9th November | 14:20~15:30

[Global Leaders Panel]

Global Leadership in Diverse Team

 

[Panelists]

Masato Murakami
President, Shibaura Institute of Technology

He received Doctor of Engineering from Graduate School of Engineering, University of Tokyo in 1984. He joined Research Laboratories I, Nippon Steel Corporation in 1984. He was appointed as Director of Division VII, Superconductivity Research Laboratory in 1993. He became Professor, Department of Materials Science and Engineering, Shibaura Institute of Technology in 2003. He has been President, Shibaura Institute of Technology since 2012. He was awarded several prizes including 1991 Nikkei BP Prize, 1992 World Congress Superconductivity Award of Excellence, 2000 Superconductor Science and Technology Award, and 2003 PASREG Special Award. He authored 1097 scientific papers with 23239 citations.

 

Fumie Saito
UN Women Japan Liaison Office

Fumie Saito works at UN Women Japan Liaison Office as a Partnership and Resource Mobilization Specialist. Before joining in UN Women, she worked in UNFPA Nepal as a Monitoring and Evaluation Specialist. Formerly a Senior Policy Coordinator for the State Minister on Gender Equality and a nationally certified senior legislative aide to parliamentarians in Japan, she successfully navigated various public policies and legislation on women’s and children’s rights such as gender-based violence and child prostitution. She has over 15 years of experience working on public policies and projects in the field of gender equality and women’s rights in both national and international settings. She has worked in different sectors, including media, academia, international and national NGOs and the government. Fumie holds two Masters’ degrees: Public Policy with a concentration in Women’s Studies (George Washington University, USA); and, International Human Rights Law (University of Essex, UK), as well as a Juris Doctor from Waseda University, Japan.

 

Xinmei Cai
Engineering Director, Google

After working as a software engineer in Microsoft and subsequently a Silicon Valley startup for 4+ years, Xinmei joined Google Mountain View in November 2004. She later became the Tech Lead of AdWords International Forms of Payments team. She was appointed Engineering Ambassador and moved to Tokyo in October 2007. Xinmei built up YouTube Japan engineering team in the next four years, where she was responsible for two global focused teams, YouTube Mobile Web and YouTube Search. In mid 2012, she joined Google Maps for Mobile, and led the team to launch the award winning Google Maps on iPhone in December 2012 followed by a complete redesign of the Google Maps on Android and iOS in July 2013. She leads Geo Engineering site in Tokyo, and her mission is to make user generated content such as photos and reviews a vital part of Google Maps. She held B.A. from Middlebury College. While working at Google, Xinmei completed M.S. in Software Engineering at Carnegie Mellon University.

 

[Moderator]

Takako Hashimoto
Vice President, Chiba University of Commerce

Takako Hashimoto graduated from the Ochanomizu University, and received a Ph.D. in computer science, specialization in multimedia information processing, from the Graduate School of Systems and Information Engineering of University of Tsukuba in 2005. She worked at the software R&D center of Ricoh Co. Ltd., in Japan for 24 years, and participated in the development of many software products as a technical leader. From April of 2009, she was involved in Chiba University of Commerce as Associate Professor. In 2015, she has become Professor of Chiba University of Commerce. In 2015, she stayed at University of California, Los Angeles as a visiting researcher. She has become Director of Institute of Economic Research, Chiba University of Commerce in 2016 and the Vice President of Chiba University of Commerce in 2018. Currently, she has focused on the data mining research and the social media analysis, especially topic extraction from millions of tweets related to severe disasters. She is developing the high performance feature selection technique for big data.