Heechang Ryu

My Google Scholar, Linkedin

Please send me an email if you want my CV. (heechang.ryu21@gmail.com)

KAIST Ph.D.

I am working on developing AI and ML algorithms that can be used in a variety of engineering systems.

My keywords are as follows:

Machine Learning

• Multi-agent reinforcement learning • Deep reinforcement learning • Deep learning model optimization

Application

• Robot control • Service recommendation • Energy storage system control

• Renewable energy prediction • Fab scheduling/logistics • Anomaly detection

Programming Skills

Over 5,000 lines: • Python • C/C++ • TensorFlow • PyTorch • Matlab

Over 1,000 lines: • Kotlin • C# • Lua

Publications' highlights

REMAX: Relational Representation
for Multi-Agent Exploration

Ryu H., Shin H., and Park J., “REMAX: Relational Representation for Multi-Agent Exploration,” In Proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), pp. 1137-1145. 2022. (acceptance rate: 26%)

Paper

Cooperative and Competitive Biases
for Multi-Agent Reinforcement Learning

Ryu H., Shin H., and Park J., “Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning,” In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), pp. 1091-1099. 2021. (acceptance rate: 24.8%)

Paper

Multi-Agent Actor-Critic
with Hierarchical Graph Attention Network

Ryu H., Shin H., and Park J., “Multi-Agent Actor-Critic with Hierarchical Graph Attention Network,” In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), pp. 7236-7243. 2020. (acceptance rate: 20.6%)

Paper

Does Adam Optimizer Keep
Close to the Optimal Point?

Bae K.*, Ryu H.*, and Shin H. (* Co-first author), “Does Adam Optimizer Keep Close to the Optimal Point?,” NeurIPS2019 Workshop on Beyond First Order Methods in ML. 2019.

Paper

Multi-Agent Actor-Critic
with Generative Cooperative Policy Network

Ryu H., Shin H., and Park J., “Multi-Agent Actor-Critic with Generative Cooperative Policy Network,” arXiv preprint arXiv:1810.09206. 2018.

Paper

Energy Storage Control Based on User Clustering
and Battery Capacity Allocation

Ryu H., Jung Y., and Park J., “Energy Storage Control Based on User Clustering and Battery Capacity Allocation,” IEEE Power & Energy Society General Meeting, pp. 1-5. 2017.

Paper

Classification of Heart Sound Recordings
Using Convolution Neural Network

Ryu H., Park J., and Shin H., “Classification of Heart Sound Recordings Using Convolution Neural Network,” Computing in Cardiology Conference (CinC), pp. 1153-1156. 2016.

Paper