Reading · Irene Y. Chen - UC Berkeley and UCSF

This page cannot be shown here. You can still read it on the original site — the toolbar below keeps your place in the directory.

Advice for aspiring and current ML researchers Enormous list of resources for all things research-related – by Shaily Bhatt (@shaily99) Applications for computer science PhD – by Jean Yang (@jeanqasaur) Applying to Ph.D. Programs in Computer Science – by Mor Harchol-Balter Emailing professors – by Dan Roy (@roydanroy) Interviewing for PhD programs – by Nils Gehlenborg (@ngehlenborg) What should grad students be learning? – by Michael Mitzenmacher Starting out in AI research – by Tom Silver (@tomssilver) Expectations for advisors and students – by John Regehr (@johnregehr), Suresh Venkatasubramanian (@geomblog), and Matt Might (@mattmight) PhD Syllabus – by Mor Naaman (@informor) Handling math bullies – by Fan Chung Graham Combatting Anti-Blackness in the AI Community – by Devin Guillory (@databoydg) Paper writing tips – by Jacob Steinhardt Shortening papers – by Devi Parikh (@deviparikh) Responding to peer feedback – by Matt Might (@mattmight) Writing conference rebuttals – by Devi Parikh (@deviparikh), Dhruv Batra (@DhruvBatraDB), Stefan Lee (@stefmlee) Tweeting about papers – by Lisa Nivison-Smith (@LNivisonSmith) Reviewing conference papers – by Colin Raffel (@colinraffel) How to write a good conference review – CVPR 2020 Tutorial Academic job search in 10 questions – by Elissa Redmiles (@eredmil1) and Nicolas Papernot (@NicolasPapernot) Another academic job search guide – by Westley Weimer How to reject a candidate – by Sara Davis (@PsySciSar) Where to present research on machine learning, healthcare, and/or fairness Neural Information Processing Systems (NeurIPS) International Conference for Machine Learning (ICML) ACM Conference on Health, Inference, and Learning (CHIL) Fair ML for Health Workshop at NeurIPS Machine Learning for Health (ML4H) Workshop at NeurIPS Representative Machine Learning Women in Machine Learning Black in AI Queer in AI LatinX in AI (Dis)Ability in AI Muslims in ML Introductory guides Causal Inference textbook – by Miguel Hernan and Jamie Robins History of Fairness in ML – by Ben Hutchinson and Margaret Mitchell ML for Healthcare class at MIT – by course staff including myself

Resources

Comments