Ke Jiang
Scholar

Ke Jiang

Google Scholar ID: lJ3AaHoAAAAJ
Nanjing University of Aeronautics and Astronautics / Osaka University
Reinforcement LearningComputer VisionMachine LearningDynamical Systems
Citations & Impact
All-time
Citations
33
 
H-index
3
 
i10-index
2
 
Publications
9
 
Co-authors
2
list available
Publications
9 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • - Publications:
  • - 'Variational OOD State Correction for Offline Reinforcement Learning' accepted by AAAI 2026
  • - 'Beyond Non-Expert Demonstrations: Outcome-Driven Action Constraint for Offline Reinforcement Learning' accepted by Pattern Recognition
  • - 'Towards Reliable Offline Reinforcement Learning via Lyapunov Uncertainty Control' accepted by IEEE Transactions on Neural Networks and Learning Systems
  • - 'RoGA: Towards Generalizable Deepfake Detection through Robust Gradient Alignment' accepted by ICME 2025 (Oral)
  • - 'Recovering from out-of-sample states via inverse dynamics in offline reinforcement learning' accepted by NeurIPS 2023
  • - Project Experience: Involved in research on offline reinforcement learning methods and theories in complex real-world scenarios, funded by the National Natural Science Foundation of China, led by Prof. Xiaoyang Tan
Research Experience
  • - From 14 April, 2025: Working as a visiting researcher at Machine Learning & Systems Laboratory, Graduate School of Information Science and Technology, Osaka University, under the supervision of Professor Yoshinobu Kawahara
Education
  • - B.Sc.: 2015.9-2019.6, School of Computer Science, Nanjing University of Information Science and Technology
  • - M.Sc.: 2019.9-2022.4, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Advisor: Prof. Xiaoyang Tan
  • - Ph.D. Student: 2022.4-Present, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Advisor: Prof. Xiaoyang Tan
Background
  • - Research Interests: (Robust, Generalizable, Safe, Offline) Reinforcement Learning; Generative Models for Long-horizon Planning; Cross-domain Classification (Videos & Image)