Research
I have worked in multiple labs and collaborated with researchers from diverse discipline. My work centers on wearable sensing, designing and analyzing data from wearable/portable devices that measure physiological signals in real time. I’m particularly interested in running AI models on embedded hardware, bridging the gap between sensing and intelligent on-device computation.
I also conduct computational research using high-performance computing (HPC) to analyze large-scale datasets such as genomics, EHR, and spectroscopy data.
My Ph.D. thesis involves an integrated framework that addresses two critical challenges in biomedical AI: data scarcity and poor generalization. My hypothesis is that by combining domain knowledge, hardware–AI co-design, and generative models, we can create synthetic biomedical data to enhance sensing + modeling. My main application is a continuation of my Master’s work : A non-invasive wearable Hydration Tracking device.
You can explore these projects in more detail on my Projects Page.
Research focus
- Wearables & Digital Biomarkers
- Computational Spectroscopy & Biomedical Sensing
- Neurotechnology & Brain–Computer Interfaces
- Computational Genomics & Bioinformatics
- Clinical Data Science (EHR/omics; robust, reproducible pipelines)