Embedded Files
Hello World! This is Jing Wang (In Chinese: 王璟).
I am currently a postdoctoral fellow at University of Alberta. I completed my PhD at University of British Columbia (UBC) in December 2024, where I also served as the lab manager for the Industrial Automation Lab (UBC) under the guidance of Prof. Clarence de Silva and Prof. Leonid Sigal. I obtained my M.A.Sc. in 2020 and B.A.Sc. in 2018, both from UBC. I was born and raised in Chengdu, a historic metropolis in southwest China with a rich history spanning over 3,000 years.
My research interests are:
Robotics: Policy Learning, Reinforcement Learning, and Vision-Language-Action.
Machine Learning: Transfer Learning, Latent-Space Modelling, Diffusion Generative Models.
Silicon Photonics: Mach–Zehnder Interferometers, Microring Modulators, AI Accelerator.
For more details about my research, please refer to my Google Scholar: [Google Scholar]
Educations
Educations
University of British Columbia, Ph.D. in Robot Vision (Supervisor: Dr. Clarence de Silva), 2022-2024
University of British Columbia, Ph.D. in Silicon Photonics, (Supervisor: Dr. Lukas Chrostowski and Dr. Sudip Shekhar), 2020-2022
University of British Columbia, MASc in Mechanical Engineering (Supervisor: Dr. Clarence de Silva), 2018-2020
University of British Columbia, BASc in ECE, 2014-2018
Publications
Publications
(* denotes equal contribution; and ^ denotes corresponding author)
(* denotes equal contribution; and ^ denotes corresponding author)
Jing Wang, YongChao Xu^, Jing Tang, Zeyu Gong, Clarence W. de Silva, Bo Tao, and Xiang Bai, Discriminative Vicinal Density Flow: Advanced Source-Free Domain Adaptation via Energy-Based Vicinical Latent Schrödinger Bridge, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
Jing Wang, Weiting Peng, Jing Tang, Zeyu Gong, Xihua Wang, Bo Tao, and Li cheng, Act to See, See to Act: Diffusion-Driven Perception-Action Interplay for Adaptive Policies, Annual Conference on Neural Information Processing Systems (NeurIPS 2025).
Jing Wang, Wonho Bae, Jiahong Chen, Wenxu Wang, and Junhyug Noh, Vicinity-Guided Discriminative Latent Diffusion for Privacy-Preserving Domain Adaptation, Annual Conference on Neural Information Processing Systems (NeurIPS 2025).
Jing Wang, Wonho Bae, Jiahong Chen, Kuangen Zhang, Leonid Sigal, What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context, International Conference on Learning Representations (ICLR 2025).
Jiahong Chen, Kuangen Zhang, Zhichao Fan, Jing Wang^, Zhilin Zhang, and Weiming Shen, Closing the Simulation-to-Reality Gap for Digital Twin-Assisted Fault Diagnosis: Sim2Real Knowledge Transfer with Contrastive Learning, IEEE/ASME Transactions on Mechatronics (TMECH), 2025.
Erfaan Rezvanfar, Jing Wang^, and Clarence W. de Silva, Enhancement of Robot Dynamics Learning by Integrating Analytical Models into Deep Neural Networks: A Data Fusion Perspective, IEEE Transactions on Artificial Intelligence, 2025.
Wenxu Wang, Rui Zhou, Jing Wang, Bo Han, Yun Zhou, Cheng Zhu, Ruichun Tang, Nevin L. Zhang, COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation, International Conference on Machine Learning (ICML 2025).
Wonho Bae, Jing Wang, Danica J. Sutherland, Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling, European Conference on Computer Vision (ECCV 2024).
Jing Wang, Jiahong Chen, Kuangen Zhang, and Leonid Sigal, Training Feedforward Neural Nets in Hopfield-Energy-Based Configuration: A Two-Step Approach, Pattern Recognition (2024).
Jing Wang, Jiahong Chen, Jianzhe Lin, Leonid Sigal, and Clarence W. de Silva. Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by Gaussian-guided latent alignment, Pattern Recognition (2021).
Jing Wang*, Jiahong Chen* and Clarence W. de Silva. Mutual Variational Inference: An Indirect Variational Inference Approach for Unsupervised Domain Adaptation, IEEE Transactions on Cybernetics (TCYB) (2021).
Kuangen Zhang, Jiahong Chen, Jing Wang, Yuquan Leng, Clarence W. de Silva, and Chenglong Fu. Gaussian-guided feature alignment for unsupervised cross-subject adaptation, Pattern Recognition (2022).
Jiahong Chen, Jing Wang, Jianxin Zhu, Tong Heng Lee, and Clarence W. de Silva. Unsupervised cross-domain fault diagnosis using feature representation alignment networks for rotating machinery, IEEE/ASME Transactions on Mechatronics (TMECH) (2020).
Jing Wang*, Jiahong Chen*, Weipeng Lin, Kuangen Zhang, and Clarence W. de Silva, Preserving Domain Private Representation via Mutual Information Maximization, Neural Networks (2024).
Kuangen Zhang, Jiahong Chen, Jing Wang, Yuquan Leng, Clarence W. de Silva, and Chenglong Fu. Ensemble diverse hypotheses for unsupervised cross-subject intent prediction, Information Fusion (2023).
Jing Wang*, Jiahong Chen*, Tongxin Shu, and Clarence W. de Silva. WSN optimization for sampling-based signal estimation using semi-binarized variational autoencoder, Information Sciences (2022).
Mohammadreza Sanadgol Nezami, Thomas Ferreira de Lima, Matthew Mitchell, Shangxuan Yu, Jing Wang, Simon Bilodeau, Weipeng Zhang, Mohammed Al-Qadasi, Iman Taghavi, Alexander Tofini, Stephen Lin, Bhavin J. Shastri, Paul R. Prucnal, Lukas Chrostowski, Sudip Shekhar. Packaging and Interconnect Considerations in Photonic Accelerators, IEEE Journal of Selected Topics in Quantum Electronics (2022).
Jing Wang*, Kuangen Zhang*, Clarence W. de Silva, and Chenglong Fu. Unsupervised cross-subject adaptation for predicting human locomotion intent, IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020).
Jiahong Chen, Teng Li, Jing Wang, and Clarence W. de Silva. WSN sampling optimization for signal reconstruction using spatiotemporal autoencoder, IEEE Sensors Journal (2020).
Jing Wang, Wenwen Zhang, Hao Zhang, Enhanced Photonic Accelerator Design for Efficient Vector-Matrix Multiplication in Deep Learning, SPIE Optics and Photonics 2024.
Wenwen Zhang, Hao Zhang, Jing Wang^, Probing Ring Resonator Sensor Based on Vernier Effect, SPIE Optics and Photonics 2024.
Wenwen Zhang, Jing Wang^, Hao Zhang, Weight Bank Addition Photonic Accelerator for Artificial Intelligence, SPIE Optics and Photonics 2024.
Kuangen Zhang, Ming Hao, Jing Wang, Xinxing Chen, Yuquan Leng, Clarence W. de Silva, and Chenglong Fu. Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features, International Conference on Mechatronics and Machine Vision in Practice (M2VIP 2021).
Jing Wang, and Kuangen Zhang. Unsupervised domain adaptation learning algorithm for RGB-D staircase recognition, Instrumentation (2019).
Zhang, Kuangen, Jing Wang, and Chenglong Fu. Directional PointNet: 3D environmental classification for wearable robotics, Instrumentation (2019).
Industrial Experiences
Industrial Experiences
University of Alberta, Postdoctoral Researcher (2025.01.15 - present)
Borealis AI, RBC Institute of Research, Canada, Machine Learning Research Intern (supervised by Prof. Greg Mori) (2022.05 - 2022.09).
Industrial Automation Lab, University of British Columbia, Lab Manager (2022.01 - 2024.11).
Maxar Technologies, Canada, Engineering Intern (2017.09 - 2018-04).
Institute of Optics Electronics, Chinese Academy of Sciences, China, Research Intern (2016.04 - 2016-09).
Academic Services
Academic Services
Area Chair: IJCAI 2025
Top Reviewer Awards: NeurIPS (2023, 2024)
Conference Reviewer: NeurIPS (2025, 2024, 2023, 2022), ICLR (2025, 2024), ICML (2025, 2024, 2022), AISTATS (2026, 2025), AAAI (2026, 2025), IJCAI 2024, IROS 2025, M2VIP2021
Program Committee: AISTATS (2026, 2025), AAAI (2026, 2025), IJCAI 2024
Journal Reviewer: Information Fusion, Pattern Recognition, IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Multimedia, IEEE Transactions on Instrumentation and Measurement, Applied Soft Computing, Transactions on Machine Learning Research, Optics Express, Neurocomputing, Control Engineering Practice, Sensors, Drones
Awards
Awards
Top Reviewer Award, NeurIPS 2024
Top Reviewer Award, NeurIPS 2023
Department Award for Excellent Research, UBC, 2022 Winter
President's Academic Excellence Initiative PhD Award, UBC, 2020 Winter, 2021 Summer, 2021 Winter, and 2022 Summer
MITACS National Research Fellowship for MASc Student, Government of Canada, 2018, 2019, and 2020
International Student Tuition Award, UBC, 2018, 2019, 2020, 2021 and 2022
Faculty of Applied Science Graduate Award, UBC, 2019 Winter
PMC-Sierra Founders Award in Electrical and Computer Engineering, PMC-Sierra Inc, 2017 Winter
Faculty of Applied Science International Student Scholarship, UBC, 2015 Winter
Second Prize of National Physics Competition, China, 2012
Teaching
Teaching
Teaching Assistant
UBC MANU 386: Industrial Automation, Sept 2022 - Dec 2022
UBC MECH 469/529: Modelling of Dynamic systems, Sept 2020 - Present
UBC MECH 520: Sensor and Actuators for Control System, Sept 2020 - Present
UBC PHYS 158: Introductory Physics for Engineers II, Sept 2021 - Dec 2021
UBC PHYS 159: Introductory Physics Laboratory for Engineers, Jan 2022 - May 2022
Page updated
Google Sites
Report abuse