Shu Kong, Ph.D.

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Assistant Professor
Dept. of AI
Dept. of CS
IAIBS
UMac

Research Affiliate
OIST

I lead the Visual Intelligence Lab. My research vision is to establish the foundations of Visual Intelligence: enabling machines to learn from the open world, domain experts, and individual users through visual perception and interaction, thereby becoming robust, knowledgeable, and personalized. To realize this vision, I pursue three complementary research directions:

  • Open-World Vision enables Visual Intelligence systems to learn from the real open world, making them more robust, generalizable, and trustworthy in open environments. My ICCV'21 paper that described the open world was recognized for Best Paper / Marr Prize.
  • AutoExpert enables these systems to learn from domain experts by acquiring, representing, and operationalizing expert knowledge, making expertise-intensive applications such as scientific discovery more accessible. I develop high-throughput visual intelligence systems for palynology, paleoecology, and evolutionary biology. My previous system, published in PNAS, was featured by the U.S. NSF that "opens a new era of fossil pollen research".
  • Personalized Visual Intelligence enables systems to learn from individual users, personalizing their perception, reasoning, memory, and interaction to each person’s unique preferences, goals, and context. I build systems to help individual users retrieve personal items (e.g., ref1, ref2) and improve the accessibility of their everyday interactions in home settings (e.g., ref1, ref2).

I previously was an Assistant Professor at Texas A&M University, and a Project Scientist at Carnegie Mellon University. I completed my postdoc training at the Robotics Institute of Carnegie Mellon University, where I was supervised by Deva Ramanan. I received my Ph.D. in Computer Science from the University of California, Irvine, where I was advised by Charless Fowlkes.

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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