Mr. Yang Yi Poh

Mr. Yang Yi Poh

Postgraduate Student
Department of Electrical and Computer Systems Engineering
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I’m a PhD student at Monash University’s Biomedical Signal Processing Lab, studying the application of source separation using deep learning in the biomedical field. My research focuses on advancing biomedical source separation by leveraging cutting-edge deep learning frameworks. I specialize in developing non-traditional methodologies for signal isolation, ranging from repurposing automatic speech recognition models like Whisper for lung and heart sound separation, to framing ECG isolation as an autoregressive token-generation task. Driven by curiosity and innovation, I also explore generative approaches such as diffusion models and flow-matching to push the boundaries of how we extract and interpret critical biomedical signals.

Ultimately, I’m interested in the novel application of deep learning to solve biomedical challenges.

Qualifications

  • Bachelors of Electrical and Computer Systems Engineering, Monash University, 2022

Research Interests

  • Deep Learning
  • Source Separation
  • Parameter-Efficient Fine-Tuning
  • Electrocardiogram (ECG)
  • Phonocardiogram (PCG)

Journal Article

  • Poh, Y. Y., Grooby, E., Tan, K., Malhotra, A., Harandi, M., & Marzbanrad, F. (2026). Reprogramming Automatic Speech Recognition Models for Neonatal Chest Sound Separation. IEEE Journal of Biomedical and Health Informatics.
  • Poh, Y. Y., Grooby, E., Tan, K., Zhou, L., King, A., Ramanathan, A., … & Marzbanrad, F. (2024). NeoSSNet: Real-time neonatal chest sound separation using deep learning. IEEE Open Journal of Engineering in Medicine and Biology, 5, 345-352.
  • Jabbar, A., Grooby, E., Poh, Y. Y., Ahmad, K. I., Hassanuzzaman, M., Mostafa, R., … & Marzbanrad, F. (2025). Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion. Computers in Biology and Medicine, 197, 110993.

Conference paper

  • Grooby, E., Poh, Y. Y., & Marzbanrad, F. (2024, July). Age-Based Heart Sound Segmentation for Accessible Pediatric Cardiovascular Disease Screening. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1-6). IEEE.

Teaching Commitments

  • ECE2111 - Signals and Systems
  • ECE2191 - Probability and AI for Engineers
  • ECE2131 - Electrical Circuits
  • ECE2071 - Systems Programming
Last modified: 05/06/2026