Seminar Series

Fall 2021 - IAM Seminar Series

Thursdays, 1:00 - 2:00pm EST in Kingsbury Hall, S145 (unless otherwise stated)

Date

Speaker, Affiliation

Topic/Title

September 2  

Prof. Greg Chini, Director, Integrated Applied  Mathematics Program - Kings S145

IAM Program Graduate Orientation

September 9

Dr. Laszlo Kindrat (IAM alum), Senior Software Engineer, Luminous Computing - Kings S145

A gentle introduction to machine learning compilers.

September 23

Dr. Markus Deserno, Professor of Physics, Carnegie Mellon University via Zoom. 

Curvaturte rigidity of asymmetric and differentially stressed membrane.

October 7

Dr. Mark E. Tuckerman, Prof. of Chemistry & Mathematics, New York University, via Zoom. 

To be announced.

October 21

Prof. Alessandro Laio, Full Professor in Statistical and Biological Physics at SISSA, Triestevia, Italy, via Zoom

Identifying informative distance measures in high-dimensional feature spaces

November 4

Dr. Francois Foucart, Assist. Prof., IAM and Physics 

To be announced.

November 18

 

 

December 2

Prof. Alan Lindsay, Assoc. Prof. Department of Applied and Computational Mathematics and Statistics, University of Notre Dame. 

To be announced.

Spring 2021 - IAM Seminar Series

Thursdays, 1230 -130 pm EST (unless otherwise stated)

Date

Speaker, Affiliation

Topic/Title

February 18

 

Prof. Baron Peters, W.H. and J.G. Lycan Professor of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign.

Multiscale Modeling Techniques for the Kinetics of Polymer Upcycling.

March 4

Dr. Duncan Hewitt, Lecturer in Applied Mathematics at University College London (UCL).

“Mud Swimming”: The Mechanics of Locomotion through a Visco-plastic Fluid.

March 18

 

Prof. Jeetain Mittal, Ruth H. and Sam Madrid Endowed Chair Professor of Chemical and Bimolecular Engineering, Lehigh University

Molecular organization in biology: What can computer simulations teach us?

April 29

 

Prof. Marek Petrik, Department of Computer Science, University of New Hampshire.

Robust Algorithms for Bayesian Batch Reinforcement Learning.