Deeksha Arya

Affiliation: Specially Appointed Assistant Professor, The University of Tokyo, Japan

Contact information: Deeksha@csis.u-tokyo.ac.jp

Brief bio: Dr. Deeksha Arya holds a Ph.D. from the Indian Institute of Technology Roorkee, India. A prolific contributor to international conferences and journals, Dr. Arya is renowned for organizing significant events such as the IEEE BigData Cups' Global Road Damage Detection Challenges, which captured worldwide attention. She also served as the Chair of Data Cup challenges for the IEEE International Conference on Big Data’2023. Her research expertise spans Data Mining, Big Data Analytics, Deep Learning, and Intelligent Transport Systems, reflecting her diverse and impactful contributions. More details about her work are available here.

ORCID: 0000-0002-7948-5930

Hiroya Maeda

Affiliation: CEO, UrbanX Technologies, Inc., Tokyo, Japan

Contact information: hiroya_maeda@urbanx-tech.com

Brief bio: Dr. Hiroya Maeda holds a Ph.D. from the University of Tokyo, Japan. He is the Founder and CEO of UrbanX Technologies, inc., the company leading the AI-driven road inspection in Japan. More details about his work are available here.

ORCID: 0000-0003-2789-4019

Hiroshi Omata

Affiliation: Project Researcher, The University of Tokyo, Japan

Contact information: homata@csis.u-tokyo.ac.jp

Brief bio: Hiroshi Omata is a Project Researcher at the University of Tokyo. He has been working on software developments for more than a decade and holds a specialization in digital signal processing of audio, web-based technology, and engagement of civic technology communities. He leads the civic technology communities and open data communities in Japan. More details about his work are available here.

Yoshihide Sekimoto

Affiliation: Professor, The University of Tokyo

Contact information: sekimoto@csis.u-tokyo.ac.jp

Brief bio: Dr. Yoshihide Sekimoto is the Director of the Centre for Spatial Information Science, the University of Tokyo. He has a burning enthusiasm to resolve social problems that become complicated by advanced spatial information processing. His study covers a wide range of topics, including the prediction of mass people movement, urban planning support by fusion of various urban data, and construction of distribution infrastructure for social infrastructure data. Further details about Dr. Sekimoto are available here.

ORCID: 0000-0003-0305-7056

Student Coordinators:

• Chenbo ZHAO
• Lingfeng LIAO
• Shubham DWIVEDI
• Zhehui YANG