Associate Professor Watanabe: I specialize in algorithms related to optimization and data mining. In particular, I am researching the development of solutions to problems that consider multiple criteria, known as "multi-objective optimization," and methods for mining the results.
We also analyze and propose solutions tailored to the needs of companies, such as optimizing low-cost, high-quality production environment models. From the perspective of food and agriculture, we are involved in creating models for greenhouse cultivation of vegetables. One company with which Muro Institute of Technology has a comprehensive collaboration agreement cultivates tomatoes as part of its business in a greenhouse the size of two to three gymnasiums.

Tomatoes shipped to supermarkets and other stores will be lost if they are more or less than the number of tomatoes contracted several weeks before, so accurate yield prediction is required. There is also the problem of how to accurately observe the conditions within the vast farm and cultivate appropriately according to those conditions. In this joint research, we are working on such yield predictions, condition estimation, and cultivation management using AI and IoT technologies.

Professor Tokura: My main research theme is protein aggregation, which can cause various diseases. For example, Alzheimer's disease is caused by the accumulation of proteins called "amyloid beta" and "tau" in the brain, which leads to neuronal death. I am using my own bio-nano imaging technology and AI to analyze how these proteins accumulate and cause neuronal death, and how we can prevent this.

Furthermore, we are working with companies to analyze foods that cause lifestyle-related diseases and, conversely, to develop foods with functionality that suppresses certain diseases. Professor Watanabe is working on a tomato production model, and I am working on improving the functionality of tomatoes to increase their added value. Although we are each involved in different projects, we hold regular meetings and work together on our research.

Associate Professor Watanabe: In my field of research, advances in equipment and IoT technology have made it possible to measure and analyze quickly and at low cost, even when using AI, which previously required time and cost.
Currently in the field of AI technology, "deep learning," in which machines automatically learn and derive answers, is attracting attention, but there are still challenges to its use, such as the inability to explain why a given answer was derived.

In the future, it will be important to develop machine learning models known as "X (Explainable) AI," which can explain to humans the process that leads to prediction or inference results, and I would like to work toward developing this.