Hello! My name is Jon and I was raised in Minnesota where I went to Mounds View High School while taking classes at the University of Minnesota through the Post Secondary Enrollment Option. At Stanford, I spent time as an EMT for Stanford EMS, and with the help of two friends, Anthony Milki and Yonghun Kim, started Stanford’s first hospice care organization: Stanford Undergraduate Hospice and Palliative Care. I also worked with friends at Berkeley to create a Science Olympiad tournament, Golden Gate Science Olympiad, to encourage students to compete and discover a joy in science (as I had myself in high school). In parallel, I developed my computer science and statistical engineering skills at both Apple and Stanford. Having a taste of medicine, industry, and academia has not only captured my interest in data mining and algorithm development, but reinforced in me the desire of having a perspective in both medicine and data sciences–to bridge the patient-centered elements of care with the analytical and systematic rigor of bioinformatics research for the purpose of improving the quality of medical care.

One rewarding aspect of medicine is the privilege of interacting with patients face-to-face. Though computers and electronic health records (EHRs) have improved the efficiency and consistency of patient care, they have transformed the humble act of patient care into something to do with computers rather than people. A variety of recent studies have shown that this increased screen time appears to be one of the leading causes of physician stress and burnout. One strategy to reorient patient care back to these face-to-face interactions is to make EHRs more transparent to the clinician–to “offload” the complexity of clinical decisions onto computerized systems that can draw on the power of machines to generate expedient inferences from large datasets.

In the past couple of years, rapid progress has been made in the ability of computers and algorithms to improve the efficacy of care, as measured by standard of care outcomes. As we have seen in the example of EHR, though new technologies may help us make less errors, the patient-centered elements of care are often overlooked. I am interested in further studying ways we can improve medicine by integrating and automating the analysis of different data modalities–a field of research known as precision medicine. Through UCSF’s medical training program, I strive to be a part of the discovery of precision medicine solutions that place clinical face-time, patient education, and scientific evidence at the core of technology. I hope to work with industry and medical care facilities to find ways to treat patients more effectively, especially in underserved populations.

Non-academically I spend time coordinating the Men’s Support Group at the local homeless shelter and volunteering with Science Olympiad as a test writer and event supervisor.