About

I am a 5th-year Ph.D. candidate in Electrical and Computer Engineering at the Georgia Institute of Technology, advised by Prof. Omer T. Inan in the Inan Research Lab. I am also an NSF Graduate Research Fellow and an Applied Machine Learning Scientist Co-op at WHOOP.

My research asks how we can turn noisy physiological signals into reliable, useful measurements of human health. I approach this through three connected questions: when can we trust a wearable signal, what can it tell us about the body, and how can we make the models that interpret it practical outside the lab? My work brings together machine learning, physiological signal processing, and wearable sensing, with a particular focus on seismocardiography—the small chest vibrations produced by the beating heart.

Across my research, I have worked on signal quality assessment and validated cardiac timings, efficient denoising on resource-constrained devices, and multimodal approaches to studying opioid withdrawal and brain–body interactions. My earlier work in federated learning and homomorphic encryption explored a complementary challenge: making data useful without exposing the people behind it. Together, these interests motivate my goal of building sensing and learning systems that are reliable, privacy-conscious, and useful in everyday life. You can find my work on the publications page and Google Scholar.

Beyond the research

“Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.”

— Marie Curie

If there is a theme to my life, it is a lifelong journey of self-discovery and learning. Hardship does not always lead to growth, and not everyone has the opportunity or freedom to learn from their struggles. I view my work and my personal growth as a way to honor that opportunity—to turn curiosity into understanding and struggle into progress.