91³Ô¹ÏÍø

Throughout each semester 91³Ô¹ÏÍø's Mathematics Department hosts math talks (colloquia).  These talks are directed towards Mathematics majors but are usually accessible at a variety of levels.  If you have questions or are interested in presenting contact Dr. Hays Whitlatch.

Upcoming Talks

Analysis of Stability Domains for Multistep Methods: Areas and Real-axis Crossings by Logan Chmielewski and Emma Sheppard

Numerical analysis allows us to analyze methods for approximating solutions of ordinary differential equations encountered in scientific research. One key characteristic of a method is stability; an unstable method’s round off error becomes unbounded as time increases. A stability domain is a graph in the complex plane that shows for which combinations of equations and step sizes a particular method will be stable.

• Presented by Logan Chmielewski: We  have  approximated the real-axis crossings of the stability domains for Adams-Bashforth (AB), Adams-Moulton (AM), and AB/AM predictor-corrector (PC) multi-step methods and then applied curve fitting  techniques to this data.  We  prove that all PC methods have at least two real-axis crossings in their stability domains, giving a formula for a non-zero real-axis crossing.

• Presented by Emma Sheppard: We have derived a formula for calculating the area inside a stability domain and will discuss its application to various types of stability domains. This formula and Mathematica have been used to find the area inside stability domains for AB multi-step methods; we have also applied it to a previously studied free-parameter method to find area as a function of the free parameter.

  
  

• Friday, 8 December 2023 at 12:05 pm in Bollier 119

Past Talks

Bioinformatics: A Cutting Edge Career for the 21st Century by Eilis Boudreau MD, PhD (Professor for the Departments of Neurology & Medical Informatics and Clinical Epidemiology, Oregon Health & Science University (OHSU)) 

• Using examples from her own work and the work of her colleagues at OHSU, Eilis Boudreau MD, PhD, will discuss the many exciting career opportunities in bioinformatics and computational biomedicine and how you can start a career in this fast-paced and exciting field..
• Friday, 14 April 2023 at 3:30 pm.

Mathematicians in Space (kinda...) with alumni Sydney Schmidt (Modeling & Simulation Engineer at Blue Origin) and Kevin Shaw (System Engineer at Lockheed Martin)

• The Department of Mathematics is pleased to welcome back alumni, Sydney Schmidt (Mathematics, '20) and Kevin Shaw (Math-Comp Sci, '20), for a special joint presentation on their journey to working in Space Engineering for top companies, Blue Origin and Lockheed Martin, respectively.  Please join us as they share about how their time at 91³Ô¹ÏÍø led them to their exciting careers in space technology, the mathematics they use in their current research (at least the unclassified parts!), and career opportunities in the industry.  A brief Q&A session will follow.
• Thursday, 30 March 2023 at 4pm. 

Arnold Lecture Programming Biology: A Matter of Life and Death by  (Professor and Chair, Electrical and Computer Engineering, University of Washington)

• Abstract: The behavior of a living cell is determined by its DNA, much like the behavior of a computer is determined by its software. How good is this analogy? Do cells have memory, program variables, and input/output signals? Can you write if-then statements and for loops with DNA, RNA, and protein? Should we one day expect programming cells to be as straightforward as programming computers? This talk will explore the similarities and differences between living cells and computers and introduce the exciting field of synthetic biology whose practitioners have made great strides in learning to program biology. Lab experiments with microbes have repurposed growth, death, mating, immune systems, and microbial communities to build entirely new behaviors. The talk will also touch on the ethics of reprogramming biology and then examine some practical applications of the work, ranging from producing carbon neutral jet fuel to discovering new therapeutics.
• Biography: Dr. Klavins is the recipient of several professional honors, including an NSF Career Award, an Allen Distinguished Investigator Award, an Innovation Award from the University of Washington, an Amazon Catalyst Fellowship and a CoMotion Innovation Fund Award. He is a dedicated educator, receiving the Faculty Innovator Award in Teaching and Learning from the UW College of Engineering for his work in course development and undergraduate research. As a scientific advisor to several UW-based startups, he has helped build a culture of entrepreneurship in research and education. Over the last 20 years he has published over 80 technical papers with collaborators around the world.  His work spans synthetic biology, robotics, control theory, and programming languages. 
• Tuesday, 21 March 2023 at 5pm.  

Mathematical modeling of water flow, plankton, pollutants, and more: Are more complex models necessarily better? by  (Research General Engineer for the United States Geological Survey)

• Abstract: A common refrain of environmental scientists is: “Environmental science isn’t rocket science. It’s harder than rocket science.” Understanding, predicting, and managing the workings of environmental systems is a grand challenge, due in no small part to the intricate interactions between physical, biological, and geochemical processes that are, individually, complex enough for whole careers to be spent deciphering them. Fortunately, technological advancements in field and laboratory instrumentation, remote sensing, and computing permit us to measure and mathematically model environmental systems with ever-increasing extent and resolution. Drawing on my and colleagues’ work in San Francisco and Chesapeake Bays, I will discuss both complex and super-simple modeling approaches, with an emphasis on the latter. I will show how simple, computationally trivial models---such as those that can be evaluated with a pencil and paper or a spreadsheet---can be surprisingly valuable for (1) diagnosing and learning about how complex environmental systems work, (2) integrating multiple physical, biological, and/or geochemical processes, (3) producing accurate results, and (4) providing valuable guidance for ecosystem management. I will draw on examples from environmental fluid mechanics, algal blooms, contaminant transport, and hypoxia in coastal and river systems.
• Biography: Dr. Lucas is a Research Engineer and Eco-hydrodynamicist with the U.S. Geological Survey. Inhabiting the interface between environmental physics and biology in aquatic ecosystems, she studies how interactions between hydrodynamics and other physical and biogeochemical processes influence water quality and aquatic ecosystem function. She works in estuarine and river systems, implementing a broad range of mathematical modeling approaches spanning multi-dimensional numerical models to simple algebraic equations solvable with a hand calculator. Lisa’s work aims at improving understanding and prediction of how aquatic ecosystems work and, thereby, supporting informed ecosystem management. She loves collaborative, interdisciplinary science, as is required in her recent projects focusing on the modeling of harmful algal blooms, nutrients, salinity intrusion, and methyl mercury. Lisa studied Civil Engineering as an undergrad at the University of Notre Dame and did her Master’s and Ph.D. in Civil & Environmental Engineering at Stanford University.
• Thursday, 2 February 2023 at 4pm.  

National Security Research and Careers in the US National Laboratories by (Pacific Northwest National Laboratory)

• The US Department of Energy maintains 17 national laboratories, located around the country, that employ over 40,000 scientific and technical staff across all STEM disciplines. Many of the laboratories, along with additional production plants and experimentation sites, focus on research and development tailored to solving the nation’s greatest national security challenges. Supporting national security missions is among the most fulfilling professional trajectories that a scientist or engineer can follow, and, in this presentation, we will discuss how to pursue technical careers in the national laboratories. In addition to being fulfilling, the actual science and technology being discovered, explored, and developed in the national laboratories is world-leading. For this discussion, we’ll highlight some of the mathematics, physics, chemistry, and engineering in nuclear fusion research, artificial intelligence and machine learning, and materials science to demonstrate how undergraduate and graduate students, as well as career staff scientists, in the national laboratories are driving scientific discovery to solve national security problems.

Dr. Aaron Luttman is a Senior Technical Advisor at Pacific Northwest National Laboratory (PNNL), where his work focuses on understanding emerging challenges in nuclear security and developing scientific approaches to addressing them, both in support of the US nuclear weapons stockpile and in support of nuclear nonproliferation research. He has degrees in mathematics from Purdue University, the University of Minnesota, and the University of Montana, and his research has focused on computer vision and image processing. Over the last 15+ years, Aaron was a university professor, a research scientist, a Senior Technical Advisor to the US National Nuclear Security Administration (NNSA) in Washington, D.C., a personnel manager of teams of scientists and engineers, and a program manager. He is active in the mathematics community, as an officer of the Mathematical Association of America’s (MAA) Special Interest Group on the mathematics of Business, Industry, and Government, as a member of the Society of Industrial and Applied Mathematics’ (SIAM) Committee on Applied Mathematics Education, and as a member of the Embry-Riddle Aeronautical University’s Industrial Advisory Board for Computational Mathematics. He is also an active industrial partner in undergraduate research, providing research projects to the MAA’s PIC Math program, to numerous REU programs, and to Montana State University’s Data Science program. Aaron was the 2011 Outstanding New Teacher at Clarkson University in Potsdam, NY, and he has received numerous awards for his scientific contributions to the NNSA. He was an MAA Distinguished Lecturer, a SIAM Visiting Lecturer, and was a featured mathematician in 101 Careers in Mathematics (3rd Ed.).

Spatial localization of eigenvectors (and waves) presented by (Director of Computation And Data Enabled Science Program at Portland State University)

• Functions describing the behavior of (acoustic or electromagnetic) waves in space and time can often be expressed in terms of infinite sums in which each term is a product of a time-dependent "amplitude" and a space-dependent "standing wave".  These standing waves are eigenvectors of an associated differential operator.  It is known that properties of the differential operator, and geometric properties of the domain in which the problem is posed, can cause some eigenvectors to be highly concentrated in relatively small parts of the domain (i.e. nearly zero outside these regions).  This phenomenon is referred to as localization of eigenvectors, and the connection between eigenvectors and waves implies that waves can also localize within certain frequency ranges.  A better theoretical understanding of the mechanisms governing eigenvector localization, and practical algorithms for identifying such eigenvectors, are important in the design of materials that have desired acoustic or electromagnetic properties.
  
  After making the connection between acoustic waves (the wave equation) and eigenvalue/eigenvector problems, we will describe and illustrate eigenvector localization through several examples, and highlight a few applications in which localization of waves is of interest.
  Although there have been significant developments in the theoretical understanding of localization over the past decade or so, there is still much room for improvement, and even more so on the computational side.  We will pose a few basic (but not necessarily simple) questions, before shifting the focus of the rest of the talk to the development of a new type of algorithm that is specifically designed to target localized eigenvectors.

Careers in Science presented by Provost Sacha Kopp (91³Ô¹ÏÍø University)

• Co-sponsored by the Physics Department, Provost Kopp will talk about careers in science, how one gets started, what’s invigorating about doing science, and what are some options for careers post graduation. A Q&A session will follow the talk.  Pizza and light beverages will be offered from 3:30pm - 4:00pm, followed by the talk from 4:00pm - 5:00pm.  Bring your friends and classmates!

The Future of Governing Equations presented by J. Nathan Kutz (University of Washington)

• Machine learning and AI algorithms are transforming a diverse number of fields in science and engineering. This is largely due their success in model discovery which turns data into reduced order models and neural network representations that are not just predictive, but provide insight into the nature of the underlying dynamical system that generated the data. We introduce a number of data-driven strategies, including targeted uses of deep learning, for discovering nonlinear multiscale dynamical systems, compact representations, and their embeddings from data. Importantly, data-driven architectures must jointly discover coordinates and parsimonious models in order to produce maximally generalizable and interpretable models of physics-based systems and processes.

Dissecting Graphs presented by Ann Clifton (Louisiana Tech University)

• Graphs are used to model a wide range of phenomena from social networks to the structure of chemical compounds.  In a social network, we may want to divide the group into teams that share some special characteristics.  In a chemical compound, we may be interested in certain types of substructures.  How far can these divisions be taken while preserving the desired characteristics?We model this question by asking which graphs have an equitable dissection.  An equitable dissection of a graph on n vertices is an iterative partitioning of the vertex set into two disjoint balanced subsets so that the induced subgraphs are connected.  We say a graph is equitably dissectable if the iteration results in n isolated vertices.  We will present some recent results and questions for future work.

RITHMOMACHIA: A Proposal of Rules and Progressions for Victory presented by Rie Durnil (91³Ô¹ÏÍø Student).

• Rithmomachia is an ancient mathematical strategy game that gradually disappeared after the Renaissance leaving inconsistent interpretations of the rules and the number of ways to achieve victories. As a basis for further research, Dr. Tomás Guardia and I propose a set of rules in hopes of creating an academic discussion to establish a final set that is both historically accurate and player friendly. Our current research on mathematic progressions within the game will also be discussed.

Inventing the Future of Medical Imaging with Mathematics presented by Dr. Melody Alsaker (91³Ô¹ÏÍø University)

• When most people think of medical imaging modalities such as CT, MRI, or ultrasound scans, they probably don't think about mathematicians being involved in the development of these important life-saving technologies. Medical imaging is part of a large and dynamic field of applied mathematics known as "inverse problems." This talk will provide an introduction to the idea of an inverse problem, and we will touch on the mathematics behind a few modern medical imaging technologies, including my own area of research, Electrical Impedance Tomography (EIT).

A Taste of Equivariant Topology presented by Dr. Eric Hogle (91³Ô¹ÏÍø University)  

• Equivariant topology studies moving shapes. Some very simple questions about how shapes can move haven't been answered until quite recently. You might think it would be hard to understand research that hasn't even been published yet, but come give it a try! If you can imagine a donut, you can learn something only a handful of people on earth know.