Chloe Su completed her undergraduate degree in Molecular, Cell, and Developmental Biology with a minor in Biomedical Research at UCLA. Chloe is passionate about improving cancer prevention and advancing cancer treatment to improve the lives of cancer patients and their families. She has a strong interest in the intersection of informatics and epidemiology. Prior to joining Stanford, Chloe was a clinical trial project and data manager at UCLA Health where she managed trials in early lung cancer detection and helped build a patient database for biomedical informatics research. In addition, Chloe also pursued various roles in the industry including clinical operations, medical affairs, as well as the development and commercialization of an ultra-rare disease drug in Japan. Chloe is currently studying the risk factors and building predictive models for recurrence in primary lung cancer. Beyond work, Chloe is a proud mum of a 12-year-old Shih Tzu, Cookie, an avid traveler, an advanced scuba diver with a newfound interest in surfing, a rookie yogi, and an aspiring Japanese conversationalist.
Andrew (Andy) Chang, MD, MS completed his undergraduate studies at Yale University, then obtained his MD and MS in Epidemiology from Stanford. He finished his residency training in the global health track of Stanford's Internal Medicine program in 2016 and served as Chief Resident in 2017. He is now in his final year of his cardiology fellowship at Stanford. Andy is passionate about utilizing population health science methodologies to investigate and combat the impact of cardiovascular disease in global vulnerable populations. His current projects include assessing and improving the quality of care for rheumatic heart disease patients in Low- and Middle-Income Countries, characterizing the effects of the US opiate epidemic on incident heart disease, and describing the COVID-19 pandemic’s effects on cardiovascular care systems. In whatever spare time he has outside of his coursework and clinical duties, Andy enjoys hiking, tennis, cooking, and inventing new ways to get his newborn son to go to bed.
Michael Hittle completed his undergraduate degree in Human Biology at Stanford in 2019 after a first career in web engineering and marketing entrepreneurship. His pivot to computational epidemiology is driven by a passion for digital health, and a desire to leverage technology to improve both our understanding of disease and the outcomes of those impacted by disease. Michael's interests lie at the intersection of neurology and the mobile phone platform, and include novel digital endpoints, machine learning, artificial intelligence, and remote patient monitoring. Michael is an avid mountain biker, snowboarder and outdoor enthusiast; he also enjoys reading, playing and listening to music and spending time with his growing family.
Samuel Jaros graduated from Loyola University Chicago in 2020 with a BS in Bioinformatics and a BA in Sociology. Before Stanford, he researched HIV in Accra, Ghana through Washington University and worked in West Virginia in health advocacy. Sam’s current projects include helping build a California-wide dashboard for examining how socioeconomic determinants of health influence the geography and timing of disease. He is also working on designing a program to help people who have received invasive surgery find non-opioid methods for pain reduction. He is a part of the BSSR Training Grant which emphasizes the combination of large-scale health data with often ignored social data to generate highly applicable human-focused discoveries. Outside of research, he is passionate about health care reform and finding equitable ways to pay for chronic disease treatment. When he is not at Stanford, you will likely find Sam cooking, biking, skiing, or learning a new way to make coffee.
Xiaojuan Liu, MS obtained her Bachelor’s degree in Preventive Medicine and a BS in Financial Mathematics in 2016, and graduated with a Master's degree in Epidemiology and Biostatistics in 2019 from Shandong University, China. She completed her Global Learning program at Duke Kunshan University and internships at Provincial Health Commission, Provincial CDC and local hospitals before coming to Stanford. Her research interest includes cardiovascular epidemiology, with a focus on risk assessment, disease prevention and prediction based on large longitudinal cohort studies, and casual inference, especially adopting cutting edge approaches to simulate randomization and generate causality from observational study. She also has passion in applying novel biostatistics models to dealing with nonstandard study designs, integrating heterogeneous data and promoting precision medicine. Alongside research and work, Xiaojuan enjoys singing, movies, exercising and traveling.
Yan Min completed her medical training and surgical residency at Peking University, Beijing, as an undergraduate student. She then pursued her master’s degree in health economics at Stanford University. She took a gap year during the master program working as a health policy analyst in the health finance cluster at the World Health Organization in Geneva, Switzerland. After she returned from Geneva, Yan also took a leadership role in establishing the Wellness Living Laboratory Cohort at the Stanford Prevention Research Center. Yan is extremely passionate about rigorous causal inference theories and applying causal inference models to large-scale observational studies. She currently focuses on constructing a causal model to address the effects of surgeon volumes and hospital volumes on long-term patient outcomes in six cardiothoracic surgery procedures. On the side, she is also having fun in statistical learning and employing bioinformatic methodology to her studies of microbiome, metabolomics, and human health. Outside of work, Yan enjoys karate, photography, backpacking, and carpentry. Also, she is willing to take on any challengers on any racket sports.
Megan Roche, MD completed a medical degree from Stanford in 2018 and a BS in Neuroscience from Duke in 2012. She is interested in bone health in athletes, genetic predictors of sports injury, and sports epidemiology. Megan is a five-time trail running national champion and a co-author of the book, “The Happy Runner.” She co-founded Some Work All Play, a coaching group centered around finding long-term fulfillment in the process of running. Megan is pursuing her PhD in Epidemiology and is a post-doctoral research fellow at the Stanford Center on Longevity. Outside of work, Megan enjoys biking, reading, strong coffee, nearly all forms of music, and trying to keep up with her dog, Addie, and her husband and co-author, David.
Sindiso Nyathi graduated from Princeton University in 2016 with a bachelor's degree in Ecology and Evolutionary Biology. He spent two years working as a Systems Modeler at the Global Obesity Prevention Center at Johns Hopkins University. His work with the GOPC focused on assessing the effectiveness of obesity-related interventions in communitites using systems science tools. His research interests include Global Health, Infectious Disease modeling and Health Policy in Low and Middle Income Countries. Sindiso is passionate about working to leverage the range of mathematical and computational tools available today to improve public health and combat disease in LMICs. His current research includes vaccine policy work, mathematical modeling of temperature dependence of arthropod vectors and vector control modeling work. Outside of class and research, Sindiso enjoys reading, swimming, photography and exploring the outdoors.
Biyao Zou graduated with a Bachelor of Economics and a BA in English Literature from Tsinghua University, China, and obtained her Master of Public Policy at the University of Oxford, United Kingdom. Before joining the PhD program in Epidemiology and Clinical Research, she worked as a research coordinator in the Division of Gastroenterology and Hepatology at Stanford, where she studied the disease and economic burden and risk factors of liver disease in the United States and Asia. She has given oral and poster presentations at international conferences such as DDW, AASLD, and EASL. Currently, she focuses on identifying causal risk factors for non-alcoholic fatty liver disease and the causal role of non-alcoholic fatty liver disease in various diseases including cardiovascular disease and cancer using a genetic epidemiology approach. Biyao enjoys cooking, hiking and spending time with her labradoodle puppy.
Jessica Hinman completed an undergraduate program at the University of Southern California in 2010 and obtained a MS in Epidemiology at the University of Iowa in 2017 prior to joining the PhD program at Stanford. Her research centers around leveraging technology to improve design and analysis methods in the study of complex disease etiology, particularly with respect to progressive neurological disorders. She feels that an interdisciplinary approach is crucial to untangling the interactions between genetic risk, environmental exposures, and lifestyle factors that underpin these disease courses. She believes epidemiologic research must be motivated by, and grounded in, measurable improvements to health access, equity, and outcomes for patients. Outside of work, Jessica enjoys reading, hiking, eating, and spending time with her husband and their rescue dogs at their home in the East Bay.
Tahmina Nasserie graduated with a Bachelor's of Science and Master's of Public Health from the University of Toronto. Prior to joining the PhD program, she worked as an epidemiologist at BlueDot, a start-up focused on reducing the risk of global infectious disease spread. In this role, she was involved in a range of applied and research-based activities, including collaboration with the Centers for Disease Control and Prevention to support the development of a web-based public health analysis tool. She was also a trainee with the Canadian Immunization Research Network and led a project using mathematical modeling approaches to forecast the epidemic spread of seasonal influenza. Tahmina is broadly interested in the application of computational, statistical, and mathematical techniques to understand the spread of infectious diseases and to assess the cost-effectiveness of epidemiologic interventions. Tahmina enjoys brewing coffee (as well as drinking it), cooking, and trying new restaurants. She also loves cycling, exploring California, and traveling.
Matthew Sigurdson (2017 cohort)
PhD in Epidemiology and Clinical Research