Hang Qiu
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I received my Ph.D. from Networked Systems Lab @ USC. My advisor was Prof. Ramesh Govindan. During my Ph.D., I was also privileged with close collaboration with Prof. Konstantinos Psounis, and Prof. Marco Gruteser. My research focuses on networked systems problems at the intersection of mobile/edge computing, machine learning, and wireless networking. My thesis, titled “Networked Cooperative Perception: Towards Robust and Efficient Autonomous Driving”, presents systems and algorithms that enable cooperative perception among networked vehicles and infrastructure sensors that can substantially augment perception and driving capabilities. I am currently a postdoc at Stanford University advised by Prof. Sachin Katti.
[Google Scholar][Thesis]
Preprints
Minimum Cost Active Labeling
Hang Qiu, Krishna Chintalapudi, Ramesh Govindan
In submission.
[Preprint]
Satyam: Democratizing Groundtruth for Machine Vision
Hang Qiu, Krishna Chintalapudi, Ramesh Govindan
Integrated into Microsoft Azure ML.
Used by researchers at UCSB, USC, UIUC, ARL across different disciplines
[Paper][Demo][Code][Webpage][FourSeasons Dataset]
[Featured in Microsoft Ignite 2019]
Select Publications [Full List]
CarMap: Fast 3D Feature Map Updates for Automobiles
Fawad Ahmad, Hang Qiu, Fan Bai, Ramesh Govindan
USENIX NSDI, 2020.
[Paper][Demo][Code]
AVR: Augmented Vehicular Reality
Hang Qiu, Fawad Ahmad, Fan Bai, Marco Gruteser, Ramesh Govindan
ACM Mobisys, 2018. Best Paper Runner-up Award
[Paper][Talk][Slides][Demo][Code]
[GetMobile Highlights]
@inproceedings{Qiu18d,
title = {AVR: Augmented Vehicular Reality},
author = {Hang Qiu and Fawad Ahmad and Fan Bai and Marco Gruteser and Ramesh Govindan},
url = {http://doi.acm.org/10.1145/3210240.3210319},
doi = {10.1145/3210240.3210319},
isbn = {978-1-4503-5720-3},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys)},
pages = {81--95},
publisher = {ACM},
address = {Munich, Germany},
series = {MobiSys '18},
abstract = {Autonomous vehicle prototypes today come with line-of-sight depth perception sensors like 3D cameras. These 3D sensors are used for improving vehicular safety in autonomous driving, but have fundamentally limited visibility due to occlusions, sensing range, and extreme weather and lighting conditions. To improve visibility and performance, we explore a capability called Augmented Vehicular Reality (AVR). AVR broadens the vehicle's visual horizon by enabling it to wirelessly share visual information with other nearby vehicles. We show that AVR is feasible using off-the-shelf wireless technologies, and it can qualitatively change the decisions made by autonomous vehicle path planning algorithms. Our AVR prototype achieves positioning accuracies that are within a few percentages of car lengths and lane widths, and it is optimized to process frames at 30fps.},
note = {Best Paper Runner-up},
keywords = {Autonomous Cars, Collaborative Sensing, Extended Vision, nsl, vehicular sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
Kestrel: Video Analytics for Augmented Multi-Camera Vehicle Tracking
Hang Qiu, Xiaochen Liu, Swati Rallapalli, Archith J. Bency, Rahul Urgaonkar, B.S. Manjunath, Ramesh Govindan, Kevin Chan
ACM / IEEE IoTDI, 2018.
[Paper][Slides][Demo][Data]
@inproceedings{Qiu18c,
title = {Kestrel: Video Analytics for Augmented Multi-Camera Vehicle Tracking},
author = {H Qiu and X Liu and S Rallapalli and A J Bency and K Chan and R Urgaonkar and B S Manjunath and R Govindan},
doi = {10.1109/IoTDI.2018.00015},
year = {2018},
date = {2018-04-01},
booktitle = {2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)},
pages = {48-59},
keywords = {nsl},
pubstate = {published},
tppubtype = {inproceedings}
}
Towards Robust Vehicular Context Sensing
Hang Qiu, Jinzhu Chen, Matt McCartney, Yurong Jiang, Shubham Jain, Gorkem Kar, Donald Grimm, Fan Bai, Marco Gruteser, Ramesh Govindan
IEEE Transactions on Vehicular Technology (TVT), vol. 67, no. 3, pp. 1909-1922, March 2018.
[Paper][Data]
@article{Qiu18b,
title = {Towards Robust Vehicular Context Sensing},
author = {H Qiu and J Chen and S Jain and Y Jiang and M McCartney and G Kar and F Bai and D K Grimm and M Gruteser and R Govindan},
doi = {10.1109/TVT.2017.2771623},
issn = {0018-9545},
year = {2018},
date = {2018-03-01},
journal = {IEEE Transactions on Vehicular Technology},
volume = {67},
number = {3},
pages = {1909-1922},
keywords = {nsl, vehicular sensing},
pubstate = {published},
tppubtype = {article}
}
Augmented Vehicular Reality: Enabling Extended Vision for Future Vehicles
Hang Qiu, Fawad Ahmad, Ramesh Govindan, Marco Gruteser, Fan Bai, Gorkem Kar
ACM HotMobile, 2017.
[Paper][Slides]
@inproceedings{Qiu17a,
title = {Augmented Vehicular Reality: Enabling Extended Vision for Future Vehicles},
author = {Hang Qiu and Fawad Ahmad and Ramesh Govindan and Marco Gruteser and Gorkem Kar Fan Bai},
url = {http://doi.acm.org/10.1145/3032970.3032976},
year = {2017},
date = {2017-02-01},
booktitle = {the 18th Workshop on Mobile Computing Systems and Applications (HotMobile 2017)},
address = {Sonoma, CA},
abstract = {Like today's autonomous vehicle prototypes, vehicles in the future will have rich sensors to map and identify objects in the environment. For example, many autonomous vehicle prototypes today come with line-of-sight depth perception sensors like 3D cameras. These cameras are used for improving vehicular safety in autonomous driving, but have fundamentally limited visibility due to occlusions, sensing range, and extreme weather and lighting conditions. To improve visibility and performance, not just for autonomous vehicles but for other Advanced Driving Assistance Systems (ADAS), we explore a capability called Augmented Vehicular Reality (AVR). AVR broadens the vehicle's visual horizon by enabling it to share visual information with other nearby vehicles, but requires careful techniques to align coordinate frames of reference, and to detect dynamic objects. Preliminary evaluations hint at the feasibility of AVR and also highlight research challenges in achieving AVR's potential to improve autonomous vehicles and ADAS.},
keywords = {nsl, vehicular sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
High-rate WiFi Broadcasting in Crowded Scenarios via Lightweight Coordination of Multiple Access Points
Hang Qiu, Konstantinos Psounis, Giuseppe Caire, Keith M. Chugg, Kaidong Wang
ACM MobiHoc, 2016.
[Paper][Talk][Slides]
@inproceedings{Qiu16a,
title = {High-rate WiFi Broadcasting in Crowded Scenarios via Lightweight Coordination of Multiple Access Points},
author = {Hang Qiu and Konstantinos Psounis and Giuseppe Caire and Keith M Chugg and Kaidong Wang},
year = {2016},
date = {2016-07-01},
booktitle = {Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc '16)},
address = {Paderborn, Germany},
keywords = {nsl},
pubstate = {published},
tppubtype = {inproceedings}
}
CARLOC: Precisely Tracking Automobile Position
Yurong Jiang, Hang Qiu, Matthew McCartney, Gaurav Sukhatme, Marco Gruteser, Fan Bai, Donald Grimm, Ramesh Govindan
ACM SenSys, 2015.
[Paper]
@inproceedings{Jiang15a,
title = {CARLOC: Precisely Tracking Automobile Position},
author = {Yurong Jiang and Hang Qiu and Matthew McCartney and Gaurav Sukhatme and Marco Gruteser and Fan Bai and Donald Grimm and Ramesh Govindan},
year = {2015},
date = {2015-11-01},
booktitle = {Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems (SenSys)},
address = {Seoul, Korea},
keywords = {nsl, vehicular sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
CarLog: A Platform for Flexible and Efficient Automotive Sensing
Yurong Jiang, Hang Qiu, Matthew McCartney, William G. J. Halfond, Fan Bai, Donald Grimm, Ramesh Govindan
ACM SenSys, 2014.
[Paper]
@inproceedings{Jiang14a,
title = {CarLog: A Platform for Flexible and Efficient Automotive Sensing},
author = {Yurong Jiang and Hang Qiu and Matthew McCartney and William G J Halfond and Fan Bai and Donald Grimm and Ramesh Govindan},
year = {2014},
date = {2014-11-01},
booktitle = {Proceedings of the 12th ACM Conference on Embedded Networked Sensor Systems (SenSys'14)},
address = {Memphis, TN, USA},
keywords = {vehicle sensing, vehicular sensing},
pubstate = {published},
tppubtype = {inproceedings}
}
Teaching
Select Awards
- Qualcomm Innovation Fellowship, Finalist, San Diego, USA, 2019
- Best Paper Runner-up Award, ACM Mobisys, Munich, Germany, 2018
- Viterbi Graduate Student Annenberg Fellowship, 2013~2017
- Outstanding Winner, Interdisciplinary Contest in Modeling (ICM), 2012
- National Fellowship, 2010, 2011, 2012
- First-Class Academic Excellence Scholarship of SJTU, 2010, 2011, 2012
- Academic Star of Shanghai Jiao Tong University, 2012
- First Prize in China Undergraduate Mathematical Contest in Modeling (CUMCM), 2011
- NSF / SIGMOBILE Travel Grants: ACM Mobicom’16, ACM Sensys’16, ACM HotMobile’17
Recent Talks
- AVR @ Qualcomm Innovation Fellowship Final, San Diego, California, USA, Apr 2019
- AVR @ Intel’s Autonomous Driving CoP Workshop, Santa Clara, California, USA, Oct 2018
- AVR @ SRC Techcon, Austin, Texas, USA, Sep 2018
- AVR @ John Hopcroft Center, SJTU, Shanghai, China, Jun 2018
- AVR @ ACM Mobisys, Munich, Germany, Jun 2018
- Kestrel @ ACM/IEEE IoTDI, Orlando, Florida, USA, Apr 2018
- AVR @ ACM HotMobile, Sonoma, California, USA, Feb 2017
- CoBCast @ ACM Mobihoc, Paderborn, Germany, Jul 2016
Contact
Email: Fullname[at]usc[dot]edu
University of Southern California
941 Bloom Walk, SAL 227
Los Angeles, CA 90089-0781
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