What's new

• July 2022: Our paper "Personal History Affects Reference Points: A Case Study of Codeforces" has been accepted at ICWSM 2023.

• March 2022: Our paper "Context-aware Spatio-temporal Event Prediction via Convolutional Hawkes Processes" has been accepted at Machine Learning.

• January 2021: My interview was published in NTT R&D Website.

Conference Papers

• • Personal History Affects Reference Points: A Case Study of Codeforces

• • Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm

• • Price and Time Optimization for Utility-Aware Taxi Dispatching

• • Effects of Intervening Backwards from Goals to Improve Sleep Habits

• • Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes

• • Effects of Personal Characteristics on Temporal Response Patterns in Ecological Momentary Assessments

• • Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization

• • Can Reinforcement Learning Lead to Healthy Life?: Simulation Study Based on User Activity Logs

• • Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data

• • Identifying Near-Miss Traffic Incidents in Event Recorder Data

• • Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm

• • Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs

• • Coordinated Traffic Signal Control via Bayesian Optimization for Hierarchical Conditional Spaces

• • Predicting Traffic Accidents with Event Recorder Data

• • Identifying Self-changeable Actions toward Regulating Rhythm of Daily Life

• • Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information

• • Refining Coarse-grained Spatial Data using Auxiliary Spatial Data Sets with Various Granularities

• • A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data

• • Estimating Latent People Flow without Tracking Individuals

• • Modeling Interdependent and Periodic Real-World Action Sequences

• • Inferring Latent Triggers of Purchases with Consideration of Social Effects and Media Advertisement

• • Probabilistic Identification of Visited Point-of-Interest for Personalized Automatic Check-in

• • Probabilistic Latent Network Visualization: Inferring and Embedding Diffusion Networks

• • A Probabilistic Behavior Model for Discovering Unrecognized Knowledge

• • Geo Topic Model: Joint Modeling of User’s Activity Area and Interests for Location Recommendation

• • Travel Route Recommendation using Geotags in Photo Sharing Sites

• • Discovering Association Rules on Experiences from Large-Scale Blog Entries

• • Ranking Entities using Comparative Relations

• • Mining and Visualizing Local Experiences from Blog Entries

• • Toward Tighter Integration of Web Search with a Geographic Information System

• • Blog Map of Experiences: Extracting and Geographically Mapping Visitor Experiences from Urban Blogs

Journals

• • Context-aware Spatio-temporal Event Prediction via Convolutional Hawkes Processes

• • Classifying Near-Miss Traffic Incidents through Video, Sensor, and Object Features

• • Deep Mixture Point Processes: Spatio-temporal Event Prediction with External Factor

• • Time-delayed Collective Flow Diffusion Models for Inferring Latent People Flow from Aggregated Data at Limited Locations

• • Predicting Traffic Accidents with Dashboard Cameras

• • Pattern Analysis of Daily Activity and Intervention Acceptability Using Nonnegative Multiple Tensor Factorization with Convolutive Transformation Matrix

• • Domain Adaptation based on Adversarial Learning for Detection and Classification of Near-miss Incident from Dashcam Data

• • Marked Temporal Point Processes for Trip Demand Prediction in Bike Sharing Systems

• • People Flow Estimation from Spatiotemporal Population Data that Considers the Characteristics of Human Movement

• • Identifying Latent Triggers of Purchases with Consideration of Social Effects and Media Advertisements

• • User Status Estimation Using E-Commerce Site’s Access Logs

• • Joint Modeling of User’s Activity Area and Interests for Local Recommendation

• • Travel Route Recommendation using Geotagged Photos

• • Estimating Method on Choosing the Item in E-Commerce

• • Mining Experiences from Large-Scale Texts

• • Ranking Method using Comparative Relations

Program Committee Member

• • NeurIPS 2020-2022 - The Annual Conference on Neural Information Processing Systems, 2020, 2021, 2022 (Reviewer)

  • ICML 2021-2022 - The International Conference on Machine Learning, 2021, 2022

  • ECML-PKDD 2020 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020

  • AAAI 2020-2022 - AAAI Conference on Artificial Intelligence 2020, 2021, 2022

  • IJCAI 2018-2020 - International Joint Conference on Artificial Intelligence 2018, 2019, 2020

Biography

• • Jul. 2021 - Present: Researcher at NTT Human Informatics Laboratories, NTT Corporation

  • Jul. 2012 - Jun. 2021: Researcher at NTT Service Evolution Laboratories, NTT Corporation

  • Apr. 2016 - Apr.2017: Visiting Scholar at Computer Science, Stanford University ( Sponsor: Jure Leskovec )

  • Oct. 2011 - Sep. 2014: Ph.D. in Informatics, Kyoto University, Japan ( Supervisor: Katsumi Tanaka )

  • Apr. 2006 - Jun. 2012: Researcher at NTT Cyber Solutions Laboratories, NTT Corporation

  • Apr. 2004 - Mar. 2006: Master of Informatics, Kyoto University, Japan

  • Apr. 2000 - Mar. 2004: Bachelor of Engineering, Doshisha University, Japan

Contact

• • E-mail: [my first name] . [my last name] .uf [at] hco.ntt.co.jp

  • Address: 1-1 Hikarinooka, Yokosuka, Kanagawa, 239-0847, Japan