Jian Shi is a final-year Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), where he is advised by Prof. Peter Wonka, specializing in computer vision, geometric deep learning, generative AI, and 3D visual computing, with particular emphasis on stereo video synthesis, 3D perception, scene reconstruction, and immersive visual experiences.
Biography
Jian Shi is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), where he conducts research under the supervision of Prof. Peter Wonka. Before joining KAUST, Shi earned an M.Sc. in Cloud Computing with Distinction (First-Class Honours) from University of Leicester and a bachelor's degree in Information Management and Information Systems from Zhengzhou University of Aeronautics. His professional experience includes research positions at NEC Laboratories China, The Chinese University of Hong Kong, and GE Power, where he worked on a broad range of machine learning and computer vision applications.
Shi has established a strong publication record in leading journals and conferences in artificial intelligence and computer vision. His work has appeared in premier venues including ACM SIGGRAPH, ICML, CVPR, ICCV, ECCV, IEEE TPAMI, and ICRA. His recent research contributions include advances in stereo video generation, depth estimation, anomaly detection, human keypoint estimation from LiDAR data, and the integration of geometric reasoning into generative AI systems.
In addition to his academic research, Shi is a co-founder and core maintainer of Kornia, one of the world's most widely used open-source differentiable computer vision libraries built on PyTorch. He has also served as a mentor and organization administrator for Google Summer of Code, helping foster open-source innovation in computer vision and machine learning.
Among his notable achievements, Shi received the KAUST Dean's List Award in 2025 in recognition of his academic excellence and research accomplishments. He is also an inventor on multiple patent filings and has delivered invited talks on emerging topics such as agentic computer vision and open-source AI infrastructure. Through both his scholarly contributions and open-source leadership, Shi continues to advance the development of next-generation vision systems that enable machines to perceive, understand, and synthesize the three-dimensional world.
Expertise and Interests
Shi's recent work explores the intersection of geometry and generative AI. His research investigates stereo video synthesis, disparity learning, diffusion models, multi-view reconstruction, and high-fidelity 3D scene understanding. By incorporating geometric constraints into learning-based systems, he seeks to improve robustness, realism, and spatial consistency in next-generation AI vision models.
Awards and Distinctions
- CEMSE Dean's List Award, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), 2025
Education
- Master of Science (M.S.)
- Cloud Computing, University of Leicester (UoL), United Kingdom, 2018
- Bachelor of Management (B.Mgmt.)
- Information Management and Information Systems, Zhengzhou University of Aeronautics (ZUA), China, 2015
