Graduate Students
Misha Baitemirova
Knight-Hennessy Scholar | GSB'23 | BMI'23
Stanford University
Research interests: Multi-modal deep learning, non-invasive continuous health tracking, digital biomarkers.
Jessica Kain
PhD Candidate
Biomedical Engineering, BS
University of Virginia
- Research interests: Precision medicine, Computational and systems biology, Machine learning, Integrative multi-omic analysis, Metabolomics
- Bio: Jessica is broadly interested in the application of computational and systems biology in precision medicine and has experience leveraging multi-omic data to better understand both rare and complex diseases.
- More She received her BS in Biomedical Engineering from the University of Virginia in 2020 and has been working in research and development at a biotech start-up. Her graduate research revolves around elucidating complex biological systems through the development and use of analytical methods that integrate multi-omic data and biomedical knowledge. Jessica is currently focused on developing interpretation methods and predictive models for the clinical application of metabolomics.
Aubrey Roberts
PhD Candidate in Epidemiology
Community Health and Prevention Research, MS; Stanford University (2021)
Neuroscience, BS; Northwestern University (2020)
Research interests: exercise physiology, molecular transducers of physical activity, epidemiology and population health, precision medicine, nutrition.
Bio: Aubrey’s graduate research involves characterizing the cardiovascular and multi-omic changes that occur with high intensity interval training (HIIT) vs. traditional endurance training in sedentary individuals. She is also interested in the health of female athletes and the interplay between nutrition, energy expenditure, and bone stress injuries.
Research interests: Early detection of diseases using wearable devices, Precision mental health, Placebo effect
Bio: Ziv’s graduate research focuses on the intersection of wearable technology, specifically smartwatches, and the early detection of a broad spectrum of diseases as well as mental states. In addition to his research, Ziv teaches BIOS 237: Engineering Wellness, a course that equips students with a comprehensive understanding of the sensors in smartwatches, along with the data science and machine learning techniques employed to detect diseases.