Department of Mathematics
Mathematics Colloquium
OrganizerThe Mathematics Department Colloquium typically meets on Thursdays from 12:20 pm to 1:10 pm in NAC 6/113, with lunch immediately after.
Most recent talks

Thursday, May 18, 2017, 12:20PM, NAC 6/113
Basilis Gidas (Brown University), Finding Genes and Towards a Mathematical Framework for Artificial Intelligence and Biological SystemsThe first half of the lecture will be on a statistical model for finding genes in the human genome. The model contains two parts: (a) A finite network (graph) which represents the overall architecture of a gene. The vertices in the network represent DNA signals (small patterns) associated with a gene and which are recognized by proteins and enzymes involved in the transcription and translation of genes. The edges of the network correspond to interactions among these signals and represent statistical variability in the architecture across genes; (b) each signal and each part of a gene is a piece of DNA with a random length as well as a random variability of its nucleotide sequence. The second part of the model articulates these variabilities.
The above gene finding procedure is conceptually similar to what is believed to underlie speech recognition whereby recognition involves two types of information: The acoustic signal represented by a concatenation of phonemes, and global regularities articulated by grammars (or syntax). The underpinning process in visual recognition is undoubtedly similar. And so is – many practitioners believe – the functioning of biological processes whereby two principles are at work: physics (biochemistry) and evolution. Physics controls the biochemical interaction of macromolecules, but it is evolution that produced the perfect “code” or “syntactic language” for the collective behavior of genes (Gene Regulatory Networks), or the collective behavior of proteins in Signal Transduction Pathways in cell growth, cell division or immunology. While specific questions and application in speech, vision, and biology have seen impressive advances and have lead to a great deal of mathematical innovation (e.g. modern statistical learning), an underpinning mathematical framework is missing. Though we do not have the framework, we know quite a bit of some of the problems the framework needs to articulate and some of the properties it needs to have. Building on the gene finding process, the second part of the talk will aim at identifying some key sources that makes the information processing in cognition and biology difficult, and hint towards a coherent hierarchical/grammatical framework.

Thursday, May 11, 2017, 12:20PM, NAC 6/113
Phil Kutzko (University of Iowa), The Math Alliance: partnering with faculty in the NYC Metropolitan Area to build a new, inclusive, community in the mathematical sciencesThe National Alliance for Doctoral Studies in the Mathematical Sciences (“Math Alliance”) is a national mentoring community of math sciences faculty working together to ensure that any student from a background that is underrepresented in the mathematical sciences and who has the desire and ability to earn a doctoral degree in a math sciences field will have the opportunity, encouragement, support and mentoring to do so. In order to institutionalize its early success, the Alliance has built a network of Master’s and doctoral programs who have made a commitment to train and mentor students from underrepresented backgrounds and has developed a program – FGAP – which works to place Alliance undergraduate and Master’s students in these programs. In order to ensure that promising undergraduates are attracted to math sciences disciplines regardless of where they attend school, the Alliance is partnering with local faculty to build regional alliances. It is my pleasure to tell you about the history and successes of our Math Alliance on the occasion of the launch of our new NYC Math Sciences Alliance!

Thursday, April 27, 2017, 12:20PM, SH205
Steve Smale (University of California at Berkeley), A life in mathematicspure and appliedMy perspective on the dichotomy of pure and applied mathematics will be discussed. This will be related to my own life as a mathematician, neither pure nor applied; but yet I I feel like a mathematician. I will give examples of scientists who have inspired me, Newton, von Neumann, Watson and Crick, Turing.