EXceL-Lab@UCF
Efficient, Scalable and Accelerated Learning Laboratory (EXceL-Lab) at University of Central Florida.
Welcome to our Efficient, Scalable and Accelerated Learning Laboratory (EXceL-Lab) at University of Central Florida, part of the Department of Computer Science and the Insititute of AI. Our mission is to build the next generation efficient and scalable machine intelligence to democritize and accelerate AI technology. We approach this through optimizing and co-designing AI algorithms and hardware systems. We also actively push efficient AI to accelerate scientific discovery.
Research Goal: Efficient/Scalable AI
- Visual Generative Model Acceleration:
PTQ4DM (CVPR’2023), PTQ4DiT (NeurIPS’2024), DKDM (CVPR’2025), SpeeD for Diffusion Fast Training (CVPR’2025), QuEST (ICCV’2025), E-CAR. - Efficient (Visual, Language, and Multimodal) Large Models:
Bi-MTDP (CVPR’2024), FBPT (ICRA’2024), PB-LLM (ICLR’2024), PTQ1.61 (ACL’2025), LLM-Viewer (Efficient LLM Survey), RPTQ, ASVD, LLaVA-PruMerge (ICCV’2025), INTP-Video-LLMs. - Neural Network Compression:
LONDON (ICCV’2021), CMIM (ECCV’2022), LCR-BNN (ECCV’2022), Causal-DFQ (ICCV’2023), CL-Calib (CVPR’2024). - Efficient Training for Neural Networks:
MIM4DD (NeurIPS’2023), DQAS (ECCV’2024), HEPrune (NeurIPS’2024), LTDD (CVPR’2025).
Members
Principal Investigator
- Yuzhang Shang, Assistant Professor
Ph.D. Students
- Kunyang Li (Fall 2025-current, B.S.: University of Electronic Science and Technology of China & M.S.: Nanyang Technological University)
M.S. Students
- Mahd Qureshi (Fall 2025-current, B.S.: Lahore University of Management Sciences)
Research Assistant
- Zhiben Chen (Summer 2025-current, B.S.: University of Macau & M.S.: CMU)