Welcoming the Second Cohort of NITMB Fellows

The NSF-Simons National Institute for Theory and Mathematics is excited to formally welcome the Institute's second cohort of NITMB Fellows!

NITMB Fellows develop and conduct independent research programs aligned with the Institute's interest in constraints and the capabilities of living systems under the mentorship of NITMB leaders.

Read on to learn more about the research interests of each new NITMB Fellow!

Ratul Biswas

Ratul Biswas received his PhD in Mathematics from the University of Minnesota, working under the supervision of Wei-Kuo Chen and Arnab Sen. His research interests lie in probability theory, particularly in exploring problems at the intersection of statistics, physics, biology, and computer science. As a Fellow at NITMB, he aims to pursue research on spin glasses, drawing inspiration from statistical physics to develop a rigorous understanding of complex biological phenomena—such as biomolecular folding, the adaptability of neural networks, and the self-organization of individuals into communities.

Giulia Garcia Lorenzana

Giulia Garcia Lorenzana is a theoretical physicist working at the intersection of statistical physics and theoretical ecology. She leverages tools developed for the study of disordered systems to analyze complex, spatially extended ecosystems. She also draws inspiration from the non-equilibrium features of ecological systems, such as non-reciprocal interactions, to define novel classes of models with emergent properties that could be widespread in living systems. She was jointly affiliated with the École Normale Supérieure and Université Paris Cité in Paris, working with Giulio Biroli and Ada Altieri, when she received her PhD.

Aditya Mahadevan

Aditya received his PhD in physics at Stanford University with interests in statistical and biological physics. As a PhD student Aditya he worked on understanding the evolution of biodiversity through mathematical models. How do ecological dynamics, from resource competition to host-pathogen interactions, influence the trajectory of evolution? What evolutionary forces, from drift to selection to recombination, lead to the immense biodiversity we see across vast spatiotemporal scales in nature? What are mechanisms for the coexistence of fine-scale diversity and how can we understand these theoretically?

Gabriel Salmon

Gabe Salmon is widely interested in how organisms spend energy and exert surprisingly decentralized control in high dimensional spaces. Precisely what new mathematical and biological behaviors are unlocked as cells—and their collectives—operate out of equilibrium? Working closely with experimentalists, he is motivated to build human-friendly mathematical tools for thinking about these new facilities, for instance in microbial ecosystems and for counting problems in biological guises. Gabe performed his doctoral work investigating gene regulation out of equilibrium and energy-limited cellular physiology with Rob Phillips at Caltech, following an undergraduate in Physics and Chemistry at Oberlin College. Gabe received his PhD from Caltech.

Mariya Savinov

Mariya Savinov received their PhD in Mathematics from New York University’s Courant Institute of Mathematical Sciences under the supervision of Prof. Alex Mogilner. In their research, Savinov has used ideas from viscoelastic mechanics, fluid dynamics, percolation theory, and active matter to develop biomechanical models which reveal the role of friction, motor stress, and system size in actomyosin network dynamics. At the NITMB, Savinov seeks to develop new mathematical modeling approaches to investigate the underlying principles of adaptive collective dynamics of multicellular systems, generating experimentally testable predictions to explore with collaborators working on eukaryotic and prokaryotic model systems.

Li Shen

Li Shen explores scientific challenges at the interface of mathematics, computer science, and biology. His doctoral research integrates mathematical frameworks rooted in algebraic topology and geometric topology with machine learning techniques to develop quantitative and multiscale methods for analyzing biomolecular structures and interactions. He received his PhD from Michigan State University under the supervision of Prof. Guo-Wei Wei.

Adrianne Zhong

Adrianne Zhong is broadly interested in studying the diverse, dynamical behavior of biological systems through the lens of geometry, in particular the geometry of stochastic processes. Zhong received her PhD at UC Berkeley in physics under the supervision of Prof. Michael R. DeWeese, investigating the relationship between nonequilibrium stochastic thermodynamics and optimal transport theory. Before that, she researched nonneutral plasma physics with Prof. Joel Fajans also at UC Berkeley.