People

Who we are



Kangil Kim | Professor

Associate Professor,
School of Electrical Engineering & Computer Science,
Gwangju Institute of Science and Technology(GIST)

email: kangil.kim.01[at]gmail[dot]com / kikim01[at]gist[dot]ac[dot]kr
CV

Research Interest

generally applicable intelligence model representation, optimization and regularization, model complexity, probabilistic and representation analysis.

Research Area

artificial intelligence, machine learning, evolutionary computation, neural network, probabilistic graphical model, statistical relation learning, logic and grammar model, genetic programming, natural language processing

Education

2012 Ph.D in Computer Science and Engineering, SNU
2006 B.S. in Computer Science, KAIST

Experience

2022~present Associate Professor, GIST, AI Graduate School
2019~2022 Assistant Professor, GIST, EECS
2016~2019 Assistant Professor, KU, CSE
2013~2016 Senior Researcher, ETRI, AI and NLP
2012~2013 Postdoc Researcher, SNU, Structural Complexity Lab
2011 Visiting Researcher, UPM, Artificial Intelligence Group
2008 Research Intern, NII

Publications

  • Selected
    • I. Kang, H. Bae, and K. Kim. “Label-Focused Inductive Bias over Latent Object Features in Visual Classification”, ICLR 2024, To be appeared.
    • H. Kim, and K. Kim. “Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation”, ICLR 2024, To be appeared.
    • H. Kim, and K. Kim. “Spherization Layer: Representation Using Only Angles”, NeurIPS 2022.
    • H.-J. Jung, D. Kim, S.-H. Na, and K. Kim. Feature structure distillation for bert transferring. arXiv preprint arXiv:2204.08922, 2022
    • S. Woo, J. Noh, and K. Kim. Tackling the challenges in scene graph generation with local-to-global interactions. IEEE Transactions on Neural Networks and Learning Systems, 2022.
    • S. Woo, J. Noh, and K. Kim. What and when to look?: Temporal span proposal network for video visual relation detection. arXiv preprint arXiv:2107.07154, 2021.
    • K. Kim, Y. Jin, S. Nah, and Y.-K. Kim. Center-shared sliding ensemble of neural networks for syntax analysis of natural language. Expert Systems with Applications, 83:215–225, 2017.
    • K. Kim, R. B. McKay, and N. X. Hoai. Recursion-based biases in stochastic grammar model genetic programming. IEEE Transactions on Evolutionary Computation, 20(1):81–95, 2016.
    • K. Kim, Y. Shan, X. H. Nguyen, and R. I. McKay. Probabilistic model building in genetic programming: a critical review. Genetic Programming and Evolvable Machines, 15(2):115–167, 2014.
    • K. Kim and R. I. McKay. Stochastic diversity loss and scalability in estimation of distribution genetic programming. IEEE Transactions on Evolutionary Computation, 17(3):301–320, 2013.
  • (all) links: google scholar, research gate

Main Projects

  • Model Analysis
    2022~2027 Representation Analysis for Learning Canonicalized Representations (NRF)
    2019~2021 Neural Networks for General Knowledge Accummulation (GIST, NRF)
    2016~2016 Improvement of Expression Power of Infinite Probabilistic Context Free Grammar (NRF)
    before 2013 Bias analysis of probabilistic context free grammar models in estimation of distribution algorithm in genetic programming (in PhD program, NRF)
    2019~2021 Neural Networks for General Knowledge Accummulation (GIST, NRF)
  • Natural Language Processing
    2016~2020 Real-time multilingual machine translation (ETRI)
    2013~2016 Multilingual machine translation (ETRI)

Review Service

IEEE Transactions on Neural Network and Learning Systems
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Audio, Speech and Language Processing
Expert Systems With Applications
NeuRIPS, ICLR, ACL, EMNLP

Acronyms

GIST (Gwangju Institute of Science and Technology, Korea)
ETRI (Electronics and Telecommunications Research Institute, Korea)
UPM (Polytechnic University of Madrid, Spain)
SNU (Seoul National University, Korea)
NII (National Institute of Informatics, Japan)