Yasumasa Tamura, Ph.D.

Assistant Professor at School of Computing, Tokyo Institute of Technology

Research Fields	Swarm Intelligence, Computational Intelligence, Machine Learning, Optimization, Distributed Systems
Place of Birth	Hokkaido, Japan
Nationality	Japan
Languages	Japanese (native), English

Education

April 2014 - March 2015	Ph.D. in the field of Computer Science and Information Technology Graduate School of Information Science and Technology, Hokkaido University, Japan
April 2012 - March 2014	Master of Computer Science and Information Technology Graduate School of Information Science and Technology, Hokkaido University, Japan
April 2008 - March 2012	Bachelor of Engineering School of Enginnering, Hokkaido University, Japan

Work Experience

April 2017 - present	Assistant Professor School of Computing, Tokyo Institute of Technology, Japan
March 2016 - February 2017	Visiting Postdoctoral Researcher IRIDIA, Université Libre de Bruxelles, Belgium
April 2015 - March 2017	Research Fellow (PD) of the Japan Society for the Promotion of Science (JSPS) Graduate School of Information Science and Technology, Hokkaido University, Japan
April 2014 - March 2015	JSPS Research Fellow (DC1) Graduate School of Information Science and Technology, Hokkaido University, Japan

Grants

April 2017 - (March 2021)	Grant-in-Aid for Young Scientists (B): 3,500,000 JPY 17K12734: "Swarm Learning for Deep Neural Networks"
April 2015 - March 2017	Grant-in-Aid for JSPS Fellow (DC1, PD): 2,500,000 JPY 26-1342: "Rule-based Neighborhood Search for Large Scale Scheduling Problem"

Project

Collaborative Learning based on Collective Decision Making

April 2017 - present, Tokyo Institute of Technology (Japan)

Keywords: Swarm Intelligence, Deep Neural Networks, Collaborative Learning

TBU

This project is supported by JSPS KAKENHI, Grant-in-Aid for Young Scientists (B), No. 17K12734, from April 2017.

Kilogrid (Collaboration)

March 2016 - February 2017, Université Libre de Bruxelles (Belgium)

Keywords: Swarm Intelligence, Swarm Robotics, Collective Decision Making

Kilogrid is a modular virtualization environment for the kilobot robots. It is developped under Prof. Marco Dorigo's supervision at IRIDIA, Université Libre de Bruxelles.

Link: Official project page

Dynamic Rule Applied Metaheuristics for Large Scale Scheduling Problems

April 2012 - March 2017, Hokkaido University (Japan)

Keywords: Combinatorial Optimization, Heuristics, Metaheuristics, Scheduling

This project proposed several solution algorithms for scheduling problems. The algorithms are based on meta-heuristics and classical heuristic rules which also optimized dynamically while searching for candidate solutions.

This project was supported by JSPS KAKENHI, Grant-in-Aid for JSPS Fellows, No. 26-1342, from April 2014 to March 2017.

Publication

Selected Papers

Yasumasa Tamura, Hiroyuki Iizuka, Masahito Yamamoto, Masashi Furukawa: Application of Local Clustering Organization to Reactive Job-shop Scheduling, Soft Computing, Springer, Vol. 19, Issue 4, pp. 891-899, 2015.
Yasumasa Tamura, Masahito Yamamoto, Ikuo Suzuki, Masashi Furukawa: Acquisition of Dispatching Rules for Job-shop Scheduling Problem by Artificial Neural Network with PSO, Journal of Advanced Computational Intelligence and Intelligent Informatics, Fuji tech. press, Vol. 17, No. 5, pp. 731-738, 2013.
Yasumasa Tamura, Ikuo Suzuki, Masahito Yamamoto, Masashi Furukawa: The Hybrid Approach of LCO and SA to Solve Job-shop Scheduling Problem, Transactions of the Institute of Systems, Control and Information Engineers, Institute of Systems, Control and Information Engineers, Vol. 26, No. 4, pp. 121-128, 2013.

International Conferences

Yasumasa Tamura, Xavier Défago: Collective Learning with Deep Neural Networks, Proceeding of the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM2017), pp. 167-168, Kyoto (Japan), 2017.
Yasumasa Tamura, Hiroyuki Iizuka, Masahito Yamamoto: Extended Local Clustering Organization using Rule-Based Neighborhood Search for Job-shop Scheduling Problem, Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Vol. 2, pp. 465-477, Singapore, 2014.
Yasumasa Tamura, Hiroyuki Iizuka, Masahito Yamamoto, Masashi Furukawa: Application of Local Clustering Organization to Reactive Job-shop Scheduling, Proceedings of the 14th International Symposium on Advanced Intelligent Systems (ISIS 2013), T1f-4, Deajeon (South Korea), 2013.
Yasumasa Tamura, Ikuo Suzuki, Masahito Yamamoto, Masashi Furukawa: The Hybrid Approach of LCO and SA to Solve Job-shop Scheduling Problem, Proceedings of the ASME/ISCIE 2012 International Symposium on Flexible Automation (ISFA 2012), 7226, St. Louis (MO, USA), 2012.

Theses

Yasumasa Tamura: Studies on Advanced Metaheuristics employing Local Clustering for Job-shop Scheduling Problem, Ph.D. (Computer Science), Hokkaido University, 2015.
Yasumasa Tamura: Learning of Dispatching Rules and Its Application to Searching Algorithms for Job-shop Scheduling Problem, Master of Computer Science, Hokkaido University, 2014. (Japanese)

Contact

	tamura(at)c.titech.ac.jp
	+81-(0)3-5734-2772
	+81-(0)3-5734-2772
	W8-84, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan (Office: West Bldg. 8E, 8th Floor, Room E804)

	tamura.yasumasa
	Yasumasa Tamura
	github.com/tamy0612
	Research map