Seminar Series

Fall 2022 - IAM Seminar Series

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

Date

Speaker, Affiliation

Topic/Title

September 8

Prof. Greg Chini, Director, Integrated Applied  Mathematics Program.

Annual Meeting: IAM Graduate students and IAM Faculty and Staff.

September 22

Dr. Kim Lowell, Research Scientist, Center for Coastal and Ocean Mapping (CCOM), and Affiliate Research Professor, Earth Systems Research Center.

Extracting Shallow-Water Bathymetry from LiDAR Point Clouds Using Data Analytics

October 6

To be announced

To be announced

October 20

Dr. Ben Montemuro, IAM Alum, class of 2020

To be announced

November 3

Prof. Kai Germaschewski, IAM Program, Physics and Astronomy To be announced 
November 17 To be announced To be announced

Spring 2022 - IAM Seminar Series

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

Date

Speaker, Affiliation

Topic/Title

January 27

Prof. Easton White, Biological Sciences, UNH

Modeling socio-ecological dynamics in the face of disturbances

February 10

Prof. Rob Phillips, Fred and Nancy Morris Professor of Biophysics and Biology, California Institute of Technology.

A Language Whose Characters are Triangles.

Friday,    March 4

Prof. Gwynn Elfring, The University of British Columbia. (Joint seminar with Mechanical Engineering).

The hydrodynamic of active matter in inhomogeneous environments.

March 10

Prof. John Gibson, Department of Mathematics and Statistics, UNH.

Fluids and Dynamical Systems 

March 24

Prof. Scott Field, UMass Dartmouth. 

Learning high-fidelity gravitational wave models from numerical relativity data.

April 7

Prof. Daniel Zuckerman, Oregon Health & Science University.

Weighted Ensemble in biocomputation and beyond: A simple, powerful splitting algorithm for rare events and dynamics.

April 21

Prof. Mahadevan, Harvard University.

Folds, cuts and isometries: art and science

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 

IAM Program Graduate Orientation

September 9

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

A gentle introduction to machine learning compilers.

September 23

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

Curvature rigidity of asymmetric and differentially stressed membrane.

October 7

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

Topology, Molecular Simulation, and Machine Learning as Routes to Exploring Structure and Phase Behavior in Molecular and Atomic Crystals.

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, Assoc. Prof., IAM and Physics 

Numerical simulations of neutron star mergers

December 2

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

Mathematics of diffusive signaling with applications to chemoreception and nuclear scaling

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.