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Ruibing Jin

Scientist
A*star
ruibing_jin(at)outlook(dot)com

About Me

I am currently a Lead Data Scientist and lead an algorithm middle platform team in TikTok. Before that, I was a Scientist at Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (ASTAR), Singapore. I obtained my Bachelor’s Degree from University of Electronic Science and Technology of China (UESTC). After that, I obtained my Master and Ph.D degree from Nanyang Technological University (NTU), Singapore, respectively, under the supervision of Prof. Wang Jianliang, Prof. Wen Changyun and Prof. Lin Guosheng. I also cooperated with Prof. Yuan Junsong.

Research Interests

My research interests include multimodal large model, AIGC, computer vision, machine learning, time series and federated learning.

Awards

Services

I am a reviewer of top-tier conferences and journals including CVPR, ICCV, ECCV, AAAI, TCSVT, TNNLS, TII, PR, etc.

News

  • [Jul. 2024] One paper is accepted by IEEE Transactions on Industrial Informatics.
  • [Jun. 2024] One paper is accepted by IEEE Transactions on Industrial Informatics.
  • [May. 2024] One paper is accepted by IEEE Transactions on Artificial Intelligence.
  • [Feb. 2024] Our AdaNet published on TII is reported on A*STAR Research Highlights.
  • [Dec. 2023] One paper is accepted by IEEE Transactions on Instrumentation and Measurement.
  • [Oct. 2023] One paper is accepted by IEEE Transactions on Neural Networks and Learning Systems.
  • [Oct. 2023] One paper is accepted by IEEE Transactions on Reliability.
  • [Mar. 2023] One paper is accepted by IEEE Transactions on Industrial Informatics.
  • [Dec. 2022] Our paper “Multi-task Self-Supervised Adaptation for Reinforcement Learning” has won the best paper award at The 17th IEEE Conference on Industrial Electronics and Applications 2022！
  • [Dec. 2022] The source code for our Bi-LSTM based Two-Stream Network for RUL is released!
  • [Nov. 2022] One paper is accepted by IEEE Transactions on Circuits and Systems for Video Technology.
  • [Oct. 2022] 💥💥Our PE-Net receives much attention and is reported by the official JAS channel and some famous media, such as Tech Xplore, EurekAlert!, and PR Newswire.
  • [Oct. 2022] The source code for our PE-Net is released!
  • [Aug. 2022] One paper is accepted by IEEE/CAA Journal of Automatica Sinica.
  • [Apr. 2022] One paper is accepted by IEEE Transactions on Instrumentation and Measurement.
  • [Feb. 2022] One paper is accepted by Knowledge-Based Systems
  • [Feb. 2022] One paper is accepted by Pattern Recognition
  • [Jun. 2021] Our team AStarTrek achieved the 1st place winner for the CVPR 2021 UG2+ Challenge Track 2.1, which is officially repored by ASTAR on LinkedIn.
  • [Jun. 2021] One paper is accepted by Journal of Biophotonics.
  • [Apr. 2021] One paper is accepted by Biomedical Optics Express.
  • [Oct. 2020] One paper is accepted by IEEE Signal Processing Letters.

Selected Publications

FedAlign: Federated Model Alignment via Data-Free Knowledge Distillation for Machine Fault Diagnosis
Wenjun Sun, Ruqiang Yan*, Ruibing Jin*, Rui Zhao, Zhenghua Chen
IEEE Transactions on Instrumentation and Measurement. TIM.

LiteFormer: A Lightweight and Efficient Transformer for Rotating Machine Fault Diagnosis
Wenjun Sun, Ruqiang Yan*, Ruibing Jin*, Jiawen Xu, Yuan Yang, Zhenghua Chen
IEEE Transactions on Reliability.

An adaptive and dynamical neural network for machine remaining useful life prediction
Ruibing Jin, Duo Zhou, Min Wu, Xiaoli Li, Zhenghua Chen
IEEE Transactions on Industrial Informatics. TII.

Position Encoding Based Convolutional Neural Networks for Machine Remaining Useful Life Prediction
Jin Ruibing, Wu Min, Wu Keyu, Gao Kaizhou, Chen Zhenghua, Li Xiaoli
IEEE/CAA Journal of Automatica Sinica. JAS.

Bi-LSTM-Based Two-Stream Network for Machine Remaining Useful Life Prediction
Ruibing Jin, Zhenghua Chen, Keyu Wu, Min Wu, Xiaoli Li, Ruqiang Yan
IEEE Transactions on Instrumentation and Measurement. TIM.

Online Active Proposal Set Generation for Weakly Supervised Object Detection
Ruibing Jin, Guosheng Lin, Changyun Wen
Knowledge-Based Systems. KBS.

Feature flow: In-network feature flow estimation for video object detection
Ruibing Jin, Guosheng Lin, Changyun Wen, Jianliang Wang, Fayao Liu
Pattern Recognition. PR.


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