Chris Dongjoo Kim
Scholar

Chris Dongjoo Kim

Google Scholar ID: SzLOAE8AAAAJ
Ai2
Machine LearningData QualityMultimodal dataReal-time Post-Training
Citations & Impact
All-time
Citations
1,272
 
H-index
7
 
i10-index
7
 
Publications
11
 
Co-authors
10
list available
Resume (English only)
Academic Achievements
  • Selected publications include 'ReSpec: Relevance and Specificity Grounded Online Filtering for Learning on Video-Text Data Streams' and several others in conferences such as CVPR, NeurIPS, ICCV, ECCV, etc.; Awards include Seoul National University CSE Best Ph.D Thesis Award, YoulChon AI Star Fellowship, Naver Ph.D. Fellowship, etc.
Research Experience
  • Full-time research engineer working on large omnimodal models at Ai2; Allen Institute for Artificial Intelligence (Feb. 2024 - Present); LG AI Research (Sep. 2024 - Apr. 2025); NALBI (Mar. 2021 - Sep. 2021); LUNIT (Sep. 2016 - Dec. 2017)
Education
  • Ph.D in Computer Science and Engineering, Seoul National University, Advisor: Professor Gunhee Kim; M.S in Computer Science and Engineering, Seoul National University, Advisor: Professor Gunhee Kim; B.S. in Computer Science and Economics, University of Toronto
Background
  • Interest in making machine reasoning accountable to the world—grounded in vision and language. The current emphasis is on the training data and evaluation needed to support this behavior at scale.
Miscellany
  • Canadian who loves nature and especially fond of animals. On spare time, likes to swim and do CrossFit