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Meng-Huan Chiang
Junior Robotics & Reinforcement Learning Engineer specializing in autonomous systems
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Robotics/ML candidate building an individual pedestrian trajectory forecasting system by adapting a GAN-style Social-GN training architecture from LSTM to a transformer-based AgentFormer design. Also has hands-on embedded robotics experience debugging lane-following behavior on a JetBot by tuning PID control, and uses Docker for reproducible training environments.
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Key Strengths
- Designed and implemented a transformer-based Social-GN + AgentFormer trajectory forecasting architecture as an individual project
- Hands-on experience stabilizing GAN-like training via multi-loss weighting (BCE + reconstruction + variability)
- Real-time robotics debugging through PID tuning for lane-following on JetBot (improved curve handling)
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Experience
Education
Awards
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Publications
2 publications
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