〈 Berger | Dillon 〉

Vin de Silva works on topological data analysis using persistent cohomology so he'll probably talk about that. He's studied the "interleaving distance" between persistence modules, using category theory to treat it and the Gromov-Hausdorff metric in the same setting. (cont)pic.twitter.com/F8Uak5DsUS

Brendan Fong is working with David Spivak at MIT. They wrote a great book on applied category theory: http://www.brendanfong.com/  and developed a graphical calculus for logic in regular categories. He's also using category theory to unify learners and lenses. (cont)pic.twitter.com/m4HFM1TBJ2

Nina Otter is at UCLA and the University of Leipzig. She's worked with Ulrike Tillmann and Heather Harrington on stratifying multiparameter persistent homology, and is now working on a categorical formulation of positional and role analysis in social networks. (cont)pic.twitter.com/Tqj4R3lu1g

Evan Patterson is a statistics grad student at Stanford. He's worked on knowledge representation in bicategories of relations, and on teaching machines to understand data science code by the semantic enrichment of dataflow graphs: https://www.epatters.org/papers/  (cont)pic.twitter.com/Jb4bExQgv1

Blake Pollard is working with Spencer Breiner and Eswaran Subrahmanian at the National Institute of Standards and Technology, using category theory to help develop the "smart grid" - the decentralized power grid we need now. https://sites.google.com/view/blakepollard/ … (cont)pic.twitter.com/mZWSLcgzfm

Prakash Panangaden (@prakash127) has long been a leader in applied category theory, focused on semantics and logic for probabilistic systems and languages, machine learning, and quantum information theory. https://www.cs.mcgill.ca/~prakash/  (cont)pic.twitter.com/JuFbKSNUVq

David Spivak at MIT wrote "Category Theory for the Sciences" and more recently "Seven Sketches" with Brendan. He just launched Conexus, which plans to award grants of up to $1.5 million to startups that use category theory. http://conexus.ai/  (cont)pic.twitter.com/LqDgJw6AzB

Brad Theilman is a grad student in computational neuroscience at U.C. San Diego. He's using algebraic topology to design new techniques for quantifying the spatiotemporal structure of neural activity in the auditory regions of the brain of the European starling. (cont)pic.twitter.com/w7bA32ExPP