We accept undergraduate students from the Department of Information Science, Faculty of Science, and graduate students from the Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo.

In our laboratory, we aim to develop machine learning techniques that solve real-world problems. In particular, we would like to study with the following objectives.

Dr. Allen Newell, an artificial intelligence researcher, who often appeared in Prof. Takeo Kanade's talk, describes his research style as follows.

"Good science responds to real phenomena or real problems."

"Good science is in the details." 

"Good science makes a difference."  

From CMU site  

We aim to achieve this style of research.

Since the world of researchers is dominated by peer evaluation among researchers, research easily fall into  "research for research's sake," e.g., solving special cases that unnecessarily complicate problems and increase conditions. 

In our laboratory, we aim to clarify the problems to be solved in society and give solutions by abstracting them appropriately. 

Therefore, the discovery of novel problems, "what kind of problems to solve", is more important than "how to solve them using advanced mathematics." 

However, we do not consider "problems that can be solved using existing methods"  new problems. A problem that requires a technically new (sometimes using advanced mathematics) method to solve the problem is considered important as a "new problem". 

The problem should be rooted in society's awareness of the issues. We need to avoid providing a solution such as we dig our own holes and fill them.

The moment of "connecting the dots" in research is a great experience that can not be obtained anywhere else. Let's create such moments with researchers around the world.