We have 4 research topics as follows:
 Optimization-based data Analytics

This is to develop scheduling policies for either performance control (e.g., maximizing throughput) or logical control (e.g., avoiding deadlock), or for both of them, by considering some data obtained from system operation. Currently, we have two topics.

 AI in Manufacturing Industry
Based on our manufacturing domain knowledge, we converge with recently developed artificial intelligence technology to derive new solutions. It can be applied to various problems such as predictive maintenance, quality inspection, and manufacturing process optimization.

 XAI(Explainable AI)

Black box AI systems have spread to many of today’s applications. the intransparency of ML techniques may be a limiting or even disqualifying factor. Research on XAI(Explainable AI) is being actively conducted to overcome these black box models. XAI is a technology that enables users to understand and interpret the behavior and the results of an artificial intelligence system and explain the process by which the results are generated. Our lab is conducting a study to determine the cause of the result by using composition methodology to interpret the result of LSTM algorithm specialized in time series data.


 Blockchain Consensus Algorithm

A consensus algorithm is a procedure through which all the peers of the Blockchain network reach a common agreement about the present state of the distributed ledger. There are various approaches to reaching a consensus. Our lab compares these approaches with each other and optimizes them for the newly proposed algorithm.


Application Areas
Production Systems, Supply Chain Management, Service Systems, etc.