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Department of Mathematics


The DASIV center is a hub of academic excellence and innovation in the field of machine learning and applied mathematics. It organizes various events and activities to disseminate cutting-edge research and foster collaboration among scholars and practitioners.

Current Events

Workshop on Variationally Stable Neural Networks

A one-and-a-half day workshop with guest lecturers speaking on advancements in training neural networks.

February 16 – 17

Applied and Computational Mathematics Seminar

The Department of Mathematics partners with the DASIV Center to host a seminar series of applied and computational mathematics. View the schedule to see details of both future and past talks.

Previous Events

Towards the approximation of parametric functions with colliding jumps

When: December 03, 2018 at 2:00pm

Where: Sumwalt 206

Speaker: Gerrit Welper (University of Florida)

The Shattered Urn

When: November 13, 2018 at 4:30pm

Where: LeConte 412

Speaker: John Burkardt (University of South Carolina)

Abstract: Sudoku, Instant Insanity, Tangrams, the Soma Cube, Pentomino Tiling and even logic puzzles like "Who Owns the Zebra" can all be thought of as tasks in which a "shattered" or disassembled object needs to be reconstructed from a collection of pieces.

Whether you are fixing a broken Greek urn, or solving a puzzle, a standard technique involves backtracking, that is, making a series of guesses until you hit a dead end, and then backing up to the last choice you made and trying the next one. This is a steady and sure procedure, but can be slow, and doesn't provide much insight into the problem.

Many of these problems can instead, almost magically, be turned into the task of solving an underdetermined linear system, something we know a lot about. I will concentrate on the particular case of tiling a region with polyominoes.

An Optimal Adaptive Fictitious Domain Method

When:  January 23, 2018 at 4:30pm

Where:  LeConte 312

Speaker: Rob Stevenson

Abstract: We consider a Fictitious Domain formulation of an elliptic PDE, and solve the arising saddle-point problem by an inexact preconditioned Uzawa iteration.

Solving the arising ‘inner’ elliptic problems with an adaptive finite element method, we prove that the overall method converges with the best possible rate.

This is a joint work with S. Berrone (Torino), A. Bonito (Texas A&M), and M. Verani (Milano)


Challenge the conventional. Create the exceptional. No Limits.