Panayu
Keelawat
Human – AI Interaction Researcher
I design and build interfaces that help people and AI think together, transforming complex conversations, instructions, and data into intuitive tools that extend how people work, reason, and collaborate.
About
I'm a Ph.D. student in Computer Science at Virginia Tech, advised by Prof. Yan Chen. My research explores real-time human–AI collaboration in the context of educational tools that make sense of live learner data.
During my M.S. at UC San Diego, I worked with Prof. Haijun Xia on natural language interfaces that let people converse with data. I earned my B.Eng. in Computer Engineering from Chulalongkorn University, where I was supervised by Prof. Boonserm Kijsirikul on machine learning for brain-computer interfaces.
I've also shipped production interfaces as a software engineer at Amazon Alexa, on the Alexa Comms Calling Experience team, and at LSEG, building DTaaS, a cloud platform for inter-bank FX deal tracking.
Experience
Work
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Aug 2022 — Aug 2024
Software Development Engineer
Amazon Alexa · Seattle, WA
Re-architected and maintained the core Alexa calling platform serving millions of calls a day, enabling LLM-driven experiences with Alexa+. Let customers place and drop in on calls through GUI or voice, with call history synced to the Alexa app.
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Jun 2019 — May 2020
Software Engineer
LSEG · Bangkok, Thailand
Built and deployed DTaaS, a cloud platform for inter-bank FX deal tracking moving over $425B in daily transaction volume. Gave traders a single view to monitor, track, and audit deals.
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May 2018 — Jul 2018
Research Intern
The University of Osaka · Osaka, Japan
EEG-based emotion recognition with deep convolutional neural networks.
Education
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2024 — Present
Ph.D., Computer Science
Virginia Tech
Human-AI interaction design for real-time learning, collaboration, and debriefing tools.
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2020 — 2022
M.S., Computer Science
UC San Diego
Natural language interfaces for data analysis workflows.
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2015 — 2019
B.Eng., Computer Engineering
Chulalongkorn University · First Class Honors
Research on brain-computer interfaces and EEG-based emotion recognition.
Publications
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01
The Help Ladder: Skill-Adaptive Peer Scaffolding for Real-Time Collaborative Programming
VL/HCC 2026
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02
Dynamite: Real-Time Debriefing Slide Authoring through AI-Enhanced Multimodal Interaction
VL/HCC 2025
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03
Transforming Procedural Instructions into In-Situ Augmented Reality Guides with InstructAR
UIST Poster 2024
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04
NBGuru: Generating Explorable Data Science Flowcharts to Facilitate Asynchronous Communication in Interdisciplinary Data Science Teams
CSCW Poster 2023
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05
Towards Understanding Text–Data Connection in Documents through the Lens of Data Operations
M.S. Thesis
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06
A Comparative Study of Window Size and Channel Arrangement on EEG-Emotion Recognition Using Deep CNN
Sensors 2021
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07
Subject-Independent Emotion Recognition During Music Listening Based on EEG Using Deep Convolutional Neural Networks
CSPA 2019
Teaching
Virginia Tech
Teaching Assistant
- CS 3744 Introduction to GUI Programming and Graphics Fall 2025, Spring 2026, Fall 2026
- CS 3654 Introduction to Data Analytics and Visualization Fall 2024
- CS 3304 Comparative Languages Summer 2026
UC San Diego
Teaching Assistant
- CSS 1 Introductory Programming for Computational Social Science Winter 2022
Chulalongkorn University
Teaching Assistant
- 2110221 Computer Engineering Essentials Semester II, 2019