I’m a 3rd-year ECE PhD student at Purdue University, supervised by Dr. Yung-Hsiang Lu. My work focuses on audio and music machine learning, specifically music practice error detection, music source separation, and reliable detection of synthetic and manipulated media with Audio Large Language Models.
Currently: Graduate Research Assistant at Purdue University; incoming Audio Applied Research Scientist Intern at Shure Incorporated (May–Aug 2026).
Resume: PDF
Experience (summary):
- Audio Applied Research Scientist Intern @ Shure Incorporated (2026, incoming)
- Applied Research Scientist Intern @ Reality Defender (2025)
- Graduate Research Assistant @ Purdue University (2024–present)
- Startup Founder @ LocaLens (2023–2024)
More details: Full Experience →
News
- (Jan 2026) Incoming Audio Applied Research Scientist Intern at Shure Incorporated (May–Aug 2026).
- (Jan 2026) LadderSym: A Multimodal Interleaved Transformer for Music Practice Error Detection accepted to ICLR 2026. (arXiv)
- (Jan 2026) AdaPerceiver: Transformers with Adaptive Width, Depth, and Tokens accepted to CVPR Findings 2026. (arXiv)
- (Jan 2026) Inference-Time Alignment of Diffusion Models with Evolutionary Algorithms accepted to CVPR Findings 2026. (arXiv)
- (Sep 2025) Paper accepted to NeurIPS 2025 AI4Music Workshop: Advancing Multi-Instrument Music Transcription: Results from the 2025 AMT Challenge. (OpenReview)
- (Jun 2025) Organizing AI4Music Workshop at NeurIPS 2025. (Website)
- (May 2025) Interning at Reality Defender.
- (Feb 2025) Awarded AAAI Student Scholarship (2025).
- (Dec 2024) Paper accepted to AAAI 2025: Detecting Performance Errors with Transformers. (AAAI)
- (Oct 2024) Paper accepted to WACV 2025: Token Turing Machines are Efficient Vision Models. (arXiv)
- (Oct 2024) Organizing AI4Music Workshop at AAAI 2025. (Website)
- (Jan 2023) Joined Purdue ECE.
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