John A. Gemmer

Student Projects

I am very interested in working with students who want to pursue an undergraduate or master's thesis. My training is broadly in applied mathematics with my doctoral research in the area of calculus of variations, differential geometry, continuum mechanics, and applied analysis. However, as an applied mathematician, I have a very broad range of interests. Below you will find descriptions of current and past projects I have mentored. Some of the descriptions have clickable images which link to more detailed descriptions of the project. In the past I used to include a list of potential projects I could mentor. However, in some sense I have found this to be constraining. Generally, if your interests lie within the intersection of science, mathematics, and modeling then I am more than happy to work with you to develop a project that overlaps with both of our interests. I would love to hear about your ideas!

Current Projects

Qiyue (Clare) Zhang: Noise Induced Transitions in the Swift-Hohenberg Equation

ridge.png Clare is completing a master's thesis under my direction in which we are studying the metastability of stationary patterns for the Swift-Hohenberg equation with white noise. Originally derived from the equations for thermal convection, the Swift-Hohenberg equation is a fourth partial differential equation that is a canonical example of pattern forming system. Moreover, the Swift-Hohenberg equation is variational in the sense that it is the gradient flow for an underlying energy functional. Clare is adapting the Freidlin-Wentzell theory of large deviations to this system in order to understand most probable transition paths between patterned states. For systems of ordinary differential equations, it is well known that for gradient systems the most probable transition paths correspond to the time reversed dynamics however no such result holds in the stochastic PDE setting. The figure to the left illustrates the evolution of the one-dimensional Swift-Hohenberg equation with space-time white noise.

Emily Foley: Spatiotemporal Chaos and Tipping in the Forced Sine-Gordon Equation

ridge.png Emily is working on a project under my direction in which we are studying the dynamics of the sine-Gordon equation with periodic forcing and random fluctuations. The sine-Gordon equation is an example of an integrable system with traveling soliton and stationary "breather" solutions. Our goal is to understand the metastability of such solutions as function of the amplitude and frequency of the periodic forcing as well as the strength of the noise. It is well known that under periodic forcing this system can exhibit quasiperiodicity and spatiotemporal chaos depending on the amplitude and frequency of the periodic forcing. In the non-chaotic regimes, Emily is working on determining if noise can cause this system to transition between various soliton/breather solutions. We are also interested in applying the techniques we learn to understand soliton solutions to Einstein's vacuum equations in general relativity.

Shelby Horth: Phase Shaping of Images

ridge.png Shelby is working on a project under my direction in which we are studying the problem of phase shaping the modulus of a complex valued function of two variables into a desired target pattern. In this setting, the modulus corresponds to the intensity of an image in physical space while the argument corresponds to the spatial phase of the signal. This is a classic problem in optics in which a complex valued signal is propagated using the linear Schrodinger equation and is closely associated with the problem of phase retrieval from two intensity measurements. In the classic setting, the intensity profiles can be related via Fourier transforms which allows for computationally efficient algorithms to be developed using the Fast Fourier Transform. Shelby is working on understanding how to develop computationally efficient algorithms for systems in which the underlying evolution equation is weakly nonlinear and hence the Fast Fourier Transform is not applicable.

Past Projects

Xuan (Kelsy) Fei 2022-2023: Predicting the Most Probable Path for Tipping in Arctic Sea Ice

ridge.png The Arctic sea ice is anticipated to melt away to a seasonally or perennially ice-free state by the end of the century. Kelsy completed an honor's thesis (co-directed by Dr. Kaitlin Hill at Saint Mary's University San Antonio) in which she studied the most probable manner which the Arctic sea ice may melt. To do so, she applied the Freidlin-Wentzell the theory of large deviations to the Eisenman and Wettlaufer Arctic energy balance model to compute most probable transition paths. Kelsy compared these results with Monte Carlo simulations which were used to obtain noise induced tipping events from which the distribution of escape times and the expected transition time could be computed. Kelsy is currently pursuing a Ph.D. in applied mathematics at The University of California Davis.

Zhengdao (Jack) Liu 2022-2023: Chaos Game on Non-Convex Domains

ridge.png In the classic chaos game on a convex polygon, a sequence of points is iteratively created by first starting with an initial random point. Second, a new point is generated by randomly selecting a vertex and generating a new point on the line connecting the vertex and the previous iteration. The new point is chosen to lie a fixed fraction of the distance between the previous point and the random vertex. The process is then repeated using the new point as the initial point. This algorithm is well known to generate fractal patterns depending on the fixed fractional difference. For example, when the fraction is a half and the polygon is a triangle, the algorithm generates the Sierpinski triangle pattern. In Jack's thesis he generalized the chaos game to non-convex domains and provided numerical evidence that the on non-convex domains there is still fractal like structure in which the iterates are attracted to. Jack is currently pursuing a masters degree in operations research at Cornell University.

Ashley Peake 2021-2023: Polarization in Online Opinion Dynamics

ridge.png As people increasingly rely on social media for news and information, personalized online content plays a significant role in determining or reinforcing personal opinions. To better understand this phenomenon, Ashley developed a coupled system of ordinary and partial differential equations which model the interaction between social media influencers (ODEs) and the density of public opinion (PDE). Specifically, the influencers were modeled by a (reverse) gradient system in which they moved to maximize their influence while the public opinion evolved by a conservation law with a flux being driven by the pull of the influencers. Assuming the dynamics of the social media influencers move on a much faster time scale than the option of the population, Ashley was able to derive necessary and sufficient conditions for the system to become polarized in the presence of two influencers, i.e. concentrate in measure around the influencer opinions. Ashley is currently pursuing an interdisciplinary Ph.D. in Social and Engineering Systems and Statistics at The Massachusetts Institute of Technology with the financial support of a NSF-GRFP.

Malindi Whyte 2021-2023: Opinion Formation on an Adaptive Network

ridge.png Understanding how people compromise to a consensus or polarize to a fragmented state is important to preserving a well-functioning society. Malindi studied the problem of determining which mechanisms could lead to consensus/polarization by adapting the bounded confidence model to a dynamic network in which people only compromise with those they are connected with and break connections if opinions differ too much. Specifically, Malindi compared the effects the network had on the original model, including party formation, through the derivation of ordinary differential equations that modeled the average dynamics at the network level. She also studied the network and how its topology changed as opinions evolved, specifically the formation of clusters which signified the formation of a party. Malindi is currently pursuing a Ph.D. in applied mathematics at at Brown University with the financial support of a NSF-GRFP.

Grace Hofmann 2022: Noise Induced Tipping in Networks of Neurons.

ridge.png Grace completed a master's thesis under my direction in which she studied noise induced tipping in a piecewise linear version of the Wilson Cowan equations. In computational neuroscience, the Wilson–Cowan model describes the dynamics of interactions between populations of very simple excitatory and inhibitory neurons. The classic Wilson Cowan equations can exhibit limit cycle behavior, multiple steady states, and hysteresis. Using the Freidlin–Wentzell theory of large deviations, Grace used tools for Hamiltonian system to compute "most probable transition paths" between metastable states as depicted in the figure to the left. Grace is currently a high school instructor at Georgetown Visitation Preparatory School.

John Turnage 2021-2022: Controllability of a Rolling Disk on Surfaces of Revolution

ridge.png John completed a master's thesis under my direction in which techniques from differential geometry, Hamiltonian mechanics, and Lie algebras were used to understand the controllability of a rolling disk on surfaces of revolution. The challenge with this problem is that the governing constraints are non-holonomic and thus the dynamics of the disk evolve on a higher dimensional manifold than one would expect from simply counting equations. Specifically, since non-holonomic constraints generically correspond to an inexact differential form, the system is non-integrable. The lack of integrability frees the disk to move in exotic directions generated by the Lie brackets of the disks standard flow directions. An example of this phenomenon is a parallel parking procedure in which a car moves orthogonal to its orientation. John is currently pursuing a Ph.D. in mathematics at the The University of Utah.

CURM 2021-2022: Mathematical Modeling of COVID-19 Dynamics

ridge.png In partnership with Hwayeon Ryu at Elon University and with financial support for the Center for Undergraduate Research in Mathematics (CURM), three undergraduate students from Wake Forest and two undergraduate students from Elon University developed and analyzed mathematical models of infectious diseases that incorporated human behavior. Specifically, the group studied the spread of an infectious disease on a network which adapts its topology in response to the disease, human behavior, contact tracing, and testing. The approach taken by the students was to develop and analyze a hybrid model bridging network models (mesoscale) with ODE models (macroscale) and implementing an optimal control strategy to minimize the economic impact as well as the spread of the disease. The alumni from this program include graduates Minato Hiraoka who is pursuing a Ph.D. in applied mathematics at Northwestern University and Sarah Ruth Nichols who is pursuing a Ph.D. in mathematics at Rice University as well as rising seniors Malindi Whyte, Christopher Boyette, and Danielle DaSilva who subsequently participated in REU programs at The University of Minnesota, Iowa State University, and Indiana University-Purdue University Indianapolis, respectively.

Hannah Scanlon 2019-2021: Spread of Infectious Diseases on Adaptive Networks

ridge.png Hannah completed a senior in which she studied the spread of an infectious disease on an adaptive network. Specifically, to account for human behavior, Hannah constructed two models which allow individuals to pause connections depending on whether they are connected to infected. Her first model operates at the micro level and consists of probabilistically modeling the time evolution of the state of edges and nodes in the human network. The second model operates at the macro level and uses differential equations to model the mean density of susceptible and infected individuals as well as the density of the types of connections. Hannah is currently pursuing a Ph.D. in mathematics at Duke University.

Grace Hofmann 2020-2021: Spiral Waves in the Belousov–Zhabotinsky reaction

ridge.png Grace completed a senior thesis in which she studied spatio-temporal patterns in systems of reaction diffusion equations. The image to the left illustrates the formation of spiral waves in fast-slow systems of reaction diffusion equations that arose in Grace's work. Grace's work combines techniques from bifurcation theory, geometric singular perturbation theory, partial differential equations, and numerical analysis to study the patterns that emerge in such systems. Beyond chemical reactions, Grace's work has application to epidemiology, morphogenesis, and climate change, to name a few. Grace went on to complete a masters degree in mathematics at Wake Forest University. Go Deacs!!!

Nick Corak 2019-2020: Stability and Formation of Hurricanes

ridge.pngNick completed a master's thesis under my direction that studied a low dimensional dynamical system model for the formation of a hurricane. With increasing sea surface temperatures it is postulated that the intensity of hurricanes will rise. Nick explored the formation and stability of hurricanes with slowly rising sea surface temperatures. In particular, using tools from calculus of variations, stochastic differential equations, and dynamical systems, Nick studied so called "noise induced" tipping events in which random fluctuations in sea surface temperature drive low intensity hurricanes to transition to high intensity super storms. Nick is currently pursuing a Ph.D. in physics at Wake Forest University. Go Deacs!!!

Kevin Buck 2019-2020: Spread of Infectious Diseases, Vaccination and Opinion Formation

ridge.pngKevin completed a senior thesis with me that developed and analyzed a spatio-temporal model for the spread of infectious diseases with vaccinations. Kevin coupled the vaccination rate to opinion dynamics on whether children should be vaccinated or not. This opinion evolves depending on neighbors opinions, infection density, as well as societal influence. Using this model, Kevin gained a more complete understanding on how to best educate the population about the necessity of vaccination. Kevin is currently pursuing a Ph.D. in mathematics at Indiana University.

Elizabeth Dicus (2019-2020): Mathematical Modeling of Sex Trafficking

ridge.pngElizabeth Dicus completed a senior thesis with me in which she developed and analyzed a mathematical model of sex trafficking. Her approach was to use a compartmental model with various populations recruited into different compartments through interaction. In her model, the recruitment rate into the prostitution class as well as the active customers depends on the current supply and demand for sex workers. By using this type of recruitment model coupled with a simple economic impetus, Elizabeth was able to understand the efficacy of government intervention such as increased incarceration rates, forced rehabilitation, etc. Elizabeth went on to become a data analyst at Heyrick Research, an organization focused on disrupting human trafficking.

Addie Harrison (2019-2020): Reaction Diffusion Equations and Pattern Forming Systems

ridge.pngAddie Harrison completed a senior thesis with me studying the formation and stability of patterns in systems of reaction diffusion equations. The underlying mechanism that leads to such patterns is the Turing bifurcation in which globally patterned states emerge with a dominant (spatial) wave number. The picture on the left is an example of such a pattern that arose in Addie's work. While Addie's work was originally motivated by its applications to chemistry, reaction diffusion equations appear in applications ranging from morphogenesis in biology, ecology and the spread of epidemics to, name a few. Addie is currently pursuing a Ph.D. in applied mathematics at the University of Arizona. Go WILDCATS!!!

Max Rezek (2018-2019): The Formation of Singularities in Non-Euclidean Plates

ridge.pngMax completed a Master's thesis under my direction that studied pattern formation in thin elastic sheets. In his thesis, he showed that the periodic patterns observed in leaves, torn elastic sheets, etc. naturally arise as low energy deformations of the sheet. He did this by explicitly constructing isometric immersions of hyperbolic geometries in the small slopes regime for algebraic and exponentially decaying metrics. His results were obtained using a priori analysis as well as through rigorous justification using gamma-convergence methods. Max is currently pursuing a Ph.D. in mathematics at the University of Arizona. Go WILDCATS!!!

Addie Harrison (2018): Human Visual Tracking and Image Formation

ridge.pngAddie worked with me during the summer of 2018 on a project studying image tracking in the human vestibulo-ocular system. Specifically, Addie created a model that couples image formation on the retina with eye and head motion to track an object moving in space. This work is applicable to image stabilization technology in cameras as well understanding the neuroscience of human visualization and depth perception.

Hanwen Wang (2018-2019): Most Probable Tipping Events in Stochastic Differential Equations

ridge.pngHanwen worked with me on a project that studied most probable tipping events in stochastic differential equations. Specifically, Hanwen developed a numerical gradient descent method for finding the most probable transition path between basins of attraction for low dimensional dynamical systems. Hanwen applied his techniques to a consumer-resource model and compared his numerical results with Monte Carlo simulations. Hanwen is currently pursuing a Ph.D. in applied mathematics at the University of Pennsylvania.

Brady Gales (2017-2019): Regularization of the Head Injury Criterion Functional

ridge.pngBrady worked with me on a project studying the so called head injury criterion (HIC) score functional. This functional attempts to quantify the chance of severe head injuries in terms of a functional defined on an acceleration curve during an accident. Brady's work on this project has shown that the HIC score is fundamentally ill-posed in the sense that minimizers consist of acceleration profiles with discontinuous jumps. In practice these jumps would lead to catastrophic injuries in the individual. Brady's work focused on introducing and studying regularized versions of the HIC score. Brady is currently pursuing a Ph.D. in applied mathematics at the University of Arizona. Go WILDCATS!!!

Dylan King (2017-2018): Energy Driven Pattern Formation

ridge.pngDylan King worked on a project studying energy driven pattern formation in two spatial dimensions. Specifically, Dylan studied the gradient flow of a proxy model for the energy of a two phase system. The image on the left illustrates the crystalline structure of an austenite-martensite alloy. Dylan's work centered on understanding on how such patterns can arise as stable equilibrium of an appropriate gradient flow.

Jessica Zanetell (2017-2018): Tipping Points in Stochastically Perturbed Filippov Systems

ridge.png Jessica completed a Master's thesis under my direction that studied tipping events in stochastic differential equations (SDES) with piecewise smooth drift. Specifically, Jessi extended the theory of large deviations to piecewise smooth systems to quantify most probable tipping events in the limit of vanishing noise strength for this type of system. This project was motivated by recent energy flux models of arctic sea ice thickness. Jessi went on to earn a master's degree in applied mathematics at the University of Arizona. Go WILDCATS!!!

Elizabeth Wallace (2017-2018): Wolves vs. Sheep

ridge.pngFor her senior thesis Elizabeth studied a discrete version of the predator prey model on a square lattice with periodic boundary conditions. In particular, Elizabeth developed a discrete dynamical system which models the time evolution of the wolves and sheep. Similar to Conway's game of life, the dynamical system consists of a simple set of rules. However, even with these simple rules the system can exhibit complex behavior that qualitatively replicates the dynamics of a predator prey system. Elizabeth is currently working as a consultant for Workday.

Christopher Grimm (2015-2016): Brachistochrone Problem in an Inverse Square Field

ridge.pngWhile I was a postdoc at Brown, undergraduate student Christopher Grimm worked with me on a project to understand brachistochrone curves in inverse square gravitational fields. Chris's work on this project used tools from calculus of variations, analysis, and numerical optimization to solve this problem. Chris went on to complete a Ph.D. in computer science at the University of Michigan.

Ragna Eide (2015-2016): Spread of Infectious Diseases on Adaptive Networks

ridge.pngWhile I was a postdoc at Brown, Ragna Eide completed an undergraduate thesis studying the spread of infectious diseases on adaptive networks. Ragna's thesis combined techniques from dynamical systems, probability theory and modeling to solve this problem. In particular, Ragna developed a macroscopic system of differential equations that closely modeled the mean of the underlying stochastic problem. Ragna went on to complete a Master's degree in mathematics at Oxford University UK.

Ekaterina Kryuchkova (2014-2016): Modeling Crowd Dynamics

ridge.pngEkaterina Kryuchkova completed an honor's thesis with me at Brown. Ekaterina developed and analyzed a model of pedestrian dynamics in a crowded room. In particular, this model was designed to analyze how pedestrians evacuate a crowded room during a panic situation. This model was compared with real world data from experiments a virtual reality laboratory at Brown. Ekaterina went on to complete Ph.D. in applied mathematics at Cornell University.

Mackenzie Simper (2015): Metastable Systems

ridge.pngMackenzie Simper worked with me during Summer 2015 on an REU project studying rare events in stochastic differential equations. Specifically, Mackenzie and I studied the escape problem for non-gradient systems. Using the Freidlin-Wentzell theory of large deviations we studied the most likely paths of escape in the limit of vanishing noise strength. Mackenzie won the AWM Alice T. Shafer prize for her work, was a Churchill scholar at Cambridge University UK and completed a mathematics Ph.D. at Stanford University.