Fabian, Stanford Biochemistry PhD, mentors students in biological modeling projects focused on COVID-19

Through the close mentorship of several important teachers in his life, Polygence mentor Fabian, a Stanford Biochemistry PhD and current data scientist, grew into a scientist and a passionate educator. He and his students have developed unique COVID-19 Polygence projects, which are anchored in principles of computational biology. Each student becomes familiar with stochastic modeling of virus transmission in a population, and then applies what they learn to the questions that are of utmost interest to them. By working with Fabian, students can take a deep dive into his areas of expertise in cell biology and data science, all while broadly developing their capacities to think critically and communicate effectively.

At age 12, Fabian moved to Long Island, NY from Peru, and his ESL teacher and mentor Linda Miller noticed his budding passion for science. She encouraged him to pursue lab research opportunities in high school, and this early experience gave Fabian an edge when applying to college. His senior year he was accepted to Yale University, where he graduated in 2013 with a degree in Molecular Biophysics & Biochemistry. There, he worked in the lab of world-renowned biochemist and immunologist David Schatz, who helped him develop keen capacities for thinking like a scientist. “David's teachings on science and philosophy form the basis of how I teach biology to high school students. It is because of David that I ask certain questions at almost every lesson: ‘What does the data tell you?’ ‘Which are the positive and negative controls?’ ‘What conclusions can we reasonably draw from this experiment?’”

Fabian went on to complete a PhD in biochemistry at Stanford, and though a PhD is the time to dive deep into a niche of expertise for one’s thesis, Fabian wasn’t afraid to broaden his skillset . Hoping to give his research an edge, Fabian decided to take courses in Stanford’s renowned Computer Science department. Working under PI Julie Theriot, a world authority in cell biology, he developed stochastic models for his thesis research on the spread of Listeria monocytogenes, a bacterial foodborne pathogen. “It was in Julie's lab that I first learned how to apply data science methods to biological questions. Additionally, the way I write about and present data to scientists and non-scientists alike improved immensely due to Julie's careful mentoring.” Through these amazing mentors he’s had in his own life, Fabian has grown to deeply value mentorship, which is at the heart of Polygence’s mission.

Beyond his incredible scholarly track record, Fabian has distinguished himself as an outstanding Polygence mentor. His students work on COVID-19 modelling Polygence projects, using the principles of both biology and data science modeling that Fabian learned at Stanford. His expertise as a scientist and educator is undeniable given the projects they’re working on. “My students have focused on questions such as how does vaccine compliance affect the spread of a virus, and what kind of impact do human daily routines, such as commuting, have during a pandemic. I provide the tools and lots of feedback, while students themselves drive the project at their own speed.”

We are furthermore impressed by Fabian’s emphasis on helping his students become better communicators across a variety of forms—from the code they write and the presentations they give to their scientific writing. Each session, Fabian has his student present new data from their project simulations. “This is not a one-sided presentation, but a conversation. I ask many questions and provide much feedback such as how to improve slides' titles, how to create better figures, etc. I challenge students to think critically about questions, hypotheses, data, and conclusions. We also brainstorm together on future directions for the project.” Additionally, his students complete and receive feedback on a variety of writing and coding assignments. “My goal is to improve a student's programming skills (use more comments, break their code into digestible functions, vectorize their code) and their writing (simpler words, less clutter, more succinct sentences).”

Fabian’s teaching style exemplifies Polygence’s belief that students should not just be given information to memorize, but should be given the tools they need to formulate important questions and pursue the answers. “I give \[my students\] a tool--simulations-- and explain it briefly, always providing them with examples of how it has been previously used by scientists. And though we come up with a research question together, I let them explore it on their own. I have been impressed by the level of ingenuity and imagination my students have shown when given the freedom to think and work independently.’

Polygence has allowed Fabian to connect with talented students who share his intense passion for science and his innate curiosity. “I was expecting to encounter smart and hardworking students, but I am astounded by their creativity in asking insightful questions and developing thought-provoking projects. I thought students would need a lot more help to get started, but they have worked more independently than I had anticipated.”

Fabian sees Polygence as a one-of-a-kind learning experience for high schoolers, allowing them to accomplish things beyond the boundaries of the traditional classroom. “There are a lot of venues for students to find online school help, typically in the form of tutors. However, Polygence takes it a step further and helps students go beyond what their schools offer. I believe Polygence can help students develop skills that are difficult to cultivate in a classroom setting...The freedom we have to ask and answer interesting questions is unparalleled to any experience a standard high school classroom can provide.” This independence is exactly what we hope to foster in our students, to set them up for success in college and all their future endeavors.

Fabian’s experiences have taught him the power of mentorship and of challenging oneself to try new things, and he hopes his Polygence students will approach their own projects with this same fearlessness. “Choosing to learn how to program at twenty-three years old and to apply this knowledge to my doctoral dissertation has been the most intellectually rewarding experience of my life. This choice encouraged me to pursue a career in data science, and I could not be happier that I did. This is all to say that I encourage students to not shy away from a rewarding learning experience because it may be outside of their comfort zone. Challenge yourself to try something different!”