Yuya Asano

Ph.D. Candidate in Intelligent Systems

Intelligent Systems Program
School of Computing and Information
University of Pittsburgh
Tel: 412-807-0563
Email:  yua17@pitt.edu
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Yuya Asano is a fourth-year Ph.D. candidate in Intelligent Systems at University of Pittsburgh, supervised by Professor Diane J. Litman. His research interest lies in the intersection of natural language processing (NLP), human-computer interaction (HCI), and educational technology. He works on the application of NLP, in particular dialogue systems and large language models (LLMs) in the domain of education to make distance learning more interactive and offer rich education to everyone regardless of their socioeconomic status.

He received HBSc in Computer Science at University of Toronto, Canada, where he worked with Professor Joseph Jay Williams on applying reinforcement learning to educational interventions. He also collaborated with Professor Carolyn Penstein Rose and Professor Majd Sakr at Carnegie Mellon University on the generation of instructionally beneficial programming hints for students and the thematic summarization of students' in-course reflections.

Education

  (Expected) Ph.D. Intelligent Systems, University of Pittsburgh 08/2021 - Present
  HBSc Computer Science, University of Toronto 09/2018 - 06/2021
     

Biography » CV (PDF)»


News

  • Information Mar 17, 2025: I passed a comprehensive exam!
  • New publication Jan 19, 2025: One first-authored paper is accepted to COLING 2025.
  • New publication Jul 14, 2024: One first-authored paper is accepted to EDM 2024.
  • Information Mar 17, 2024: Team ISABEL won the 3rd place in Alexa Prize TaskBot Challenge 2.
  • Information Jul 6, 2023: Our AIED 2023 poster received the best poster award!

  • Current Projects All Projects»

    Collaborative Learning with Nao Robots

    This project investigates how to support dyads of middle school learners who interact to teach a robot about mathematics. We are particularly interested in how the robot can use dialogue, gaze, and gesture to facilitate the interactions between the two students and between the robot and the students.

    ISABEL: IncluSive And collaBorativE aLexa

    Our team ISABEL employs context-aware, multi-modal communication using state-of-the-art machine learning techniques to enable flexible and human-like collaboration. Our TaskBot will tailor interactions to users with different preferences and capabilities so that it will be more accessible to diverse groups and ultimately reach more users.

    Selected Publications All Publications»

    Google Scholar   ORCID  


    Awards and Honors

    • Scholarship PhD Fellowship, University of Pittsburgh, Pittsburgh, PA, USA, 2021-2022.
    • Scholarship University of Toronto Excellence Awards, University of Toronto, Toronto, ON, Canada, 2019.
    • Other Jane Street Electronic Trading Challenges Algorithm Prize, Jane Street, Toronto, ON, Canada, 2019.
    • Scholarship Rhea V. Scott Scholarship, New College at University of Toronto, Toronto, ON, Canada, 2019.
    • Scholarship Presidential Scholarship, Beloit College, WI, USA, 2016-2018.