Calendar
Posted January 12, 2026
Applied Analysis Seminar Questions or comments?
3:30 pm Lockett Hall 232
Daniel Massatt, New Jersey Institute of Technology
TBA
Event contact: Stephen Shipman
Posted November 15, 2025
Last modified January 21, 2026
Algebra and Number Theory Seminar Questions or comments?
2:00 pm – 3:00 pm Lockett 233 or click here to attend on Zoom
Kiran Kedlaya, University of California San Diego
TBA
Event contact: Gene Kopp
Posted March 5, 2026
Last modified March 9, 2026
Informal Analysis Seminar Questions or comments?
1:30 pm – 2:30 pm Lockett 233
Long Teng, LSU
Doubling Inequalities for Schrodinger operators with power growth potentials
TBD
Posted January 15, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Sayani Mukherjee, Louisiana State University
TBD
TBD
Posted December 1, 2025
Last modified March 5, 2026
Control and Optimization Seminar Questions or comments?
9:30 am – 10:20 am Zoom (click here to join)
Khai Nguyen, North Carolina State University
On the Structure of Viscosity Solutions to Hamilton–Jacobi Equations
This talk presents regularity results for viscosity solutions to a class of Hamilton-Jacobi equations arising from optimal exit-time problems in nonlinear control systems under a weak controllability condition. A representation formula for proximal supergradients, based on transported normals, is derived, with applications to optimality conditions, the propagation of singularities, and the Hausdorff measure of the singular set.
Posted January 11, 2026
Last modified March 6, 2026
Applied Analysis Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett 223
Zhiyuan Geng, Purdue University
Asymptotics for 2D vector-valued Allen-Cahn minimizers
For the scalar two-phase (elliptic) Allen–Cahn equation, there is a rich literature on the celebrated De Giorgi conjecture, which reveals deep connections between diffuse interfaces and minimal surfaces. On the other hand, for three or more equally preferred phases, a vector-valued order parameter is required, and the resulting diffuse interfaces are expected to resemble weighted minimal partitions. In this talk, I will present recent results on minimizers of a two-dimensional Allen–Cahn system with a multi-well potential. We describe the asymptotic behavior near the junction of three phases by analyzing the blow-up limit, which is a global minimizing solution converging at infinity to a Y-shaped minimal cone. A key ingredient in our approach is the derivation of sharp upper and lower energy bounds via a slicing argument, which allows us to localize the diffuse interface within a small neighborhood of the sharp interface. As a consequence, we obtain a complete classification of global two-dimensional minimizers in terms of their blow-down limits at infinity. This is joint work with Nicholas Alikakos.
Posted March 9, 2026
Informal Analysis Seminar Questions or comments?
12:30 pm – 1:30 pm Lockett 233
Zhiwei Wang, Louisiana State University
Some recent progress on frequency methods to quantitative unique continuation
We study quantitative unique continuation for elliptic equations with lower order terms of H\"older regularity via a frequency function method. We establish quantitative three-ball inequalities and corresponding vanishing-order bounds. Our results are quantitative with explicit dependence of the three-ball constants and the vanishing-order exponents on the H\"older exponent, which has a unified framework matching sharp endpoint results.
Posted January 15, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Saumya Jain, Louisiana State University
TBD
TBD
Posted March 3, 2026
Last modified March 9, 2026
Shuang Guan, Tufts University
The HRT Conjecture for a Symmetric (3,2) Configuration
The Heil-Ramanathan-Topiwala (HRT) conjecture is an open problem in time-frequency analysis. It asserts that any finite combination of time-frequency shifts of a non-zero function in $L^2(\mathbb{R})$ is linearly independent. Despite its simplicity, the conjecture remains unproven in full generality, with only specific cases resolved. In this talk, I will discuss the HRT conjecture for a specific symmetric configuration of five points in the time-frequency plane, known as the (3,2) configuration. We prove that for this specific setting, the Gabor system is linearly independent whenever the parameters satisfy certain rationality conditions (specifically, when one parameter is irrational and the other is rational). This result partially resolves the remaining open cases for such configurations. I will outline the proof methods, which involve an interplay of harmonic analysis and ergodic theory. This is joint work with Kasso A. Okoudjou.
Posted January 15, 2026
Colloquium Questions or comments?
3:30 pm Lockett 232
Kumar Murty, University of Toronto
TBA
Posted January 5, 2026
Last modified March 9, 2026
Control and Optimization Seminar Questions or comments?
9:30 am – 10:20 am Zoom (click here to join)
Jonathan How, Massachusetts Institute of Technology
AIAA and IEEE Fellow
Resilient Multi-Agent Autonomy: Perception and Planning for Dynamic, Unknown Environments
Unmanned ground and aerial systems hold promise for critical applications, including search and rescue, environmental monitoring, and autonomous delivery. Real-world deployment in safety-critical settings, however, remains challenging due to GPS-denied operation, perceptual uncertainty, and the need for safe trajectory planning in dynamic unknown environments. This talk presents recent advances in planning, control, and perception that together enable robust, scalable, and efficient aerial autonomy. On the planning and control side, I first introduce DYNUS, which enables uncertainty-aware trajectory planning for safe, real-time flight in dynamic and unknown environments. Building on this foundation, MIGHTY performs fully coupled spatiotemporal optimization to generate agile and precise motion by jointly reasoning about path and timing. Together with prior work on Robust MADER, these methods enable fast, safe, multi-robot navigation under uncertainty. On the perception side, I introduce complementary mapping frameworks that support long-term autonomy and planning. GRAND SLAM combines 3D Gaussian splatting with semantic and geometric priors to produce unified scene representations suitable for photorealistic planning. A second example is ROMAN, which builds on ideas from our prior open set mapping work including SOS MATCH and VISTA. ROMAN compresses environments into sparse, object-centric maps that are orders of magnitude smaller than traditional representations, while still enabling accurate re-localization and loop closure under extreme viewpoint changes. I also discuss the interaction between perception and control, with a focus on safety filtering for systems that rely on learned perception models. Finally, I present results from simulation and hardware experiments and conclude with open challenges in building resilient autonomous aerial systems. Together, these advances move us closer to reliable multi-robot autonomy with meaningful real-world impact. [For the speaker's biographical sketch, click here.]
Posted January 2, 2026
Last modified March 10, 2026
Control and Optimization Seminar Questions or comments?
10:30 am – 11:20 am Joint Computational Mathematics and Control and Optimization Seminar to Be Held In Person at Location TBA and on Zoom (click here to join)
Jia-Jie Zhu, KTH Royal Institute of Technology in Stockholm
Optimization in Probability Space: PDE Gradient Flows for Sampling and Inference
Many problems in machine learning and Bayesian statistics can be framed as optimization problems that minimize the relative entropy between two probability measures. In recent works, researchers have exploited the connection between the (Otto-)Wasserstein gradient flow of the Kullback-Leibler (or KL) divergence and various sampling and inference algorithms, interacting particle systems, and generative models. In this talk, I will first contrast the Wasserstein flow with the Fisher-Rao flows of a few entropy energy functionals, and showcase their distinct analysis properties when working with different relative entropy driving energies, including the reverse and forward KL divergence. Building upon recent advances in the mathematical foundation of the Hellinger-Kantorovich (HK, a.k.a. Wasserstein-Fisher-Rao) gradient flows, I will then show the analysis of the HK flows and its implications in examples of machine learning tasks.
Event contact: Susanne Brenner
Posted January 15, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Krishnendu Kar, Louisiana State University
TBD
TBD
Posted March 1, 2026
3:30 pm – 4:30 pm Lockett 232
Simon Bortz, University of Alabama
TBA
Posted January 15, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Nilangshu Bhattacharyya, Louisiana State University
TBD
TBD
Posted February 5, 2026
Last modified February 6, 2026
Control and Optimization Seminar Questions or comments?
9:30 am – 10:20 am Zoom (click here to join)
Wonjun Lee, Ohio State University
Linear Separability in Contrastive Learning via Neural Training Dynamics
The SimCLR method for contrastive learning of invariant visual representations has become extensively used in supervised, semi-supervised, and unsupervised settings, due to its ability to uncover patterns and structures in image data that are not directly present in the pixel representations. However, this success is still not well understood; neither the loss function nor invariance alone explains it. In this talk, I present a mathematical analysis that clarifies how the geometry of the learned latent distribution arises from SimCLR. Despite the nonconvex SimCLR loss and the presence of many undesirable local minimizers, I show that the training dynamics driven by gradient flow tend toward favorable representations. In particular, early training induces clustering in feature space. Under a structural assumption on the neural network, our main theorem proves that the learned features become linearly separable with respect to the ground-truth labels. To support the theoretical insights, I present numerical results that align with the theoretical predictions.
Posted March 9, 2026
3:30 pm Lockett 232
Alexander Burgin, Georgia Tech
TBA
Posted January 15, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Anurakti Gupta, Louisiana State University
TBD
TBD
Posted December 27, 2025
Last modified February 25, 2026
Control and Optimization Seminar Questions or comments?
9:30 am – 10:20 am Zoom (click here to join)
Aris Daniilidis, Technische Universität Wien
Variational Stability of Alternating Projections
The alternate projection method is a classical approach to deal with the convex feasibility problem. We shall first show that given two nonempty closed convex sets $A$ and $B$, the consecutive projections $x_{n+1} = PB(PA(x_n))$, $n \ge 1$ produce a self-contacted sequence, providing in particular an alternative way to establish convergence in the finite dimensional case [2]. In infinite dimensions, a regularity condition is required to ensure convergence of the above sequence $\{x_n\}_{n\ge 1}$ [4]. In [3], it was established that a regularity condition from [1] also ensures the variational stability of the above method. In this talk, we shall complete this result and show that variational stability is actually equivalent to the aforementioned regularity assumption. REFERENCES: [1] H. Bauschke, J. Borwein, On the convergence of von Neumann’s alternating projection algorithm for two sets, Set-Valued Anal. 1 (1993), 185–212. [2] A. Bohm, A. Daniilidis, Ubiquitous algorithms in convex optimization generate self-contracted sequences, J. Convex Anal. 29 (2022) 119–128. [3] C. De Bernardi, E. Miglierina, A variational approach to the alternating projections method, J. Global Optim. 81 (2021), 323-350. [4] H. Hundal, An alternating projection that does not converge in norm, Nonlinear Anal. 57 (2004), 35–61.
Posted January 15, 2026
Last modified January 22, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Fabian Espinoza de Osambela, Louisiana State University
TBD
TBD
Posted January 2, 2026
Control and Optimization Seminar Questions or comments?
9:30 am – 10:20 am Zoom (click here to join)
Behçet Açıkmeşe, University of Washington
AIAA and IEEE Fellow
Optimization-Based Design and Control for Next-Generation Aerospace Systems
Next-generation aerospace systems (e.g., asteroid-mining robots, spacecraft swarms, hypersonic vehicles, and urban air mobility) demand autonomy that transcends current limits. These missions require spacecraft to operate safely, efficiently, and decisively in unpredictable environments, where every decision must balance performance, resource constraints, and risk. The core challenge lies in solving complex optimal control problems in real time, while (i) exploiting full system capabilities without violating safety limits, (ii) certifying algorithmic reliability for critical guidance, navigation, and control (GNC) systems, and (iii) co-designing hardware and software subsystems for optimal end-to-end performance. Our solution is optimization-based autonomy. By transforming GNC challenges into structured optimization problems, we achieve provably robust, computationally tractable solutions. This approach has already revolutionized aerospace, e.g., reusable rockets land autonomously via real-time trajectory planning, drones navigate dynamic obstacles, and spacecraft perform precision docking, all powered by algorithms that solve optimization problems with complex physics-based equations and inequalities in milliseconds. Emerging frontiers (such on-orbit satellite servicing, multi-vehicle asteroid exploration, large-scale orbital spacecraft swarms, and global hypersonic transport) push these methods further. Yet barriers remain, e.g., handling non-convex constraints, ensuring solver resilience, large-scale optimization for decision making and co-design, and bridging the gap between theory and flight-ready systems. This talk explores how real-time optimization is rewriting the rules of autonomy, and how researchers can turn these innovations into practice, propelling aerospace engineering into an era where aerospace systems think, adapt, and perform at the edge of the possible.
Posted March 6, 2026
Applied Analysis Seminar Questions or comments?
3:30 pm 233 Lockett Hall
Yunfeng Zhang, University of Cincinnati
TBA
Event contact: Xiaoqi Huang
Posted January 15, 2026
Informal Geometry and Topology Seminar Questions or comments?
3:30 pm – 4:30 pm Lockett Hall 233
Huong Vo, Louisiana State University
TBD
TBD
Posted January 24, 2026
Control and Optimization Seminar Questions or comments?
10:30 am – 11:20 am Note the Special Seminar Time. Zoom (click here to join)
Michael Friedlander, University of British Columbia
SIAM Fellow
Seeing Structure Through Duality
Duality is traditionally introduced as a source of bounds and shadow prices. In this talk I emphasize a second role: revealing structure that enables scalable computation. Starting from LP complementary slackness, I describe a generalization called polar alignment that identifies which "atoms" compose optimal solutions in structured inverse problems. The discussion passes through von Neumann's minimax theorem, Kantorovich's resolving multipliers, and Dantzig's simplex method to arrive at sublinear programs, where an adversary selects worst-case costs from a set. The resulting framework unifies sparse recovery, low-rank matrix completion, and signal demixing. Throughout, dual variables serve as certificates that decode compositional structure.
Posted January 5, 2026
Control and Optimization Seminar Questions or comments?
9:30 am – 10:20 am Zoom (click here to join)
Necmiye Ozay, University of Michigan
IEEE Fellow, and ONR Young Investigator, NASA Early Career Faculty, and NSF CAREER Awardee
TBA