Ryan Hernandez is a Professor in the Department of Bioengineering and Therapeutic Sciences at the University of California San Francisco. He is also a core member of the Institute for Human Genetics, Bakar Computational Health Sciences Institute and the Quantitative Biosciences Institute. His lab studies population genetics and computational/statistical genetics using large-scale genomic data, with an emphasis on using evolutionary thinking to understand the genetic architecture of complex traits across diverse human populations. Ryan is the Director of the Biological and Medical Informatics (BMI) graduate program, the Director of the UCSF Initiative for Digital Transformation in Computational Biology and Health Data Science, and co-Director of the Post-baccalaureate Research Opportunities to Promote Equity in Learning (PROPEL) training program. Ryan has been committed to improving diversity at all rungs of biomedical sciences, particularly in biomedical informatics. In particular, Ryan recently co-founded a post-baccalaureate research training program at UCSF (PROPEL) to provide the training opportunities that individuals from historically excluded backgrounds need to be highly competitive for PhD and MD-PhD programs. In its inaugural year, the program is supporting the development of 54 diverse scholars.
Magnus Nordborg is Scientific Director of the Gregor Mendel Institute and a Senior Group Leader focusing on population genetics. His lab uses a combination of computational biology together with lab and field work to understand how and which DNA differences are responsible for differences between individuals. Magnus is internationally recognized as a pioneer in the use of genome-wide association studies to study patterns of natural variation in non-human organisms. He is a Fellow of the American Association for the Advancement of Science and a Corresponding Member of the Austrian Academy of Sciences.
Pleuni Pennings is an Associate Professor of Biology at San Francisco State University (SFSU). Her lab studies the evolution of drug resistance in viruses and bacteria, often using publicly available datasets on patients in clinical trials or cohort studies. This approach has provided unique insights in the within-host evolutionary dynamics of HIV. Over the last seven years, Pleuni has been involved in the creation of several programs at SF State University to increase the number of biology and biochemistry students that learn coding and data science skills. She and her colleagues work hard to make sure that all their computational classes and programs are welcoming to students from groups underrepresented in (computational) research. They run two part-time summer programs and the following academic programs: the PINC minor (CS for undergrads), the GOLD certificate (data science for MS students), and the gSTAR certificate (biotech/ML for Bio/Chem/CS students), with support from NSF and Genentech. Together, these programs now reach about 200 students each year. The success of these programs shows that biology students at SFSU, which are majority women of color and include many first generation students, are very interested and highly successful in learning computational skills—we just need to create more inclusive classes that speak to more students.