Abdullah Jamal

Contact

Phone: (407)-538-6366

Short Bio

Abdullah Jamal is a Staff ML Scientist at Intuitive Surgical. He received his PhD from University of Central Florida under the supervision of Dr. Liqianq Wang and Dr. Boqing Gong (remote/Google Research). His research focuses on computer vision and machine learning, with an emphasis on multimodal foundation models, visual representation learning, vision-language reasoning, and world models. He is particularly interested in scalable learning, model adaptation and distillation, and methods for building generalizable multimodal systems that can reason from visual evidence and operate in dynamic environments.

Before joining UCF, he received B.E. degree in Information and Communication Systems from National University of Sciences and Technology, Pakistan in 2013.

Recent News

Aug 2026 — DART: Depth-as-Target Pretraining for Surgical Vision Foundation Models accepted to BMVC 2026.
Aug 2026 — SUREON: A Benchmark and Vision-Language-Model for Surgical Reasoning featured in Intuitive’s official press release on AI-enabled healthcare.
May 2026 — Mitigating Surgical Data Imbalance with Dual-Prediction Video Diffusion Model accepted to ICML 2026.
Feb 2026 — SurgLaVi: Large-Scale Hierarchical Dataset for Surgical Vision-Language Representation Learning published in Medical Image Analysis.
May 2026 — Multimodal Masked Point Distillation for 3D Representation Learning published in TMLR.
June 2026 — Recognized as an IEEE CVPR Outstanding Reviewer