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Chanyeok Choi — Robot engineer, MS in Applied AI at Hanyang University.
Contact Information
| Name | Chanyeok Choi |
| Professional Title | Robot Engineer · MS in Applied AI, Hanyang University |
| angledsugar@gmail.com |
Experience
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2022 - present Seoul, South Korea
Graduate Research Assistant
Hanyang University
Robot learning research under Prof. Youngmoon Lee.
- Self-Supervised Critical Phase Detection (CPD): step-level premature-commitment detector and ≈ 1K-parameter residual adapter for frozen π₀ / π₀.₅ VLA policies on LIBERO; cross-modal execution gap between action-expert latent and proprioception (preprint, under review).
- Poisoning attacks on multi-agent RL: reward-poisoning attacker agent on cooperative PPO/SAC crawlers in a Unity 50×50 m benchmark; 18.7%/20.9% reward drop in multi-agent PPO/SAC, up to 98.1% in single-agent SAC (Humanoids 2025 LBR).
- Safety-RL: bridging the sim-to-real gap by allowing safe optimization and exploration during robot learning.
- Vision (HumanPose): hybrid PoseNet/SegNet approach for crowded scenes with overlap and occlusion.
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2021 - 2021 South Korea
Research Intern
KITECH — Process Platform Research Division
- Researched AI methods for detecting defective products on high-speed conveyor belts.
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2019 - 2020 Seoul, South Korea
Research Intern
Hanyang University — CAI Lab
- IKEA Furniture Assembly Collaborative Robot: RL simulation in which two manipulators identify randomly placed furniture parts and assemble them collaboratively.
Profile
Education
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2022 - present Seoul, South Korea
MS
Hanyang University
Applied Artificial Intelligence
- Advisor: Prof. Youngmoon Lee
- Research on safety-RL, poisoning attacks on multi-agent RL, and vision-language-action policy failure detection.
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2018 - 2022 Seoul, South Korea
BS
Hanyang University
Robotics
- Advisors: Prof. Youngmoon Lee, Prof. Taejoon Park, Prof. Changsoo Han
Publications
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2026 Self-Supervised Critical Phase Detection for VLA Refinement
Preprint (under review)
Self-supervised step-level critical-phase detector and ≈ 1K-parameter residual adapter that refines frozen π₀ / π₀.₅ VLA policies inside detected phases.
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2025 Poisoning Attacks on Multi-Agent Reinforcement Learning Systems
IEEE-RAS International Conference on Humanoid Robots (Humanoids), Late-Breaking Report
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2024 HAPtics: Human Action Prediction in Real-time via Pose Kinematics
International Conference on Pattern Recognition (ICPR), Kolkata, India
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2024 Causes and Fixes of Unexpected Drone Shutoffs
ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED)
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2024 Snapbot: Enabling Dynamic Human Robot Interactions for Real-Time Computational Photography
ACM/IEEE International Conference on Human-Robot Interaction (HRI), Late-Breaking Report
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2023 Leveraging Keypoints as Dynamic Centroids for Unified Representation of Human Pose and Instance Segmentation
Preprint (withdrawn from CVPR 2024)
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2023 SSK-DNN: Semantic and Sentiment Knowledge for Incremental Text Sentiment Classification
IEEE ICDM Workshop on Incremental Learning (IncrLearn), Shanghai, China
Awards
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2023 Information & Communication Planning and Evaluation President Award (2nd place) — SW Talent Festival
AnimeGAN Filter Photographer: a manipulator that frames and captures stylized portraits under safety-RL constraints.
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2021 Capstone Design Award (3rd place) — Hanyang University
Guide Robot Dog: a full-stack quadruped robot motivated by guide dogs, intended to assist visually impaired pedestrians.
Teaching
Lead Teaching Assistant — Robot Vision System: Hanyang University, Fall 2022 & Fall 2023. Lead other graduate TAs for a class of 30–40 students; developed an autonomous robot training and vision environment in Unity. [[Materials](https://github.com/Angledsugar/RobotVisionSystem)]
Teaching Assistant — Robot Learning: Hanyang University, Spring 2022 & Spring 2023. Class of 40–50 students. Designed a Pac-Man RL project and an ultrasonic-sensor self-driving car kit for real-world maze escape. [[Materials](https://github.com/Angledsugar/RobotVisionSystem)]
Skills
Robot Learning (Advanced): Reinforcement Learning, Safety-RL, Sim-to-Real, Vision-Language-Action, Multi-Agent RL, Adversarial / Poisoning Attacks
Perception (Intermediate): Human Pose Estimation, Segmentation, Self-Supervised Representation Learning
Engineering (Advanced): Python, PyTorch, ROS, Unity, C++, Embedded Control, Field Robotics
Languages
Korean : Native speaker
English : Professional working proficiency
Interests
Research Interests: Vision-Language-Action policies, failure / critical-phase detection, safe robot learning, sim-to-real transfer, multi-agent RL, human-robot interaction