Shu Kong

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I am an Assistant Professor of Computer Science at the University of Macau, leading the Visual Intelligence Lab. I am currently visiting OIST, working on interdisciplinary research. I previously held academic positions at Texas A&M University and Carnegie Mellon University. I did my postdoc training at the Robotics Institute of CMU working with Deva Ramanan. I received my PhD from UC-Irvine advised by Charless Fowlkes.

My research vision is to establish the foundations of Visual Intelligence, the ability of machines to perceive, understand, and interact with human-like robustness, adaptability, and generalization. To realize this vision, I develop fundamental algorithms at the interaction of CV, ML, HCI, robotics and graphics, and couple them with high-impact applications. This ensures that my algorithmic innovations both address and are informed by real-world challenges, and enables my contributions spanning autonomous systems, and scientific discovery, including applications in ecology, evolutionary biology, and palynology.

My research is guided by first-principles thinking and a commitment to identifying the fundamental limitations of existing visual intelligence systems. Guided by these principles, I establish Open World Vision (OWV), laying the foundation for more robust, generalizable and trustworthy Vision Intelligence systems. On OWV, my ICCV'21 paper was recognized for Best Paper / Marr Prize. Building upon OWV, I establish AutoExpert, aiming to democratize Visual Intelligence in not only real-world applications but also scientific domains. For example, I develop algorithms for high-throughput pollen analysis, aiming to advance research in paleoecology, palynology, phylogenetics, and long-term evolution. One of such algorithms was pubished in PNAS and featured by the U.S. NSF that "opens a new era of fossil pollen research".

I am actively looking for self-motivated PhD students at the University of Macau. PhD students will be fully funded with fellowships.

Email contact

  • related to UM: skong [at] um [dot] edu [dot] mo
  • related to OIST: shu.kong [at] oist [dot] jp
  • others: aimerykong [at] gmail [dot] com
  • related to TAMU: shu [at] tamu [dot] edu

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