Making agriculture smarter through cross-cultural and interdisciplinary integration
To address climate change and ensure stable and sustainable food production and supply with limited land and water resources while preserving the environment, innovative breeding and advanced cultivation technologies are essential.
Among these, it is important to understand and model the relationship between crop phenotypes and genotypes as well as environmental factors (climate, soil, microbes, fertilizers, irrigation conditions, etc.).
Through modeling, it is expected that we can support efficient breeding by designing desired crop performance and optimal cultivation management by predicting crop responses under changing environments.
My expertise lies in a cross-disciplinary field called plant phenomics, which comprehensively analyzes and evaluates plant phenotypes.
Specifically, my education and research focus on the development and agricultural application of data sensing technologies using robots, drones, and satellites, as well as image processing, machine learning, and artificial intelligence-based data analysis, and their implementation in society.
Recently, the developed drone remote sensing technology for plant growth diagnosis has been widely used in production and breeding sites both in Japan and abroad.
Educational approach
To devote the whole of one’s youth to a meaningful pursuit.
I teach the knowledge necessary for collecting and analyzing data in agriculture.
For example, I teach basics of Matlab, Python programming, image analysis, machine learning, and deep learning through lectures and lab seminars.
I also oversee field ICT training where students experience cutting-edge smart agriculture technologies such as autonomous tractors and drones.
Because we promote numerous international collaborations and participation in international conferences, we also emphasize communication in English.
Our daily research activities and results are updated regularly here. https://lab.fieldphenomics.com/
We welcome students who want to work internationally, enjoy both fieldwork (plant cultivation management and data collection) and desk work (algorithm design and programming), and have stamina and passion.
Although research life may be tough, I believe you can grow beyond your limits.
I expect students to become next-generation researchers, engineers, leaders, and policymakers with interdisciplinary and international perspectives, broad vision, and strong execution skills to contribute to society.
Most students and postdocs who collaborated have advanced to IT companies interested in agriculture, or research institutes and universities overseas.
Vision for industry-academia collaboration
A diverse set of revolutions is needed to solve global food challenges!
In recent years, the introduction of information science and technology such as AI into agriculture has become a major focus of agricultural policies worldwide, and private companies are also promoting smart agriculture.
Developing countries are no exception.
In response, many countries have introduced various policies to foster human resources to support this trend.
Our laboratory conducts research through flexible and close interdisciplinary collaboration with faculty specializing in diverse fields such as breeding, crop cultivation, plant pathology, environmental conservation, plant evolution, statistics, and information science, from the standpoint of agricultural informatics.
We also conduct many joint research projects with companies.
We are also actively working to disseminate research results to agricultural research institutes of local governments.
We welcome inquiries from companies or organizations interested in joint research and social implementation of technologies such as agricultural remote sensing with drones and robots, image analysis, AI-based plant phenotyping, and pipeline development.
Please also see the related page [Press releases] here: https://www.u-tokyo.ac.jp/focus/ja/people/k0001_01967.html
