This Week in Mathematics

Department of Mathematics

This Week in Mathematics


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Next Week [Mar 01, 2026 - Mar 07, 2026]

Entries for this week: 5

Monday March 02, 2026

Applied and Computational Math Seminar [url]
Beyond the Resume: How to Get Hired in Competitive Industries
- Teeratorn Kadeethum, Siemens Energy
Time: 3:05pm Room: 101

Tuesday March 03, 2026

Applied and Computational Math Seminar
The Data Bottleneck in Neural Operators for Engineering Systems: Challenges and Paths Forward
- Teeratorn Kadeethum, Siemens Energy
Time: 3:05pm Room: 231
Abstract/Desc: Neural operators such as DeepONet and Fourier Neural Operators have shown remarkable promise in learning solution mappings for parametric partial differential equations, offering orders-of-magnitude speedups over traditional solvers. However, their deployment in real engineering systems faces a fundamental chicken-and-egg problem: training these data-hungry models demands large, high-fidelity datasets that are precisely what engineering applications struggle to provide. In practice, experimental measurements are expensive, sparse, and often limited to a handful of observable quantities — for instance, only a few discrete temperature readings may be available in a low-pressure turbine environment, while velocity and pressure fields remain entirely unobservable. High-fidelity simulations can in principle fill these gaps, but they carry their own burdens: long turnaround times, high computational cost, and persistent difficulties in calibration against complex real-world geometries. This talk examines the tension between the data requirements of modern operator learning and the realities of engineering data acquisition, and discusses emerging strategies — including physics-informed training, multi-fidelity fusion, transfer learning, and hybrid simulation-measurement frameworks — for charting a viable path forward.

- Sam Ballas, FSU
Time: 3:05PM Room: LOV 232

Thursday March 05, 2026

Financial Math
- Ololade Sowunmi,
Time: 3.05 Room: LOV 231

Algebra seminar
TBA
- Haoyang Liu, UCSB
Time: 3:05pm Room: Zoom
Abstract/Desc: TBA

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February