PhD candidate at KAIST AI


About me

I’m an PhD candidate in the Kim Jaechul Graduate School of AI at Korea Advanced Institute of Science and Technology (KAIST AI), advised by Prof. Se-young Yun. Prior to beginning of my PhD course, I worked as a research engineer at Samsung Heavy Industires. I recieved an M.S. in Ocean system engieerning from KAIST under the supervision of Prof. Hyun Chung and B.S in Industrial engineering at Konkuk University. My research interests focus on meta-learning, bayesian models, implicit neural representation, neural rendering, multi-agent reinforcement learning and their applications. Here is my CV.

Contact

Email : callingu [at] kaist.ac.kr


Research experience


[2014~2019] Research engineer at Samsung Heavy Industries
[2023] Research Intern at NAVER Cloud AI Lab.



Awards


[2021] 2nd Winner in Student track at Machine Learning for Combinatorial Optimization Challenge (ML4CO) in NeurIPS2021 (Team : KAIST_OSI, Team leader).
[2016] Outstanding Project for Increasing Productivity at Samsung Heavy Industires.



Conference Publications (Peer reviewed)


Neural Processes with Stochastic Attention: Paying more attention to the context dataset
[paper][code][video]
Mingyu Kim, Kyeong Ryeol Go and Se-Young Yun
International Conference on Learning Representations (ICLR) 2022, Virtual



Workshop Publications (Peer reviewed)


The StarCraft Multi-Agent Challenges+ : Learning Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
[paper][code][projectpage]
Mingyu Kim*, Jihwan Oh*, Yongsik Lee, Joonkee Kim, SeongHwan Kim, Song Chong and Se-Young Yun
AI for Agent Based Modeling Workshop(Spotlight) in International Conference on Machine Learning (ICML) 2022, Baltimore

AVATAR: AI Vision Analysis for Three-dimensional Action in Real-time
Daegun Kim*, Jineun Kim*, Wongyo Jung*, Jungoon Park*, Mingyu Kim*, Anna Shin, Yong-Cheol Jeong, Seahyung Park, Gwanhoo Shin, Yewon Lee, Jea Kwon, Daesoo Kim
CV4Animals Workshop in Computer Vision and Pattern Recognition Conference (CVPR) 2022, New Orleans

Neural Processes with Stochastic Attention: Paying more attention to the context dataset
[paper][code]
Mingyu Kim, Kyeong Ryeol Go and Se-Young Yun
5th Meta-learn Workshop in Neural Information Processing Systems (NeurIPS) 2021, Virtual



Journal Publications (Peer reviewed)


The StarCraft Multi-Agent Exploration Challenges : Learning Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
[paper][code][projectpage]
Mingyu Kim*, Jihwan Oh*, Yongsik Lee, Joonkee Kim, SeongHwan Kim, Song Chong and Se-Young Yun
IEEE Access, 2023

Simplified welding distortion analysis for fillet welding using composite shell elements
[paper]
Mingyu Kim, Minseok Kang and Hyun Chung
International Journal of Naval Architecture and Ocean Engineering, Vol. 7(3), 2015

Meta-learning Amidst Heterogeneity and Ambiguity
[paper]
KyeongRyeol Go, Mingyu Kim, and Se-young Yun
IEEE Access, 2022

Optimization of P.E area division and arrangement based on product mix
[paper]
Sanghwan Kim, Mingyu Kim and Hyun Chung
Journal of Marine Science and Technology, Vol. 19(4), 2014

Optimization of Quantity Allocation using Integer Linear Programming in Shipbuilding Industry
[paper]
Junggoo Park, Mingyu Kim
Journal of the Society of Naval Architecture of Korea (Domestic), Vol. 57(1), 2020

A Study on Process Management Method of Offshore Plant Piping Material using Process Mining Technique
[paper]
Junggoo Park, Hojung Kim, Mingyu Kim, Jichan Park
Journal of the Society of Naval Architecture of Korea (Domestic), Vol. 56(2), 2019

A Study on the Installation Readiness Management Method of Offshore Plant using CAD Information
[paper]
Junggoo Park, Hojung Kim, Mingyu Kim, Jichan Park
Journal of the Society of Naval Architecture of Korea (Domestic), Vol. 56(2), 2019

A Study on the Utilization Strategy of Social Commerce in Small Restaurants
[paper]
Sungseok Ko, Mingyu Kim, Yungjin Yoo, Seoksul Kim
Journal of the Society of Korea Industrial and Systems Engineering (Domestic), Vol. 35(1), 2012



Academic Services


[Conference Reviewer] NeurIPS2022, ICLR2023
[Workshop Reviewer] MetaLearn in NeurIPS2021