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Ser Nam Lim

Associate Professor

BIOGRAPHY

Lim is an associate professor of Computer Science at the University of Central Florida and a member of the UCF AI Initiative. He is a former research scientist manager at Meta and a former director at GE Research. Lim received his doctorate in computer vision from the University of Maryland and holds master’s and bachelor’s degrees in computer science from the National University of Singapore.

He spent ten years at GE Research focusing on video recognition, 3D reconstruction, representation learning, and visual matching in computer vision. At Meta, Lim led teams developing next-generation AI algorithms for automatic understanding of massive user-uploaded images and videos to ensure platform safety.

He has published more than 150 peer-reviewed papers, with more than half appearing in top-tier AI conferences. His research interests include image and video generation, AI for augmented reality, and vision-language representation and understanding. Lim’s recent work includes papers accepted at ICML, CVPR, ECCV, ICCV, NeuRIPS, SIGGRAPH, EMNLP and ICLR, covering topics such as long-horizon agents, generative zero-shot image retrieval, and generative models for fine-grained tasks. He has made significant contributions to computer vision and multimodal AI with over 17,000 citations.

EDUCATION

  • Ph.D. in Computer Science, University of Maryland at College Park
  • M.S. in Computer Science, University of Maryland at College Park
  • B.S. in Computer Science, National University of Singapore
  • AI Knowledge
  • Generative AI
  • Multimodal AI

“Visual prompt tuning”, M Jia, L Tang, BC Chen, C Cardie, S Belongie, B Hariharan, SN Lim, ECCV 2022

“Large scale learning on non-homophilous graphs: New benchmarks and strong simple methods”, D Lim, F Hohne, X Li, SL Huang, V Gupta, O Bhalerao, SN Lim, NeuRIPS 2021

“Hornet: Efficient high-order spatial interactions with recursive gated convolutions”, Y Rao, W Zhao, Y Tang, J Zhou, SN Lim, J Lu, NeuRIPS 2022

“Adavit: Adaptive vision transformers for efficient image recognition”, L Meng, H Li, BC Chen, S Lan, Z Wu, YG Jiang, SN Lim, CVPR 2022

“Nerv: Neural representations for videos”, H Chen, B He, H Wang, Y Ren, SN Lim, A Shrivastava, NeuRIPS 2021

“Ma-lmm: Memory-augmented large multimodal model for long-term video understanding”, B He, H Li, YK Jang, M Jia, X Cao, A Shah, A Shrivastava, SN Lim, CVPR 2024

“Open vocabulary semantic segmentation with patch aligned contrastive learning”, Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed, Rui Wang, Ashish Shah, Philip HS Torr, Ser-Nam Lim, CVPR 2023

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