Inclusive Computing Lab
Machine Learning and Computational Modeling for Inclusive Human Interaction
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International Christian University (ICU)
Introduction
We conduct interdisciplinary research to understand the cognitive, emotional, and social dimensions of human experience and to develop technologies that support cognition and communication. Our work integrates machine learning, computational modeling, and multimodal data analysis to investigate these processes. We also develop and evaluate assistive technologies to foster more inclusive communication and social interaction.
Our priorities are to enjoy doing research and to publish our work in international academic journals.
Profile of Hiroki Tanaka (Principal Investigator)
Google Scholar, ResearchGate, LinkedIn, ORCiD, ICU researchers, GitHub
Keywords
Keywords
Multimodal Interaction, Dialogue Support, Autism Spectrum, Affective Computing, Assistive Technology
Lab Members and Events
Lab Members and Events
AY 2026: 2 Master's course students and 8 senior thesis students, plus 2 as secondary supervisors
Lab retreat @ Karuizawa
AY 2025: 1 Master's course student and 8 senior thesis students, plus 2 as secondary supervisors
AY 2024: 2 senior thesis students, plus 2 as secondary supervisors
AY 2016–2023 at NAIST: 6 doctoral course students and 13 Master's course students
Thesis Titles
Thesis Titles
AY2026
Integrating Graph-based Depression Detection with LLM-based Chain-of-Thought Prompting in Clinical Interviews
AY2025
Transfer Learning for Motor Imagery BCIs: Linear Probing, Fine-Tuning, and Unity Game Integration
The Effect of Virtual Character Lip-Syncing on Human Perception and Pupil Responses
Evaluating the safety of generative AI usage for mental health support
A Component-wise Analysis of Pragmatic Metacognitive Prompting (PMP) for Sarcasm Detection
Multi-Model Alpha Generation Using Market, Sentiment, and Macroeconomic Signals
Eye-Gaze Behavior in Web-Based Tasks: An Experimental Investigation of the Relationship Between Peripheral Vision and Task Efficiency With Age Held Constant
Unsupervised Classification of ASMR Triggers: A Comparative Study of Tensor Decomposition and PCA
Communication Characteristics of Children with ASD and TD Peers as Reflected in Speech-Derived Features in SST: An Analysis Using Interpretable Machine Learning Models
AY2024
Exploring EEG-indicators to Evaluate Auditory Processing Disorder
AI-Generated Music with Lyrics Based on Common Cognitive Distortions to Alleviate Negative Thoughts
Contact
Contact
Division of Arts and Sciences, College of Liberal Arts, International Christian University, Japan
Email: hiroki.tanaka@icu.ac.jp
Office: T341
Address: Troyer Memorial Arts and Sciences Hall, 3-10-2 Osawa, Mitaka, Tokyo 181-8585
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