KOBAYASHI Ryota
(Associate Professor/Division of Transdisciplinary Sciences)
Department of Complexity Science and Engineering/Data Science, Time series analysis, Complex systems
Career Summary
2004: Graduated from Faculty of Science (Kyoto University)
2009: Received Ph.D (Physics and Astronomy) from Kyoto University
2009: Assistant Professor (Ritsumeikan University)
2011: Visiting Researcher (Czech Academy of Sciences)
2013: Assistant Professor (National Institute of Informatics)
2015: Visiting Researcher (University of Namur)
2020: Associate Professor (University of Tokyo)
Research Activities
Event time series analysis (2013-present):
We focus on event time series, i.e., the timestamps of an event, appearing in various areas including social media analysis, marketing, finance, seismology, and neuroscience.
We are developing a method for discovering hidden rules underlying an event time series [1, 2].
Using machine learning to construct a map of neuronal connections [1]
Mathematical modeling of single neurons (2006-present)
We have studied how a neuron (nerve cell) process information in the brain. We proposed a mathematical model for simulating a rich variety of neurons [3] and a method for estimating input signal to a neuron from experimental data [4]. Recently, we analyzed the effect of the population size of neurons on information transmission [5].
Literature
[1] Kobayashi R, Kurita S, Kurth A, Kitano K, Mizuseki K, Diesmann M, Richmond BJ, and Shinomoto S. "Reconstructing neuronal circuitry from parallel spike trains", Nature Communications, 10:4468 (2019)
[2] Kobayashi R and Lambiotte R. "TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics", Proc. of 10th International AAAI Conference on Web and Social Media (ICWSM 2016), pp.191-200, Cologne, Germany (2016)
[3] Kobayashi R*, Tsubo Y*, and Shinomoto S. "Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold", Frontiers in computational neuroscience 3:9 (2009) (*: Equal Contribution)
[4] Kobayashi R, Tsubo Y, Lansky P, and Shinomoto S. "Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron", Advances in Neural Information Processing Systems 24 (NIPS 2011), pp.217-225, Granada, Spain (2011)
[5] Kostal L, Kobayashi R. "Critical size of neural population for reliable information transmission", Physical Review E (Rapid Communication), 100:050401(R) (2019)
Future Plan
I am interested in understanding human behavior in online systems based on time series and mathematical modeling. This work has potential implications on recent problems in internet such as spreading of fake news and misinformation and flaming.
Messages to Students
It is important for you not only to learn by yourself but also to talk with people. Please do not hesitate to contact me if you are interested in my research. I am looking forward to working with you.