://github.com/cuihenggang/mltuner-geeps">github</a>]
</span><br>
<b>Henggang Cui</b>, Gregory R. Ganger, and Phillip B. Gibbons
<br>
<i>[older PDL TR version] CMU Parallel Data Lab Technical Report 2016</i>
[<a href="./archive/paper/[pdl-tr16]mltuner.pdf">pdf</a>]
<br>
<i>[newer arxiv version] arXiv 1803.07445</i>
[<a href="https://arxiv.org/abs/1803.07445">link</a>]
[<a href="./archive/paper/[arxiv]mltuner.pdf">pdf</a>]
<br>
<br>
<span style="font-weight: bold;">
Addressing the Straggler Problem for Iterative Convergent Parallel ML
[<a href="http://acmsocc.github.io/2016/schedule.html">link</a>]
</span><br>
Aaron Harlap, <b>Henggang Cui</b>, Wei Dai, Jinliang Wei,
Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
<br>
<i>ACM Symposium on Cloud Computing (SoCC), 2016</i>
<br>
<br>
<span style="font-weight: bold;">
GeePS: Scalable Deep Learning on Distributed GPUs with a GPU-Specialized Parameter Server
[<a href="http://eurosys16.doc.ic.ac.uk/program/program/">link</a>]
[<a href="./archive/paper/[eurosys16]geeps.pdf">pdf</a>]
[<a href="https://github.com/cuihenggang/geeps">github</a>]
</span><br>
<b>Henggang Cui</b>, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, and Eric P. Xing
<br>
<i>ACM European Conference on Computer Systems (EuroSys), 2016</i>
<br>
<br>
<span style="font-weight: bold;">
Using Data Transformations for Low-latency Time Series Analysis
[<a href="http://acmsocc.github.io/2015/schedule.html">link</a>]
[<a href="./archive/paper/[socc15]aperture.pdf">pdf</a>]
[<a href="./archive/report/timeseries.pdf">full version</a>]
</span><br>
<b>Henggang Cui</b>, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, and Gregory R. Ganger
<br>
<i>ACM Symposium on Cloud Computing (SoCC), 2015</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
Managed Communication and Consistency for Fast Data-Parallel Iterative Analytics
[<a href="http://acmsocc.github.io/2015/schedule.html">link</a>]
</span><br>
Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, <b>Henggang Cui</b>, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, and Eric P. Xing
<br>
<i>ACM Symposium on Cloud Computing (SoCC), 2015</i>
<br>
<i>Best Paper Award</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
Exploiting Iterative-ness for Parallel ML Computations
[<a href="https://sites.google.com/site/2014socc/home/program">link</a>]
[<a href="./archive/paper/[socc14]iterstore.pdf">pdf</a>]
[<a href="https://github.com/cuihenggang/iterstore">github</a>]
</span><br>
<b>Henggang Cui</b>, 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
<br>
<i>ACM Symposium on Cloud Computing (SoCC), 2014</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
Exploiting Bounded Staleness to Speed Up Big Data Analytics
[<a href="https://www.usenix.org/conference/atc14/technical-sessions/presentation/cui">link</a>]
[<a href="./archive/paper/[atc14]lazytable.pdf">pdf</a>]
</span><br>
<b>Henggang Cui</b>, 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
<br>
<i>USENIX Annual Technical Conference (ATC), 2014</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server
[<a href="http://papers.nips.cc/paper/4894-more-effective-distributed-ml-via-a-stale-synchronous-parallel-parameter-server">link</a>]
[<a href="./archive/paper/[nips13]ssp.pdf">pdf</a>]
</span><br>
Qirong Ho, James Cipar, <b>Henggang Cui</b>, Jin Kyu Kim, Seunghak Lee,
Phillip B. Gibbons, Garth A. Gibson, Gregory R. Ganger, and Eric P. Xing
<br>
<i>Neural Information Processing Systems (NIPS), 2013</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
Optically Cross-Braced Hypercube: A Reconfigurable Physical Layer for
Interconnects and Server-Centric Datacenters
[<a href="http://www.opticsinfobase.org/abstract.cfm?uri=OFC-2012-OW3J.1">link</a>]
[<a href="./archive/paper/[ofc12]hypercube.pdf">pdf</a>]
</span><br>
<b>Henggang Cui</b>, Danielle Rasooly, Moises R. N. Ribeiro, and Leonid Kazovsky
<br>
<i>Optical Fiber Communication Conference (OFC), 2012</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
Scalable Data Center Multicast using Multi-class Bloom Filter
[<a href="http://www.cs.utah.edu/~mprobst/ICNP2011/program.html">link</a>]
[<a href="./archive/paper/[icnp11]mbf.pdf">pdf</a>]
</span><br>
Dan Li, <b>Henggang Cui</b>, Yan Hu, Yong Xia, and Xin Wang
<br>
<i>19th IEEE International Conference on Network Protocols (ICNP), 2011</i>
<br>
<h2>Patents</h2>
<span style="font-weight: bold;">
Motion Prediction for Autonomous Devices
</span><br>
Nemanja Djuric, <b>Henggang Cui</b>, Thi Duong Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider, David McAllister Bradley
<br>
<i>US20200272160A1</i>
<br>
<br>
<span style="font-weight: bold;">
Object Motion Prediction and Autonomous Vehicle Control
</span><br>
Nemanja Djuric, Vladan Radosavljevic, Thi Duong Nguyen, Tsung-Han Lin, Jeff Schneider, <b>Henggang Cui</b>, Fang-Chieh Chou, Tzu-Kuo Huang
<br>
<i>US20190049970A1</i>
<br>
<br>
<span style="font-weight: bold;">
Processing a query using transformed raw data
</span><br>
<b>Henggang Cui</b>, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, Haris Volos
<br>
<i>US20170322987A1</i>
<br>
<br>
<h2>Talks</h2>
<span style="font-weight: bold;">
Exploiting Application Characteristics for Efficient System Support of Data-parallel Machine Learning
[<a href="./archive/talk/cui-thesis-defense.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>
<br>
<i>CMU Ph.D. Thesis Defense,
Pittsburgh, PA, April 2017</i>
<br>
</li>
<br>
<!--
<span style="font-weight: bold;">
MLtuner: System Support for Automatic Machine Learning Tuning
[<a href="./archive/talk/pdl-retreat-16-mltuner.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>, Gregory R. Ganger, and Phillip B. Gibbons
<br>
<i>Parallel Data Lab Retreat, Bedford Springs, PA, October 2016</i>
<br>
</li>
<br>
-->
<span style="font-weight: bold;">
GeePS: Scalable Deep Learning on Distributed GPUs with A GPU-specialized Parameter Server
[<a href="./archive/talk/eurosys16-geeps.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, and Eric P. Xing
<br>
<i>ACM European Conference on Computer Systems (EuroSys),
London, UK, April 2016</i>
<br>
</li>
<br>
<!--
<span style="font-weight: bold;">
Scalable Deep Learning on Distributed GPUs with A GPU-specialized Parameter Server
[<a href="./archive/talk/pdl-retreat-15-geeps.pptx">slides</a>]
</span><br>
<b>Henggang Cui</b>, Gregory R. Ganger, and Phillip B. Gibbons
<br>
<i>Parallel Data Lab Retreat, Bedford Springs, PA, October 2015</i>
<br>
</li>
<br>
-->
<span style="font-weight: bold;">
Using Data Transformations for Low-latency Time Series Analysis
[<a href="./archive/talk/socc15-aperture.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, and Gregory R. Ganger
<br>
<i>ACM Symposium on Cloud Computing (SoCC),
Kohala Coast, HI, August 2015</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
Exploiting Iterative-ness for Parallel ML Computations
[<a href="./archive/talk/socc14-iterstore.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>, 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
<br>
<i>ACM Symposium on Cloud Computing (SoCC),
Seattle, WA, November 2014</i>
<br>
</li>
<br>
<!--
<span style="font-weight: bold;">
Exploiting Iterative-ness for Parallel ML Computations
[<a href="./archive/talk/pdl-retreat-14-iterstore.pptx">slides</a>]
</span><br>
<b>Henggang Cui</b>, 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
<br>
<i>Parallel Data Lab Retreat, Bedford Springs, PA, October 2014</i>
<br>
</li>
<br>
-->
<!--
<span style="font-weight: bold;">
Ingest-time Transformations in Time Series Database
[<a href="./archive/talk/pdl-retreat-14-timeseries.pptx">slides</a>]
</span><br>
<b>Henggang Cui</b>, Kimberly Keeton, Indrajit Roy, Krishnamurthy Viswanathan, Haris Volos, and Gregory R. Ganger
<br>
<i>Parallel Data Lab Retreat, Bedford Springs, PA, October 2014</i>
<br>
</li>
<br>
-->
<span style="font-weight: bold;">
Exploiting Bounded Staleness to Speed Up Big Data Analytics
[<a href="./archive/talk/atc14-lazytable.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>, 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
<br>
<i>USENIX Annual Technical Conference (ATC),
Philadelphia, PA, June 2014</i>
<br>
</li>
<br>
<span style="font-weight: bold;">
LazyTable: Distributed Machine Learning with the Stale Synchronous Parallel Model
[<a href="./archive/talk/sosp13-wip-lazytable.pdf">slides</a>]
</span><br>
<b>Henggang Cui</b>, James Cipar, Qirong Ho, Jin Kyu Kim, Abhimanu Kumar,
Seunghak Lee, Greg R. Ganger, Phil B. Gibbons, Garth A. Gibson, and Eric P. Xing
<br>
<i>WIP Talk, ACM Symposium on Operating Systems Principles (SOSP),
Farmington, PA, November 2013</i>
<br>
</li>
<!--
<span style="font-weight: bold;">
Exploiting Bounded Staleness to Speed up Big Data Analytics
[<a href="./archive/talk/pdl-retreat-13-lazytable.pptx">slides</a>]
</span><br>
<b>Henggang Cui</b>, James Cipar, Qirong Ho, Jin Kyu Kim, Abhimanu Kumar,
Seunghak Lee, Greg R. Ganger, Phil B. Gibbons, Garth A. Gibson, and Eric P. Xing
<br>
<i>Parallel Data Lab Retreat, Bedford Springs, PA, October 2013</i>
<br>
</li>
-->
<h2>Public services</h2>
Program committee of <i>Conference on Neural Information Processing Systems (NeurIPS) 2024</i>.
<br>
Program committee of <i>International Conference on Machine Learning (ICML) 2024</i>.
<br>
Program committee of <i>International Conference on Learning Representations (ICLR) 2024</i>.
<br>
Program committee of <i>Conference on Neural Information Processing Systems (NeurIPS) 2023</i>.
<br>
Program committee of <i>CVPR 2023 "Precognition: Seeing through the Future" Workshop</i>.
<br>
Program committee of <i>International Conference on Machine Learning (ICML) 2023</i>.
<br>
Program committee of <i>International Conference on Learning Representations (ICLR) 2023</i>.
<br>
Program committee of <i>ECCV 2022 "AVVision2022" Workshop</i>.
<br>
Program committee of <i>Conference on Neural Information Processing Systems (NeurIPS) 2022</i>.
<br>
Program committee of <i>ICML 2022 Workshop on Safe Learning for Autonomous Driving</i>.
<br>
Program committee of <i>CVPR 2022 "Precognition: Seeing through the Future" Workshop</i>.
<br>
Reviewer of <i>IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022</i>.
<br>
Program committee of <i>International Conference on Machine Learning (ICML) 2022</i>.
<br>
Program committee of <i>International Conference on Learning Representations (ICLR) 2022</i>.
<br>
Reviewer of <i>IEEE International Conference on Robotics and Automation (ICRA) 2022</i>.
<br>
Program committee of <i>ICCV 2021 "AVVision2021" Workshop</i>.
<br>
Reviewer of <i>IEEE Robotics and Automation Letters (RA-L) 2021</i>.
<br>
Program committee of <i>Conference on Neural Information Processing Systems (NeurIPS) 2021</i>.
<br>
Program committee of <i>IJCAI 2021 "Autonomous Driving" Workshop</i>.
<br>
Program committee of <i>The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-KDD) 2021</i>.
<br>
Program committee of <i>CVPR 2021 "Precognition: Seeing through the Future" Workshop</i>.
<br>
Reviewer of <i>IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021</i>.
<br>
Program committee of <i>International Conference on Machine Learning (ICML) 2021</i>.
<br>
Reviewer of <i>IEEE Intelligent Vehicles Symposium (IV) 2021</i>.
<br>
Reviewer of <i>IEEE International Conference on Robotics and Automation (ICRA) 2021</i>.
<br>
Reviewer of <i>International Conference on Learning Representations (ICLR) 2021</i>.
<br>
Program committee of <i>NeurIPS 2020 "Machine Learning for Autonomous Driving" Workshop</i>.
<br>
Program committee of <i>The Web Conference (WWW) 2021</i>.
<br>
Reviewer of <i>IEEE Robotics and Automation Letters (RAL) 2020</i>.
<br>
Program committee of <i>ECCV 2020 "Autonomous Driving" Workshop</i>.
<br>
Program committee of <i>The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-KDD) 2020</i>.
<br>
Program committee of <i>CVPR 2020 "Precognition: Seeing through the Future" Workshop</i>.
<br>
Reviewer of <i>IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020</i>.
<br>
Program committee of <i>International Conference on Machine Learning (ICML) 2020</i>.
<br>
Reviewer of <i>IEEE Intelligent Vehicles Symposium (IV) 2020</i>.
<br>
Reviewer of <i>Cluster Computing (CC) 2020</i>.
<br>
Program committee of <i>The Web Conference (WWW) 2020</i>.
<br>
Reviewer of <i>IEEE International Conference on Robotics and Automation (ICRA) 2019</i>.
<br>
Reviewer of <i>IEEE Robotics and Automation Letters (RAL) 2019</i>.
<br>
Reviewer of <i>IEEE Big Data 2019</i>.
<br>
Program committee of <i>NeurIPS 2019 "Machine Learning for Autonomous Driving" Workshop</i>.
<br>
Reviewer of <i>Cluster Computing (CC) 2019</i>.
<br>
Program committee of <i>CVPR 2019 "Precognition: Seeing through the Future" Workshop</i>.
<br>
Reviewer of <i>IEEE Transactions on Network Science and Engineering (TNSE) 2018</i>.
<br>
Program committee of <i>ACM Symposium on Cloud Computing (SoCC) 2018</i>.
<br>
Program committee of <i>Computing Conference (CC) 2018</i>.
<br>
Program committee of <i>ACM Symposium on Cloud Computing (SoCC) 2017</i>.
<br>
<h2>Teaching</h2>
Teaching assistant of Storage Systems (15746/18746), Spring 2015.
[<a href="http://www.ece.cmu.edu/~ganger/746.spring15/index.html">link</a>]
<br>
Teaching assistant of Storage Systems (15746/18746), Fall 2016.
[<a href="http://www.ece.cmu.edu/~ganger/746.fall16/index.html">link</a>]
<br>
<h2>Misc</h2>
Henggang Cui at [<a href="https://www.linkedin.com/in/henggangcui/">LinkedIn</a>], [<a href="https://scholar.google.com/citations?user=hcVpBCIAAAAJ&hl=en">Google Scholar</a>], [<a href="https://github.com/cuihenggang/">Github</a>], [<a href="http://www.inaturalist.org/people/474164">iNaturalist</a>], [<a href="http://ebird.org/ebird/profile/NjAzNjM4/">eBird</a>].
<br>
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