Prof. Toyo (Toyotaro) Suzumura

Short Introduction

Full Bibliography

 He is a full professor at the Graduate School of Information Science and Technology, the University of Tokyo since April 1st, 2021. Until March 2021 -  prior to moving to academia, he was a principal research scientist and global lead of scalable graph learning project and the Future of Computing initiative at the headquarter of IBM Research, namely IBM T.J. Watson Research Center located in New York, USA. He led the worldwide team of more than 50 world-class top scientists in the area of artificial intelligence, big data, high-performance computing, large-scale graph analytics in IBM Research and led the Research Strategy for Financial Service Research as well. He also served as a principal investigator for the MIT-IBM Watson AI Lab project with Prof. Charles Leiserson from MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). He currently also serves as a visiting full professor at the national laboratory in Spain – named Barcelona Supercomputing Center in Spain.            

 He has broad knowledge and experience in the research and development of artificial intelligence, machine learning, large-scale graph analytics/learning, broader coverage of computer science areas including big data processing in large-scale distributed systems, parallel and distributed middleware, and its application to real-time data stream computing, large-scale graph processing, cloud computing, and various performance optimization technologies, design and implementation of dynamic scripting languages and object-oriented parallel language and large-scale traffic simulation.

 Prof. Suzumura had worked for IBM Research since 2004 for 17 years after finishing his Ph.D. in 2004 in the area of Cloud/Grid and supercomputing fields at Tokyo Institute of Technology in Japan.  During his 17 years in IBM Research, as a dual-appointment, he had been also appointed as a visiting associate professor at Tokyo Institute of Technology since 2009 and supervising 16 graduate students in his own laboratory “Suzumura Laboratory” and also a visiting associate professor of University College Dublin in Ireland since 2014/04 supervising 10 master students and 3 Ph.D. students.  Since 2013/10, He had worked for IBM Research – Ireland, the R&D headquarter of IBM Research in Europe as an international assignment specifically focusing on a variety of Smarter-Cities related technologies. Since April 2015, He joined the headquarter of IBM Research named IBM T.J. Watson Research Center in New York, the USA as a full-time research scientist.   

 He has published over 90 reviewed research papers including top-quality international conferences and workshops as well as serving program committee chairs and members for top-tier big data and AI conferences. His notable accomplishment is that he won the 1st place

Recent Academic Activities as Program Committee Members 

• Artificial Intelligence and Data Mining

  • Association for the Advancement of Artificial Intelligence - AAAI  (URL) (2024, 2022, 2021, 2019) 

  • IEEE International Conference on Machine Learning and Applications (ICMLA 2023, 2022, 2021) 

  • ACM International Conference on AI in Finance (URL) (2023, 2022, 2021, 2020)

  • IEEE BigData (2023, 2022, 2021, 2018, 2017, 2016, 2013)

• High-Performance Computing and Cloud Computing 

  • ACM/IEEE Supercomputing (2022, 2021, 2019, 2016, 2015, 2014)

  • IEEE IPDPS (2021) , IEEE HiPC (2022) 

  • IEEE Cloud (2010,2011,2012,2013,2014,2015,2016, 2017,2018,2019) 

  • IEEE ICWS(International Conference on Web Services) (2014,2015,2016,2017, 2018, 2019)

This is an open-ended topic that every researcher should deeply think about at all times.  Let me take a note of my current policy as of Oct 18, 2021, with regards to how I can decide research themes.    This policy might change every year, and I believe that this should be.  

Before fully joining academia in April 2021, I had been with IBM Research for 17 years after I got my Ph.D. in 2004. And also in the past 8 years, I had been in Europe and United States. I learned a lot from one of the top computer science research institutes - IBM Research.  It is well known that it is difficult to continue to maintain basic research labs in any industry since one of the important KPIs for industries is profits.   Balancing profits and pursuing basic research is a pretty challenging problem. 

From my experiences at IBM Research, research problems and themes had been decided by thoroughly discussing what could be groundbreaking things for our society and also their clients. Thus,  research themes and directions were decided in a top-down manner. Sometimes innovative research ideas should come in a bottom-up manner without thinking of any real applications in society, but this might be rare. If you think about what computer science is, it should always be tied to its applications and impacts on real-world societies.  Any kind of outcome from computer science should be the fundamental basis for advancing real applications.  

This is my current research style as of writing in April 2021, but nobody knows how it might change every year.  Thus, even if I move to academia and supervise students and work with collaborators, one of the most important points for me is what could be real values for our real-world societies. We need to continue to ask ourselves all the time whether our research themes are not only for publishing to top-tier conferences but also give big impacts to societies. We should not set up research themes only for publications.  This should be common sense that we can agree upon among senior researchers, but I can see this sometimes happening for young researchers who feel pressure to have more papers to move up to the next level of their careers.  I will be continuing to add my thoughts in research styles, but there is no clear answer. That's for sure. That's why it is always important to continue to think about the reasons for what you are working on.  

My ongoing experiments in Tokyo as a global career (Nov, 2021) - shifting from Industry to fully Adacemia

After spending around 8 years in Europe and the United States, I decided to relocate to Tokyo from New York City due to the pandemic situation in 2020. Although it did not matter with COVID or not, I had been feeling that where you live and work does NOT matter for computer scientists. Thus I started to think about whether I should continue to stay in New York City where the pandemic gave strong damage. I managed to obtain a permanent residency or green card and was supposed to live and work in the US longer but the pandemic situation made me seriously start to think that I should not stick to the US and should relocate to a city where I can feel safer and comfortable to live and work.

Around June 2020, I decided to relocate to Tokyo. Then after exploring some job opportunities, I got back to Tokyo at the end of March 2021. Although I finally went to the US  and worked there - especially for the respectful (still love it) research institute - IBM T.J. Watson Research Center, the headquarter of IBM Research,  which I was dreaming of for a long time since I was a grad student. One aspect of my goals got achieved in that I was able to do and lead various exciting projects that I had thought of, but my intuition told me that I should move to the next step in my career.

Now I am in Tokyo. To me, as previously mentioned, where you live does not matter and should not matter. So wherever you live, you can connect to respectful researchers all over the world if you look in the same direction - using online communication tools obviously - without working with them at the same physical location. Life is a journey and nobody can change or ask how and where you live. It’s your life. I will enjoy life and work in Tokyo at this moment.   (Noted: Nov 2021, Tokyo)