Cross-cutting Theories in Biology Symposium

On May 17-18, 2021, the University of Chicago will host a mini-symposium to bring together our faculty and two colleagues from the French National Centre for Scientific Research (CNRS) in Paris for talks and discussions about new ideas and theories in biology. Prof. Aleksandra Walczak and Prof. Thierry Mora will join us from the Ecole Normale Superieure. They will each give talks on the interactions between COVID-19 and the immune system, followed by additional presentations by UChicago faculty about more cross-cutting ideas in biology.

Schedule

Each day will feature a presentation by our guests from CNRS, followed by two UChicago faculty presentations and discussion.

  • Monday, May 17 – 8:00 a.m. to 9:30 a.m. CDT
  • Tuesday, May 18 – 8:00 a.m. to 9:30 a.m. CDT

The event will be hosted on Zoom. Click here to register.

Featured Speakers

Aleksandra Walczak

Aleksandra Walczak

Permanent Researcher of the Centre National Recherche Scientifique at Laboratoire Physique Théorique, Ecole Normale Supérieure, Paris

Prof. Walczak’s research is at the interface of statistical mechanics and immunology, including gene regulatory networks, collective behavior of the immune system and population genetics. Her lab describes systems at the cellular scale, understanding links between function, development, and evolvability of conserved pathways and their elements. They use experimental data to learn probabilistic models and the immune system, and develop theoretical descriptions to see how interactions between molecular components in the cell influence phenotypes.

Thierry Mora

Thierry Mora

Permanent Researcher of the Centre National Recherche Scientifique at Laboratoire Physique Théorique, Ecole Normale Supérieure, Paris

Prof. Mora studies the behavior of complex biological systems that show interesting emergent phenomena in immunology, neuroscience, cellular biology, and collective behavior. He combines a bottom-up approach, in which mechanisms of organization are hypothesized from efficient design principles, and top-down approach, where local rules of interaction are learned from data using statistical learning and statistical physics techniques. His lab focuses on model systems where collective effects play important role.

Faculty Speakers

Stefano Allesina

Stefano Allesina

Professor and Chair of Ecology and Evolution

Prof. Allesina is a theoretical ecologist studying mostly ecological networks. He is interested in the dynamics of large ecological communities, models for network structure, and the response of ecological communities to extinctions. His laboratory develops mathematical, computational and statistical tools for the analysis of ecological systems.

Sarah Cobey

Sarah Cobey

Associate Professor of Ecology and Evolution

Prof. Cobey investigates the coevolution of pathogens and hosts’ adaptive immunity. Her group uses computational and mathematical tools to test hypotheses and to advance theory. Their earlier work focused on the evolutionary consequences of immune-mediated competition between different pathogen strains, including pneumococcus, human papillomavirus, and especially influenza. More recently, the focus has expanded to include the related dynamics of the host immune response.

Aaron Esser-Kahn

Aaron Esser-Kahn

Associate Professor of Molecular Engineering

Prof. Esser-Kahn’s research interests lie at the intersection of biology, chemistry and materials science. His group’s current research focuses on three projects that function as extensions of this philosophy: working toward microvascular thermal and gaseous exchange units, creating materials for reprogramming the immune system, and working towards creating synthetic tissue scaffolds.

Matthew Stephens

Matthew Stephens

Ralph W. Gerard Professor of Statistics and Human Genetics

Prof. Stephens works on a wide variety of problems at the interface of statistics and genetics. His lab often tackles problems where novel statistical methods are required, or can learn something new compared with existing approaches. Much of that research involves developing new statistical methodology, many of which have a non-trivial computational component. And because data sets are getting larger and larger, that work often involves modern methods for “high-dimensional statistics”. The lab also makes extensive use of Bayesian hierarchical models to borrow information across data sets or sampling units.

Organizing Committee