Department of Informatics, Faculty of Information Science and Electrical Engineering
Department of Information Science and Technology, Graduate School of Information Science and Electrical Engineering
Department of Electrical Engineering and Computer Science, School of Engineering
Automated Reasoning is a key technique in intelligence science and technology. It is expected to be applied to a wide range of fields including hardware/software verifications, supporting legal reasoning, and so on. Currently, we are developing efficient automated reasoning systems such as SAT/MaxSAT solvers and their applications. We have tackled the following problems including large-scale combinatorial problems: Ramsey problem, scheduling problem, correcting errors in AES key schedule images, coalition structure generation problem, and inductive logic program.
Nowadays, various data are collected every day. Many machine learning techniques have been developed so far. We would like to practically show the effectiveness of these techniques using real data. Currently, we are working on the following two applications: classification of several objects in microscopic images of body fluids and anomaly detection for factory equipments.