Saint Louis University Mathematics & Statistics Events

• Friday, September 19
  Speaker: Jeremy T. Tyson, University of Illinois at Urbana-Champaign
  Title: Mathematics of Change Ringing: An Illinois Geometry Lab research project
  Abstract: Change ringing is an ancient musical tradition typically played on sets of bells mounted in a tower. The bell ringers successively sound each bell multiple times, with the goal of sounding every possible permutation of bells according to certain rules (dictated by the physics and mechanics of the bell-playing process). Such a performance is known as a `change’. Mathematically, change ringing is modelled by Hamiltonian paths on the Cayley graph for the corresponding symmetric group equipped with a specific set of generators. I will talk about a Fall 2020 undergraduate research project, carried out in the Illinois Geometry Lab (now known as the Illinois Mathematics Lab), in which the students analyzed bell changes using a combination of graph theory and group theory. Along the way I’ll comment on the challenges of supervising such a research project at the height of the pandemic, the structure of the Illinois Mathematics Lab and its role in providing research experiences for undergraduate math students in the context of a large, public university, and opportunities for mathematics departments of various sizes and with diverse missions to implement similar programs for undergraduate research. In fact, the Illinois Mathematics Lab is one member in Geometry Labs United, a nationwide network of labs for undergraduate research in mathematics with an emphasis on visualization and experimentation.
  
  

• Friday, October 10
  Speaker: Yingying WU, University of Houston
  Title: TBA
  
  

• Friday, October 17
  Speaker: Emily King, Colorado State University
  Title: Interpretable, Explainable, and Adversarial AI: Data Science Buzzwords and You (Mathematicians)
  Abstract: Many state-of-the-art methods in machine learning are black boxes which do not allow humans to understand how decisions are made. In a number of applications, like medicine and atmospheric science, researchers do not trust such black boxes. Explainable AI can be thought of as attempts to open the black box of neural networks, while interpretable AI focuses on creating clear boxes. Adversarial attacks are small perturbations of data that cause a neural network to misclassify the data or act in other undesirable ways. Such attacks are potentially very dangerous when applied to technology like self-driving cars. The goal of this talk is to introduce mathematicians to problems they can attack using their favorite mathematical tools.  The mathematical structure of transformers, the powerhouse behind large language models like ChatGPT, will also be explained.
  
  

• Monday, October 20
  Speaker: Glenn Ledder, University on Nebraska-Lincoln
  Title: TBA

• Friday, October 24
  Speaker: Ljupcho Petrov, Washington University in Saint Louis
  Title: TBA

• Monday, September 15, AWM Speaker Series (Virtual)

Speaker: Dr. Veronica Ciocanel, Duke University
Title: Protein journey inside cells: How can mathematical modeling and data analysis help?
Abstract: For cells to function properly, many molecules and proteins must move around and organize themselves into complex patterns. How do these particles move in such precise ways inside cells? 

There are several types of protein filaments in cells that provide the elaborate roads along which most protein transport occurs.  I will discuss examples where mathematical modeling provides exciting tools to study and understand the interactions between these filaments and motor proteins in cells. In frog egg cells, differential equations models give us insights into how messenger RNA moves along filament highways and accumulates in robust spatial patterns, which ensures that the frog embryo then develops properly. In neurons, other mathematical tools from stochastic modeling help us understand how certain proteins navigate axons and their constrictions, to maintain a healthy speed of neuronal communication. All these interdisciplinary projects lead to exciting collaborations with researchers from other fields to address complex biological questions.