Uploaded September 2025 | Updated September 2026, 2 weeks ago
Sean Lawley, University of Utah
Stochastic modeling and analysis can help answer pressing medical questions. In this talk, I will attempt to justify this claim by describing recent work on two problems in medicine. The first problem concerns ovarian tissue cryopreservation, which is a proven tool to preserve ovarian follicles prior to gonadotoxic treatments. Can this procedure be applied to healthy women to delay or eliminate menopause? How can it be optimized? The second problem concerns medication nonadherence. What should you do if you miss a dose of medication? How can physicians design dosing regimens that are robust to missed/late doses? I will describe (a) how stochastics theory offers insights into these questions and (b) the mathematical questions that emerge from this investigation. The first problem is based on joint work with Joshua Johnson (University of Colorado School of Medicine), John Emerson (Yale University), and Kutluk Oktay (Yale School of Medicine).
Learn more, follow us on social media and check out our podcasts:
https://linktr.ee/sfiscience
Sean Lawley, University of Utah
Stochastic modeling and analysis can help answer pressing medical questions. In this talk, I will attempt to justify this claim by describing recent work on two problems in medicine. The first problem concerns ovarian tissue cryopreservation, which is a proven tool to preserve ovarian follicles prior to gonadotoxic treatments. Can this procedure be applied to healthy women to delay or eliminate menopause? How can it be optimized? The second problem concerns medication nonadherence. What should you do if you miss a dose of medication? How can physicians design dosing regimens that are robust to missed/late doses? I will describe (a) how stochastics theory offers insights into these questions and (b) the mathematical questions that emerge from this investigation. The first problem is based on joint work with Joshua Johnson (University of Colorado School of Medicine), John Emerson (Yale University), and Kutluk Oktay (Yale School of Medicine).
Learn more, follow us on social media and check out our podcasts:
https://linktr.ee/sfiscience








![Exploring Chemical Space with Chemputation and Assembly Theory
Lee Cronin, University of Glasgow, SFI
Recent advancements in automation and digitization of chemistry have opened new avenues for exploring chemical complexity. In this talk I will explain how Assembly Theory[1-2] and Chemputation[3-4] can be used to develop a new paradigm to understand and harness the principles of Assembly Theory in chemical synthesis. Assembly Theory provides a framework for quantifying molecular complexity and understanding the emergence of complex chemical systems. Chemputation, on the other hand, offers a standardized method for digitizing and automating chemical synthesis through modular robotic platforms and a chemical programming language (χDL). By combining these approaches, researchers can systematically explore vast chemical spaces, optimize reaction conditions, and potentially discover novel molecules and materials. The integration of these two methodologies enables a new approach to explore chemical space with autonomous experimentation and discovery. As these technologies continue to evolve, they promise to accelerate chemical research, improve reproducibility, provide new insights into the fundamental nature of chemical complexity.
Learn more, follow us on social media and check out our podcasts:
https://linktr.ee/sfiscience Exploring Chemical Space with Chemputation and Assembly Theory](https://i.ytimg.com/vi/hjacdY50gbY/mqdefault.jpg)

