Depu Meng is a Senior Research Engineer and Tech Lead at Applied Intuition, focusing on multimodal foundation model training and physicalworld models. He was a Post-Doctoral Reseach Fellow at the University of Michigan, working with Dr. Henry X. Liu. He received the Ph. D. degree from University of Science and Technology of China, with a joint-PhD program with Microsoft Research Asia. His Ph. D. advisors are Dr. Baining Guo from Microsoft and Prof. Houqiang Li from USTC, he was also advised by Dr. Jingdong Wang. He interned at Microsoft Research Asia during 2017-2018, and 2019-2021. Here is his CV.

His research interests include multi-modal foundation model, physical world model, robotics world foundation model, etc.

Education

• Sept. 2018 - Jun. 2023
  Ph.D.
  School of Information Science and Technology, major in Control Science and Engineering
  University of Science and Technology of China - Microsoft Research Asia Supervisor: Dr. Baining Guo and Prof. Houqiang Li
• Sept. 2014 - Jun. 2018
  B.E.
  School of the Gifted Young (SCGY), major in Electrical Engineering
  University of Science and Technology of China

Work Experience

• Sep. 2025 - present
  Senior Research Engineer, Technical Lead
  AI Research, Applied Intuition
• Dec. 2024 - Aug. 2025
  Machine Learning Engineer
  AI Research, DiDi Autonomous Driving
• Apr. 2022 - Dec. 2024
  Post-Doctoral Research Fellow and Visiting Scholar
  Mobility Transformation Lab, University of Michigan
  Mentor: Prof. Henry X. Liu
• Aug. 2021 - Apr. 2022
  Research Intern
  Autonomous Delivery Group, Meituan
  Mentor: Dr. Changqiang Yu
• Jul. 2019 - Jul. 2021, Jul. 2017 - Jul. 2018
  Research Intern
  Visual Computing Group, Microsoft Research Asia
  Mentor: Dr. Jingdong Wang

Selected Publications

* Equal contribution, † Project lead

	Tianshuo Xu, Yichen Xie, Depu Meng†, Chensheng Peng, Quentin Herau, Bo Jiang, Yihan Hu, Wei Zhan Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution Arxiv, 2026 [Paper] [Project] [Code] [Model] [Dataset]
	Bo Jiang, Depu Meng, Yihan Hu, Yichen Xie, Tianshuo Xu, Wei Zhan LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation Arxiv, 2026 [Paper] [Project] [Code]
	Quentin Herau*, Tianshuo Xu*, Depu Meng†, Zhijie Yang, Chensheng Peng, Spencer Sherk, Yihan Hu, Wei Zhan SpectralSplat: Appearance-Disentangled Feed-Forward Gaussian Splatting for Driving Scenes Arxiv, 2026 [Paper]
	Yichen Xie, Depu Meng, Chensheng Peng, Yihan Hu, Quentin Herau, Masayoshi Tomizuka, Wei Zhan URoPE: Universal Relative Position Embedding across Geometric Spaces ECCV, 2026 (Oral) [Paper] [Project] [Code]
	Rusheng Zhang*, Depu Meng*, Shengyin Shen, Zhengxia Zou, Houqiang Li, Henry X. Liu MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles Tech Report [Paper] [Code]
	Rusheng Zhang, Depu Meng, Lance Bassett, Shengyin Shen, Zhengxia Zou, Henry X. Liu Robust Roadside Perception: an Automated Data Synthesis Pipeline Minimizing Human Annotation IEEE Transactions on Intelligent Vehicles (T-IV) & U.S. Patent, 2024 [Paper]
	Depu Meng, Owen Sayer, Rusheng Zhang, Shengyin Shen, Houqiang Li, Henry X. Liu ROCO: A Roundabout Traffic Conflict Dataset Transportation Research Board Annual Meeting (TRBAM), 2023 [Paper] [Data]
	Depu Meng, Changqian Yu, Jiajun Deng, Deheng Qian, Houqiang Li, Dongchun Ren Hybrid Motion Representation Learning for Prediction from Raw Sensor Data IEEE Transactions on Multimedia (T-MM), 2023 [Paper]
	Yunsheng Ni, Depu Meng, Changqian Yu, Chengbin Quan, Dongchun Ren, Youjian Zhao CORE: COnsistent REpresentation Learning for Face Forgery Detection CVPR Workshop on Media Forensics (CVPR Workshop), 2022 [Paper] [Code]
	Depu Meng*, Xiaokang Chen*, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun and Jingdong Wang (*: Equal Contribution) Conditional DETR for Fast Training Convergence International Conference on Computer Vision (ICCV), 2021 [Paper] [Code] [Model]
	Depu Meng, Zigang Geng, Zhirong Wu, Bin Xiao, Houqiang Li and Jingdong Wang Consistent Instance Classification for Unsupervised Representation Learning ICCV Workshop: Self-supervised Learning for Next-Generation Industry-level Autonomous Driving (ICCV Workshop), 2021 [Paper]
	Liming Zhao, Mingjie Li, Depu Meng, Xi Li, Zhaoxiang Zhang, Yueting Zhuang, Zhuowen Tu, Jingdong Wang Deep Convolutional Neural Networks with Merge-and-Run Mappings International Joint Conference on Artificial Intelligence (IJCAI), 2018 [Paper] [Code]

Services

• Conference Reviewer: CVPR, ECCV, ICCV, NeurIPS, ACM MM, IROS
• Journal Reviewer: IJCV, IEEE T-IV, IEEE T-MM, IEEE T-CSVT, Neuralcomputing, Pattern Recognition