Links
Links to people
Formative influence
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I learn a lot of Maths and other things from Christopher Douglas who also supervised my PhD.
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I learned a lot of Computer Science from Samson Abramsky who supervised the first part of my PhD.
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From undergrad to post-grad to post-doc, I’ve talked a lot of Maths with David Reutter.
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Sources of inspiration, motivation and support:
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My thesis examiners Andre Henriques and Mike Shulman,
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Highly inspiring: David Ayala, Michael Eichmair, John Francis, Emily Riehl, Matthijs Vákár, Dominic Verity, Jamie Vicary, Mahmoud Zeinalian, … (and many more)
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Enjoyable activities
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Getting caught in snow storms with Christoph Weis, Jan Steinebrunner, Luciana Bonatto and Thibault Décoppet
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Eating breakfast in the office with Emily Cliff, Craig Smith, Kieran Calvert and Richard Mathers
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Climbing with Alice Kerr and Filippos Sytilidis
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Trying to schedule a lunch with Lukas Brantner,
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Surfing with Nanook Bergmann,
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Solving physics homework with Henry Clausen,
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Learning new bird names from Allison Roth
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Accompanying Anton Richter on the piano,
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Meditating with Mikesh Udani,
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Sketching faces with José Ernesto Rodríguez,
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Making hot pot with Ruth Sang Jones, Ella Bentin and Albert Xiao.
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Acting as the personal trainer for Valentina Semenova and Julian Winkler,
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Mindfulness exercises on the gymnastic rings with Matthijs Vákár
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Getting crypto predictions from Benedikt Buenz,
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Evaluating the human condition with Marius Vollberg,
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My partner Chloé Colson does Maths too!
Links to things
General
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A central source of inspiration in all aspects always comes from the \(n\)-Category Cafe and the \(n\)Lab and its authors.
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Two fast ways of making commutative diagrams: quiver and tikzcd by Yichuan Shen.
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The Manifold Atlas for great summaries of what is known and what isn’t.
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Codeforces for coding puzzles.
Algebraic and Differential topology
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Jim Davis and Paul Kirk, Lecture notes in algebraic topology: fantastic notes for a grad student who has had a first course in algebraic topology.
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Peter May, A Concise Course in Algebraic Topology: a logical next step, after having had some exposure to category theory as well. This fills in many topics that are left as “projects” in the previous notes.
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Alexandru Scorpan, The wild world of 4-manifolds: gives useful intuition about all the non-intuitive (but not technically “wild”) things that one starts to see in dimension 4.
Category and Type Theory
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Samson Abramsky and Nikos Tzevelekos, Introduction to Categories and Categorical Logic.
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Emily Riehl, Categorical Homotopy Theory: a natural bridge between ideas from classical homotopy theory and category theory.
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Many authors, The HoTT Book: doubles as an introduction to type theory and many other things.
Computer science
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Sanjeev Arora and Boaz Barak, Computational Complexity: A Modern Approach
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Andriy Burkov, The Hundred-Page Machine Learning Book
Reading list/Comments
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R. Sadykov’s, “Elements of surgery theory”
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Antti Laaksonen, “Competitive Programmer’s Handbook”
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I’m also looking for material to teach me more mathematical physics, in order to understand better some of the challenges that fundamental physics is facing. If you have favorites, do let me know :-)
If anything should be added to the above, or doesn’t seem right, feel free to comment.