AI Researcher & Graduate Student
I'm a graduate student in the Master of Science in Applied Computing (MScAC) program at the University of Toronto, specializing in speech technology and multi-modal AI. With professional experience in engineering and deploying scalable audio pipelines (ASR/TTS) to cloud environments, I bring both research depth and practical implementation skills. My work spans speech processing, computer vision, and computational imaging, with a focus on building robust AI solutions that bridge the gap between cutting-edge research and real-world applications.
Tackled the problem of simultaneous language identification and transcription for zero-shot languages by engineering a dynamic embedding method. Synthesized tokens for unseen languages by weighting Whisper's pretrained embeddings based on LID confidence scores. Outperformed baselines with a 27% reduction in overall CER (51.9% → 37.7%) and a massive improvement in Dialect CER (65.9% → 38.5%), validating the model's ability to generalize to unseen dialects.
Championship victory in JAXA's international competition, designing safe navigation paths for Astrobee robot on the International Space Station.
Watch Competition Video →Received Honorable Mention Award among 55 teams for developing pregnancy and childcare information dashboard. Project integrated into Taipei City Government's official repository.
Courses: Computational Imaging, Introduction to Causality
Ranked 4th in graduating class | Dean's List Award (4 semesters)
Undergraduate Researcher at the Speech Processing & ML Lab