Makoto Kawano

Ph.D. Student at Keio University | makora[at]ht.sfc.keio.ac.jp

ABOUT

Thank you for visiting.
My name is Makoto Kawano. I'm a Ph.D. student at Keio University, advised by Prof. Hideyuki Tokuda. I'm interested in Ubiquitous Computing and Artificial Inteligence. Currently, my research topics lie in the interaction between urban computing and deep learning. I'm also the member of deeplearning.jp.

EDUCATION

Bachelor of Arts in Environment and Information Studies
Keio University
4 Years Course

GRADUATED IN MARCH 2014

Master of Interdisciplinary Information Studies
The University of Tokyo
2 Years Course

GRADUATED IN MARCH 2016

Ph.D. in Media and Governance
Keio University
3 Years Course

GRADUATING IN MARCH 2019
IN PROGRESS



WORK

Research Assistant - Intern
Nippon Telegraph and Telephone Corp.

I have worked on estimating transportation mode. After surveying related works, I implemented recursive autoencoders and show the experiments results during internship.

AUGUST 2014 - SEPTEMBER 2014

Front-end & Server-side Engineer - Intern
CyberAgent, Inc.

SEPTEMBER 2014 - NOVEMBER 2014

Research Assistant - Intern
Yahoo Japan Corp.

FEBRUARY 2015 - JULY 2015

Research Fellowship for Young Scientists (DC1)
Japan Society for the Promotion of Science.

Awarded to excellent young researchers, these fellowships offer the fellows an opportunity to focus on a freely chosen research topic based on their own innovative ideas. Ultimately, the program works to foster and secure excellent researchers.

APRIL 2016 - RECENT

IN PROGRESS


PUBLICATIONS

International Conference Posters
Makoto Kawano, Takuro Yonezawa, Jin Nakazawa, Satoshi Kawasaki, Ken Ohta, Hiroshi Inamura, Hideyuki Tokuda. "Classifying urban events' popularity by analyzing friends information in location-based social network." Proceedings of the First International Conference on IoT in Urban Space. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 2014.

Domestic Journal
河野 慎, 米澤 拓郎, 中澤 仁, 川崎 仁嗣, 太田 賢, 稲村 浩, 徳田 英幸, “ソーシャルネットワークにおけるフォロー集合分析に基づく実世界イベント分類手法”, 情報処理学会論文誌,< Vol.56, No.1, pp.72-82A.

河野 慎, 遠藤 結城, 戸田浩之, 小池 義昌, 植田 一博: "Recursive Autoencoderにもとづいた移動軌跡からの特徴量自動抽出手法の提案", 日本データベース学会和文論文誌, Vol. 14(2016年3月発行),Article No. 12.

Domestic Other
河野 慎, 遠藤 結城, 戸田浩之, 小池 義昌, 植田 一博: "Recursive Autoencoderにもとづいた移動軌跡からの特徴量自動抽出手法の提案", 第7回データ工学と情報マネジメントに関するフォーラム (DEIM 2015), D5-5, 2015年3月2日~3月4日.

河野慎, et al. "イベント参加者のフォロー関係に基づくイベント分類手法の提案." 情報処理学会研究報告. MBL,[モバイルコンピューティングとユビキタス通信研究会研究報告] 2013.3 (2013): 1-6.

河野慎, et al. "自律型エージェントによるユーザの嗜好を多面的に反映した推薦システムの提案." 第 75 回全国大会講演論文集 2013.1 (2013): 397-398.

Awards
学生プレゼンテーション賞
河野 慎, 遠藤 結城, 戸田浩之, 小池 義昌, 植田 一博: "Recursive Autoencoderにもとづいた移動軌跡からの特徴量自動抽出手法の提案", 第7回データ工学と情報マネジメントに関するフォーラム (DEIM 2015), D5-5, 2015年3月2日~3月4日.


SKILLS

Python


Swift


Java


HTML/CSS


Javascript


Illustrator / Photoshop





-->
CONTACT

Email
makora[at]ht.sfc.keio.ac.jp

Address
5322, Endo, Fujisawa-shi
Kanagawa-ken, Japan

Phone
+80 466-47-0836

SOCIAL LINKS