Colloquium Series
Spring 2025
April 11, 2025
Amol Aggarwal, Columbia University
Topic: TBD
Time: 4:00-5:00 pm
Location: TBD
Reception: TBD
Abstract: TBD
March 7, 2025
Jen Horn, Georgia Institute of Technology
Topic: TBD
Time: 4:00-5:00 pm
Location: TBD
Reception: TBD
Abstract: TBD
February 7, 2025
Nick Trefethen, University of Oxford
Topic: TBD
Time: 4:00-5:00 pm
Location: TBD
Reception: TBD
Abstract: TBD
Fall 2024
November 1, 2024
Lenore Cowen, Department of Computer Science and Department of Mathematics, Tufts University
Topic: Pathways for Learning from Structure and Organization of Protein Interaction Networks
Time: 4:00-5:00 pm
Location: 113 Breaker Hall
Reception: JCC 501 5:00-6:00 pm
Abstract: Biological networks are powerful resources for the discovery of genes and genetic modules that drive disease. Similar to in the social networks analysis domain, diffusion-based low-dimensional network embedding methods have proved quite powerful for biological networks. In particular, these methods have been highly successful in creating coherent local neighborhoods that correlate to gene function, enabling the downstream use of the entire machine learning toolbox to perform multiple inference tasks on these networks. We highlight the recent success of diffusion-based methods in biological networks for gene function prediction, link prediction, and for disease module prediction. We also discuss structural ways in which some types of biological networks seem to be organized differently than social networks, and show the advantage of customizing methods for particular types of biological network data. Also, biological domain offers unique additional sources of principled structured data organization (such as evolution), that can be leveraged to improve inference, resulting in some interesting open problems in multiplex network inference. If time permits, we will present some very recent work on how we are using these methods to understand coral reef resilience to heat stress in the Anthropocene.
October 18, 2024
Marc Hodes, Department of Mechanical Engineering and Department of Mathematics, Tufts University
Topic: Analytical Solutions Elucidating Transport Phenomena on Superhydrophobic Surfaces
Time: 4:00-5:00 pm
Location: JCC 270
Reception: JCC 501 5:00-6:00 pm
Abstract: Superhydrophobic surfaces (SHs) are regularly microfabricated to mimic the lubricating properties of “self-cleaning” lotus leaves by trapping a gas layer beneath a portion of the liquid flowing over them. Technological applications exploiting them include overcoming diYusion- limited mixing within mm-scale droplets of liquid for chemical assays and pumping of liquid in microfluidic circuits. The analysis of momentum/heat/mass/charge transport phenomena on SHs is mathematically challenging because of mixed Dirichlet-Neumann boundary conditions as a consequence of (flat) liquid-solid interfaces adjacent to (curved) liquid-gas interfaces. Over the past decade we have applied mathematical techniques (asymptotics, conformal maps, boundary perturbations, reciprocity, etc.) to resolve a suite of problems. I will describe our solution approach to one such problem, viz., heat transfer to a liquid flowing over a SH textured with ridges (on which the liquid is suspended) that are oriented transverse to the flow. Then, I will discuss the ramifications of our results on the direct liquid cooling of microelectronics, whereby a liquid metal is pumped through the Silicon comprising a microprocessor and related physical experiments in our lab. Finally, I will, briefly, discuss the solutions we have obtained to other problems related to transport phenomena on SHs.