Lingqi Yan
Associate Professor of Computer Science
Research Interests
Professor Yan's research is in Computer Graphics, mainly aimed at rendering photorealistic visual appearance at real world complexity, including theoretical foundations that reveal the unknown principles of the visual world, as well as best practices to improve rendering performance for both offline and real-time applications. Professor Yan's research combines traditional and modern solutions. He enjoys working with mathematics and physics to solve appearance modeling, real-time ray tracing and sampling, large-scale scene aggregation, wave optics and general light transport algorithms. He also actively explores neural aided rendering techniques, exploiting the power of AI on difficult rendering problems, such as neural BRDFs, denoising, appearance synthesis, multiple scattering inference, generative post-processing, super-resolution and frame generation.
Email
Prior to joining MBZUAI, Professor Yan served as an Associate Professor of Computer Science at UC Santa Barbara, where he was Co-Director of the MIRAGE Lab and an affiliated faculty member in the Four Eyes Lab. He has also held roles as a Visiting Professor at NVIDIA and Research Consultant at Intel.
His research focuses on photorealistic rendering in computer graphics, with a world-leading publication record at ACM SIGGRAPH. Professor Yan has introduced novel research directions such as detailed appearance modeling, while also contributing to practical advancements, including frame generation technologies for video games.
rofessor Yan's contributions have earned wide recognition, including the ACM SIGGRAPH Outstanding Doctoral Dissertation Award, multiple Best Paper Awards, and association with several Academy Awards for Best Visual Effects, granted to films that explicitly adopted his research.
In addition to his research, Professor Yan is deeply committed to education. He is the creator of the popular online courses GAMES101 and GAMES202, which have reached millions of learners and helped broaden access to computer graphics education worldwide.
His research focuses on photorealistic rendering in computer graphics, with a world-leading publication record at ACM SIGGRAPH. Professor Yan has introduced novel research directions such as detailed appearance modeling, while also contributing to practical advancements, including frame generation technologies for video games.
rofessor Yan's contributions have earned wide recognition, including the ACM SIGGRAPH Outstanding Doctoral Dissertation Award, multiple Best Paper Awards, and association with several Academy Awards for Best Visual Effects, granted to films that explicitly adopted his research.
In addition to his research, Professor Yan is deeply committed to education. He is the creator of the popular online courses GAMES101 and GAMES202, which have reached millions of learners and helped broaden access to computer graphics education worldwide.
- Ph.D. in Computer Science from University of California, Berkeley
- Bachelor of Engineering in Computer Science from the Tsinghua University
- Eurographics Symposium on Rendering (EGSR) Best Paper Award and Best Visual Effects Award, 2023
- ACM SIGGRAPH Technical Papers Awards: Best Paper Honorable Mention, 2022
- ACM SIGGRAPH Outstanding Doctoral Dissertation Award, 2019
- Zilin Xu, Xiang Chen, Chen Liu, Beibei Wang, Lu Wang, Zahra Montazeri, Ling-Qi Yan: “Towards Comprehensive Neural Materials: Dynamic Structure-Preserving Synthesis with Accurate Silhouette at Instant Inference Speed”, ACM SIGGRAPH 2025 (Conference Track), 2025
- Songyin Wu, Zhaoyang Lv, Yufeng Zhu, Duncan Frost, Zhengqin Li, Ling-Qi Yan, Carl Ren, Richard Newcombe, Zhao Dong: “Monocular Online Reconstruction with Enhanced Detail Preservation”, ACM SIGGRAPH 2025 (Conference Track), 2025
- Zhimin Fan, Chen Wang, Yiming Wang, Boxuan Li, Yuxuan Guo, Ling-Qi Yan, Yanwen Guo, Jie Guo: “Bernstein Bounds for Caustics”, ACM Transactions on Graphics (Proceedings of SIGGRAPH 2025), 2025
- Zhimin Fan, Yiming Wang, Chenxi Zhou, Ling-Qi Yan, Yanwen Guo, Jie Guo: “Multiple Importance Reweighting for Path Guiding”, ACM Transactions on Graphics (Proceedings of SIGGRAPH 2025), 2025
- Yang Zhou, Tao Huang, Pradeep Sen, Ravi Ramamoorthi, Ling-Qi Yan: “Efficient Scene Appearance Aggregation for Level-of-Detail Rendering”, ACM Transactions on Graphics, 2025
- Apoorv Khattar, Junqiu Zhu, Ling-Qi Yan, Zahra Montazeri: “A Texture-Free Practical Model for Realistic Surface-Based Rendering of Woven Fabrics”, Computer Graphics Forum, 2025