Returning to Academia: UVA Data Science
Some personal news: I'm joining the University of Virginia as Associate Professor of Data Science and Assistant Dean of Research in UVA's new School of Data Science.
I started my academic career in biomedical research as faculty in the University of Virginia (UVA) School of Medicine. After eight years I jumped to industry & government consulting to tackle problems in public health and biosecurity for a few years before joining Colossal Biosciences and their moonshot mission to reverse biodiversity loss.1 The through line across all these is applying modern data science techniques to understand the fundamental paradigms of life2 and build the future of biology. Each year we generate yet more biological data (particularly in genomics), with the ability to sequence, measure, and track biological systems at a resolution and with multiple modalities that were unimaginable a decade ago. The core bottleneck isn't data generation, it's interpretation, and this sense-making requires an approach that lives at the intersection of biology, statistics, computer science, and ethics.
My time at Colossal was a deep dive into that challenge. And it's given me the opportunity to work with the most brilliant genome engineers, computational biologists, imaging experts, embryologists, and cell biologists I've ever met. We get a lot of criticism, some fair, some in bad faith, but I'm convinced the tech we're developing will have a massive net positive benefit on conservation. Being a part of this mission and team has been a highlight of my career so far, and for that I am deeply grateful and will forever be a cheerleader for what Colossal is doing in all areas of biodiversity restoration and conservation.
I've learned and grown a lot as a scientist in the industry and startup world for the last ~7 years. But lately I've felt a growing pull toward a different kind of model for scientific progress. One where I have the space to think deeply and carefully about a problem and partner with world experts across disciplines to push back the boundaries of our collective ignorance in life science. So much of modern science, both in industry and academia, still operates in silos. Biologists, computational scientists, statisticians, and ethicists often work sequentially, not collaboratively. The handoffs are slow, and the feedback loops are weak. This structure isn't built for rapid progress in modern life sciences research.
That’s why I am thrilled to share that this fall I’m returning to the University of Virginia to join the faculty at the UVA School of Data Science (SDS) as tenured Associate Professor of Data Science and Assistant Dean of Research.
It's not every day you find a 200-year old institution brave enough to reinvent itself. UVA's SDS is more than just a new building or a new degree program; it's a fundamental rethinking of an academic center for research and education. It was designed from the ground up as a school without walls, an interdisciplinary nexus where data science intersects with a broad set of technical domains (like genomics and biomedicine), ethics, and societal impact.3 SDS has deep partnerships with schools throughout the university (like my former home the UVA School of Medicine), tackling challenges in genomics and personalized health, and is a core reason I was drawn to the school.
UVA SDS thrives explicitly on interdisciplinary research. SDS brings together insights from specific domains like genomics, medicine, cybersecurity, environmental science, etc. with ethics, law, and even the humanities, all unified under a data science umbrella. Faculty collaborate beyond departmental boundaries, creating an environment where complex societal and scientific questions can be tackled by diverse, collaborative teams rather than isolated individuals. This is exactly the environment I want to be in, one that thrives on diverse ideas and interconnected problems rather than isolated specialization.
Beyond research, SDS is deeply committed to training a new kind of workforce, with B.S., M.S., and Ph.D. programs in Data Science. The PhD program is particularly exciting as it provides a comprehensive curriculum that extends beyond analytics covering design, systems, and values, so that graduates are technically talented, expert analysts, competent theorists, and engaged, collaborative scientists. When I was previously on UVA's faculty, teaching was one of the most rewarding parts of my job. I'm excited to jump back into data science education (but admittedly a little intimidated by the new challenges in education in the post-ChatGPT era).
As assistant dean of research I'll have an administrative role in working with faculty to help them fund their research in an increasingly hostile funding environment. Bringing back an an animal from extinction was hard4 but getting funding for research from NIH and NSF right now is probably even harder. Over the years since leaving academia I've focused on getting funding from other sources like DOD, DARPA, and other private funding sources. I think academic researchers will need to be a bit more entrepreneurial over the next few years (a recent UVA SDS Data Points Podcast guest agrees, as does the SDS Dean). I'm looking forward to working with faculty to meet this challenge at this moment.
Ultimately, choosing UVA’s SDS wasn’t just about career progression. It was about joining an intellectually diverse community committed to exploring the full potential of data science to solve urgent, real-world problems. The path ahead feels incredibly challenging but profoundly meaningful and exciting, and I’m eager to join colleagues old and new at UVA and see where this next chapter leads.
I recently published this essay on moving from academia to industry. I’ll write another one soon on moving from industry back to academia (which is much more difficult and less common!).
I stole this turn of phrase from a friend and colleague Alexander Titus. Go read his newsletter, The Connected Ideas Project.
SDS’s “Story of Us” digital exhibition (https://story.datascience.virginia.edu) chronicles the history of SDS from its early beginnings to its current form. It’s a good read, but if you don’t have time, the podcast version is shorter.
Let's not argue about the definition of a “species” here. My former boss and Colossal chief scientist has been over this before.
Congratulations, you will be terrific there, please don't give up blogging/posting...
looking forward to working with you!