About
Kentaro Kuwata
Data scientist, analyzing satellite data and IoT environment data (e.g. weather, soil, etc.) of over terra-byte class to contribute solving environmental problems.
Enjoying private coding such as algorithm trading.
Work
- Constructed a data platform integrating various types of satellite data to provide image data to customers in near-real time by using Django framework on AWS
- Developed a yield prediction model for one of the largest U.S. wine makers by using machine learning
- Developed a fusion methodology simulating soil moisture percolation by using IoT sensor data, basic soil sciences and machine learning
- Analyzed satellite data and other IoT environmental data to evaluate crop water stress
- Analyzed TerraSAR-X (German Earth-observation satellite) data for the field of agriculture and disaster management. Extracting data to assess the conditions of areas stricken by flood and typhoons in Thailand and Japan
- Feasibility study of Japanese small satellite system transportation to foreign country in the Middle East (UAE and Saudi Arabia). Researched satellite market and usage in Abu Dhabi and Saudi Arabia
Computer skills
- OS: Ubuntu, Mac, Windows 10
- Programming: Python, Shellscript, Scala
- GIS: QGIS, PostGIS
- Environment: Docker, PyCharm Professional
- Python library: GDAL, rasterio, scikit-learn, Django, numpy, pandas, matplotlib, jupyter, Pytorch
- Scala library: Spark, Slick, geotrellis
- Database: PostgreSQL
Academic
Doctoral thesis:
A study of development of agricultural insurance using satellite data and deep learning
Conference
- “Estimating corn yield in the United States with MODIS EVI and machine learning methods”, Kuwata, K., Shibasaki, R., International Society for Photogrammetry and Remote Sensing 2016, Prague, Czech Republic.
- “Estimating crop yield with deep learning and remotely sensed data”, Kuwata, K., Shibasaki, R., 2015 IEEE Geoscience and Remote Sensing Society, the International Geoscience and Remote Sensing Symposium 2015, Milan, Italy.
- “Weather index for crop insurance to mitigate basis risk”, Kuwata, K., Mahmood, F., Shibasaki, R., IEEE Geoscience and Remote Sensing Society, the International Geoscience and Remote Sensing Symposium 2015, Milan, Italy.