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Today, Friday, March 6, 2026

Posted February 26, 2026

LSU SIAM Student Chapter

11:00 am – 12:30 pm Lockett Hall-Keisler Lounge

Harbir Antil, George Mason University
Malena Espanol, Arizona State University
A Lunch with SCALA Speakers

A lunch and informal discussion providing an opportunity to ask questions before SCALA.


Posted September 3, 2025
Last modified January 14, 2026

Conference

1:00 pm – 4:00 pm Saturday, March 7, 2026 Digital Media Center Theatre

Scientific Computing Around Louisiana (SCALA) 2026

http://www.cct.lsu.edu/SCALA2026


Posted February 26, 2026

Combinatorics Seminar Questions or comments?

2:30 pm Lockett 233 (Simulcast via Zoom)

Zi-Xia Song, University of Central Florida
Dominating Hadwiger's Conjecture

A dominating $K_t$ minor in a graph $G$ is a sequence $(T_1,\cdots,T_t)$ of pairwise disjoint non-empty connected subgraphs of $G$, such that for $1 \leq i < j \leq t$, every vertex in $T_j$ has a neighbor in $T_i$. Replacing "every vertex in $T_j$" by "some vertex in $T_j$" retrieves the standard definition of a $K_t$ minor. The strengthened notion was introduced in 2024 by Illingworth and Wood, who asked whether every graph with chromatic number $t$ contains a dominating $K_t$ minor. This is a substantial strengthening of the celebrated Hadwiger's Conjecture, which asserts that every graph with chromatic number $t$ contains a $K_t$ minor. Sergey Norin referred to this question as the "Dominating Hadwiger's Conjecture" and believes it is likely false. In this talk, we present our recent work on the Dominating Hadwiger's Conjecture and discuss the key ideas of our results. Joint work with Michael Scully and Thomas Tibbetts.

Monday, March 16, 2026

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

Tuesday, March 17, 2026

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

Wednesday, March 18, 2026

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 March 5, 2026

Informal Analysis Seminar Questions or comments?

3:30 pm – 3:30 pm Lockett 233

Long Teng, LSU
Doubling Inequalities for Schr\"odinger operators with power growth potentials

TBD

Friday, March 20, 2026

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.

Monday, March 23, 2026

Posted January 11, 2026

Applied Analysis Seminar Questions or comments?

3:30 pm – 4:30 pm Lockett 223

Zhiyuan Geng, Purdue University
TBA

Wednesday, March 25, 2026

Posted March 3, 2026

Harmonic Analysis Seminar

3:30 pm Lockett 232

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.

Event contact: Rui Han


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

Thursday, March 26, 2026

Posted January 15, 2026

Colloquium Questions or comments?

3:30 pm Lockett 232

Kumar Murty, University of Toronto
TBA

Friday, March 27, 2026

Posted January 5, 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
TBA


Posted January 2, 2026
Last modified January 8, 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
TBA

Wednesday, April 1, 2026

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

Harmonic Analysis Seminar

3:30 pm – 4:30 pm Lockett 232

Simon Bortz, University of Alabama
TBA

Wednesday, April 8, 2026

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

Friday, April 10, 2026

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.

Monday, April 13, 2026

Posted February 9, 2026

LSU SIAM Student Chapter

12:30 pm – 2:00 pm Keisler Lounge

Industry Speaker

Wednesday, April 15, 2026

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

Friday, April 17, 2026

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.

Wednesday, April 22, 2026

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

Friday, April 24, 2026

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.

Wednesday, April 29, 2026

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

Friday, May 1, 2026

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.

Friday, May 8, 2026

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