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Huijing Zhao is a Professor of Machine Intelligence
at Peking University. She received B.S.
degree in computer science in 1991 from Peking University, China.
From 1991 to 1994, she was recruited by Peking University
in a project of developing a GIS platform. She obtained M.E. degree in
1996 and Ph.D. degree in 1999
in civil engineering from the University of Tokyo, Japan.
After several years' post-doctoral research at the same university, in
2003, she was promoted to be a visiting associate professor in the Center
for Spatial Information Science, University
of Tokyo, Japan.
In 2007, she joined Peking University as a tenure-track professor at the School of Electronics Engineering
and
Computer Science according to an “Introducing Young Talent Researchers
Program” of the university, called "Hundred Talents Program".
She became an associate professor with tenure on 2013, and promoted to full professor with tenure on 2020.She has research
interest in several areas in connection with intelligent vehicle and
mobile robot, such as machine perception, behavior learning and motion
planning, and she has special interests on the studies through real world
data collection.
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Announcement :
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For the latest research
activities and more information, please visit the lab website POSS.
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Students are welcome to take the course ”introduction to intelligent robots”(autumn semester, for the 3-4
grade undergraduate school students mainly). Many excellent
project videos
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Students for internship,
undergraduate research training, Master, PhD, are welcome.
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Please contact zhaohj/AT/cis.pku.edu.cn.
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Research
: (More
Details)
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Research Fields:
intelligent vehicle and mobile robotics, machine perception and reasoning
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With special interests on
the environmental perception, localization and mapping, driving behavior
modeling and reasoning technologies in real-world traffic environment g
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For details, please visit
the lab website POSS.
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Teaching : (More
Details)
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Independent teaching
“Introduction to Intelligent Robots”, 32 hours, autumn semester, for the
3-4 grade undergraduate school students, lecturer: Zhao,H.
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Independent teaching
“Algorithm Design and Analysis”, 32 hours, spring semester, the 2nd grade
undergraduate school students, lecturer: Zhao,H.
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Participate teaching
introductory courses of “Introduction to Intelligent Information Science”
for graduate school studentsand “Introduction
to Intelligent Science and Technology” for undergraduate school students.
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Selected
Publications : More
Details
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Mei,J., Gao,B.,
Xu,D., Yao,W., Zhao,X., Zhao,H., Semantic Segmentation
of 3D LiDAR Data in Dynamic Scene Using Semi-supervised Learning, IEEE
Trans. on Intelligent Transportation Systems (T-ITS), 5(2), 178-187, 2020.
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Xu,D., Ding,Z., He,X., Zhao,H, Moze,M., Aioun,F., Guillemard,F., Learning From Naturalistic Driving Data for Human-Like Autonomous Highway Driving, IEEE Trans. on Intelligent Transportation Systems (T-ITS), 2020.
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Fang,Y., Wang,C.,
Yao,W., Zhao,X., Zhao,H., Zha,H., On-Road
Vehicle Tracking Using Part-Based Particle Filter, IEEE Transactions on
Intelligent Transportation Systems (T-ITS), 20(12), 4538-4552, 2019. -
Xu,D., Zhao,H.,
Guillemard,F., Geronimi,S.,
Aioun,F., Aware of Scene Vehicles -
Probabilistic Modeling of Car-Following Behaviors in Real-World Traffic, IEEE
Transactions on Intelligent Transportation Systems (T-ITS), 20(6) ,
2136–2148, 2019.
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Mei,J., Yu,Y.,
Zhao,H., Zha,H.,
Scene-Adaptive Off-Road Detection Using a Monocular Camera, IEEE Trans.
on Intelligent Transportation Systems (T-ITS), 19(1), 242-253, 2018.
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Zhao,H., Wang,C.,
Lin,Y., Guillemard,F.,
Geronimi,S., Aioun,F.,
On-road Vehicle Trajectory Collection and Scene-based Lane Change
Analysis: Part I, IEEE Trans on Intelligent Transportation Systems
(T-ITS), 18(1), 192-205, 2017.
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Yao,W., Zeng,Q.,
Lin,Y., Xu,D., Zhao,H., Guillemard,F., Geronimi,S., Aioun,F.,
On-road Vehicle Trajectory Collection and Scene-based Lane Change
Analysis: Part II, IEEE Trans on Intelligent Transportation Systems
(T-ITS), 18(1), 206-220, 2017.
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Wang,C., Fang,Y.,
Zhao,H., Guo,C., Mita,S., Zha,H.,
Probabilistic Inference for Occluded and Multiview On-road Vehicle
Detection, IEEE Trans. on Intelligent Transportation Systems (T-ITS),
17(1), 215 – 229, 2016.
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Funded Projects: (Selected) – More
Details
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NSFC Project (General
Program): On-Road Vehicles' Behavior Analysis and Contextual
Understanding, 2016-2019.
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NSFC Project (General
Program): Towards 3D SLAM in an Outdoor Dynamic Urban Environment,
2010-2012.
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NSFC-ANR Joint Sino-French
Research Project: Multimodal Perception and Reasoning for Transnational
Intelligent Vehicles (PRETIV), 2012-2014.
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National 863 Project:
Intersection Sensing using Distributed Multi-modal Sensors, 2007-2009.
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PSA-PKU OpenLab Project, Driving Behavior Modeling and Reasoning based on Multimodal Perception (DMARP v1.0 and v2.0), 2012-2019.
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SAIC Cooperative Research
Project, Development of Key Techniques based on 3D LiDAR SLAM, 2017-2018.
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TCRDL Cooperative
Research Project (with Toyota Central Research & Development
Laboratories, INC., Japan), Online Sensor Calibration using Road
Structural Features, 2013-2015.
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ICT‐Asia program (France),
Vehicle perception and reasoning enhanced with digital maps (PREDiMap), 2011.4-2013.3.
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LIAMA project, 3D
Multimodal Perception and Reasoning (MPR), 2010.11-2012.10.
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Mazda Cooperative
Research Project (Japan), A Study of Enhancing Driving Safety at an
Intersection using Laser Sensing, 2007-2009.
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Authorized Patents:
Chinese Invention Patent
- Classification method of vehicle-borne LiDAR data based on
neural network model, Authors: Mei, J., Zhao, H., Application No.
201910053794.0, 2019.1.21.
- Road extraction method at off-road environment using 3D
LiDAR data, Authors: Gao, B., Pan, Y., Xu, A., Zhao, H., Application No.
201910121876.4, 2019.2.19.
- Calibration method and system of vehicle-borne 3D LiDAR,
Authors: Ju, X., Zhao, H., Application No. 201910129953.0, 2019.2.21.
- Multi-modal fusion-based positioning method for unmanned
ground platform, Authors: Ju, X., Zhao, H., Application No.
201910130418.7, 2019.2.21.
- A vehicle-borne 3D measurement system and application. Authors: Yu, Y., Zhao, H., et al. (Peking Univ.), No. ZL 2014 1 0635872.5, 2016.6.15.
- An automated method of vehicle training sample collection
using multi-model sensor data. Authors: Wang, C., Zhao, H., et al.
(Peking Univ.), No. ZL 2012 1 0234127.0, 2015.6.24.
- A system of estimating pedestrians’ motion direction using
laser scanner. Authors: Zhao, H., et al. (Peking Univ.), Zhou, S., et al.
(China TransInfo), No. ZL 2009 1 0091650.0,
2011.6.8.
- A method and system of moving object detection using
multiple laser scanners. Authors: Zhao, H., et al., (Peking Univ.), Shibasaki R., No. ZL 2008 1 0170194.4, 2011.7.20.
- A method and system of multiple laser scan data fusion,
Authors: Zhao, H., et al., (Peking Univ.), Shibasaki
R., No. ZL 2008 1 0171317.6, 2011.9.21.
International Invention
Patent
- Method for driver identification based on car following
modeling, Authors: Xu, D., Tu, C., Zhao, H., (Peking Univ.), Moze, M., Aioun, F., Guillemard, F.（PSA Automobiles SA）, Application No. PCT/CN2018/092903, 2018.6.26.
- Method for providing vehicle trajectory prediction,
Authors: Xu, D., He, X., Zhao, H., (Peking Univ.), Moze,
M., Aioun, F., Guillemard,
F.（PSA
Automobiles SA）, Application No. PCT/CN2018/092905, 2018.6.26.
- Prediction method for trajectory of vehicle, prediction system and vehicle Sun,R.,Hu,S.,Zhao,H. (Peking Univ.), Moze,M., Aioun,F., Guillemard,F. (PSA Automobiles SA) ), Application No. PCT/CN2019/113683, 2019.10.28
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