Skip to content Skip to navigation

PhD Students

Alex Dainis

Alex is a graduate student in the Genetics Department here at Stanford. She has a B.S. in Biology and a B.A. in Film, Television, and Interactive Media from Brandeis University, where she graduated in 2011. Her research interests involve RNA silencing, from her undergraduate research using RNAi as a tool to probe gustatory nociception in fruit flies to her current work in the Ashley Lab investigating RNA silencing as a potential therapeutic tool. Alex is passionate about science education and communication. She has previously worked as an Associate Producer at an educational media production company, has created a successful science-education YouTube channel, and has worked with organizations including Ted-Ed and the Google Science Fair, all in the pursuit of teaching the whole world the wonders of science.

Hannah De Jong

Hannah is a graduate student in Stanford's Genetics PhD program, and a DOE Computational Science Graduate Fellow. She grew up in Ithaca, NY, and earned a B.S. in Biological Sciences and Biometry/Statistics from Cornell University in 2014. Her prior research topics range from plant-aphid-virus interactions to the polar bear gut microbiome. In the Ashley lab, she is focused on better understanding the biology of hypertrophic cardiomyopathy using genome-editing and bioinformatic approaches. Outside the lab, she enjoys hiking, wilderness backpacking, photography, and collecting owls.

John Gorzynski

John is a graduate student in the genetics Ph.D program. As an undergraduate he studied biology and continued to veterinary school where he received a DVM. During his time at university, John investigated the effects antiviral drugs have on retrovirus in relation to the development of resistance. He then switched his research focus in vet school and investigated genetic variations related to structural heart disease in captive chimpanzees. John then transitioned to the clinic as a mixed animal veterinary surgeon, treating animals ranging in size from mice to horses, with a lot of dogs, cats and cows in between. While John enjoyed his time as a veterinarian, he often found himself thinking of how to further investigate cardiomyopathies in great apes. This interest is what led John to the Ashley lab. While not in the lab or the clinic, John enjoys running ultra-marathons, skiing and scuba diving.

Cameron Prybol

Cameron is a PhD student in the department of Genetics. He grew up on the east coast and, as soon as he was old enough to work a TV remote, began self-indoctrinating himself with a love of biology through a steady supply of Wild Discovery reruns. After a brief stint of falsely believing he wanted to study mechanical engineering, he came to his senses and enrolled in the Biochemistry and Molecular Biology program at the University of Georgia. He partook in research focusing on metabolic pathways of hyperthermophilic archaea, Lepidoptera of the Costa Rican cloud forests, and dabbled in computer science before finally taking a course on genomics. He was hooked from the moment he saw the legendary and ubiquitous NHGRI "cost per genome vs. Moore's Law" graph for the first time. Shortly thereafter, he landed himself a position conducting forward genetic screens on the mechanisms of chromatin remodeling and genome stability in Neurospora crassa with Zack Lewis. After two years with the Lewis lab and having likely contaminated all of his worldly possessions with N. crassa fungal spores, he enrolled in the Biosciences PhD program at Stanford and began his journey of learning how to decode clinical jargon. His current research with the Ashley lab focuses on RNA regulation of cardiac development and disease and collaborating with Stanford's Center for Undiagnosed Diseases. He has additional research interests in long-read sequencing technology and high-throughput screening and enjoys participating in open source software development as it applies to his work. When he's not in lab, you may find him seeking remote wilderness areas, pretending to be athletic on single-track running trails, or learning about ecological restoration and community development projects in the Bay Area.

Anna Shcherbina

Anna is a graduate student in the Biomedical Informatics PhD Program at Stanford University. She is interested in developing algorithms that utilize machine learning and data mining approaches to derive medically relevant conclusions from multi-layer omics data. Anna attended the Massachusetts Institute of Technology, where she double majored in Computer Science and Biological Engineering. After graduation she pursed an M.Eng. degree at MIT Lincoln Laboratory in the Bioengineering Systems and Technologies group, where she continued to work until beginning her PhD at Stanford. During this time she developed algorithms to characterize microbiome metagenomic datasets, to predict kinship and biological ancestry from variant data, and to characterize different stages of healing from muscoskeletal injury. Currently, Anna is developing deep learning algorithms for identifying pathogenic variants in undiagnosed diseases. She is also mining “big data” sources such as the UK Biobank and the MyHeart Counts mobile health data for meaningful associations between physical activity and health. Anna's long term goal is to contribute to precision medicine by integrating physical activity, medical history, and genetic information to build a more complete picture of patient health.

Jessica Torres

Jessica is a graduate student in the Biomedical Informatics Ph.D. Program who is interested in clinical applications of wearable technology/mobile health for better patient management and outcomes. She received her B.S. in Cell and Molecular Biology and M.s in Bioinformatics from San Diego State University in 2011 and 2013 respectively. During her masters and subsequent, she worked for a biotech company developing noninvasive prenatal diagnostics before joining the Stanford Biomedical Informatics Ph.D. program. Outside the lab, Jessica enjoys spending time with her husband, puppy, and drinking lots of iced coffee.