My name is Varun Viswanath, and I am a 5th year PhD student at the University of California, San Diego working in the DigiHealth lab lead by Edward Wang and in the Smarr Lab led by Benjamin Smarr.

My research focuses on improving ubiquitous and wearable healthcare devices. I develop novel methods to study large-scale health data and design novel deep learning approches to better identify health outcomes from wearable data.

I’ve explored how wearable device data can predict the onset of illnesses like COVID-19 and how biases can challenge such illness detection tasks. I’ve recently studied how human sleep phenotypes obtained from large cohort wearable studies (N>60,000) can be leveraged to improve health algorithms detecting respiratory and cardiometabolic disorders. I previously explored how smartphones can predict lung condition (smartphone spirometry) and blood oxygen percentage (smartphone oximetry). Currently, I am a research intern working on sleep algorithms with the Digital Health Team in Samsung Research America. In the future, I aim to further explore how deep learning and other statistical methods can augment wearable and ubiquitous technology to improve peoples’ health and lifestyle.

I plan to defend and graduate near the end of this academic year and am actively seeking post-doctoral industry fellowships and academic post-doc postions.

I received my Bachelor’s in Computer Science from the Paul G. Allen School of Computer Science and Engineering at the University of Washington. As an undergraduate researcher, I was advised by Shwetak Patel for 3 years as part of the Ubicomp Lab. My senior research thesis was on “Using Confidence in Smartphone Spirometry”. I’ve also interned with the Uber Elevate (Summer 2017). I maintain a list of my publications under the Research tab.

CV / Resume, Google Scholar, Email ID: vkviswan@ucsd.edu

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