PhD @rllabmcgill @MILAMontreal, Intern @MSFTResearch Former RS Intern @DeepMind, @Intel, @UF, @IITKanpur, Robert Bosch, @VIT_univ she/her. On the Job Market!
Sep 26, 2020 • 17 tweets • 5 min read
“X papers accepted at Y”
~ What people don’t tell about paper acceptances! ~ A thread #AcademicChatter#phdlife1/N Many papers that you see accepted now would have been very likely a second or a third submission! That doesn’t mean they are not worthy instead they actually took a lot more work including feedback from multiple reviewers, revisions, skilled rebuttals & perseverance!
Sep 22, 2020 • 22 tweets • 5 min read
Applying for grad school? Sharing here a few pointers on grad school applications! Pl feel free to share w/ folks who might benefit! Disclaimer: I am not an expert! I came across some questions from different people and I see a pattern, so here we go: #AcademicChatter 0/N
Where to apply? How to do this? Start with a list of schools 3 dream schools, 4 would love to go, 3 safe( will get in most likely)! Google sheets, to do lists, color codes, then marie kondo the hell out of this process! You got this! 1/N
Aug 8, 2020 • 6 tweets • 2 min read
Why is there zero *explicit* training on almost everything that matters a lot in academia except research? Be it reviewing, writing, communication, presentation skills, or even networking. They are left for each to hone & champion majorly by themselves! 1/N
The advisor and peers ofcourse help one develop such skills and get better at these over time! But it is often after many attempts people in later career stages say “I wish someone told me this earlier..” I don’t even believe the entire burden should be on the advisor alone! 2/N
Jul 2, 2020 • 4 tweets • 3 min read
Humans have a remarkable understanding of which states afford which behaviors. We provide a framework that enables RL agents to represent and reason about their environment through the lens of affordances bit.ly/31qjlSv
#ICML2020 paper from my internship @DeepMind 1/4
In this work, we develop a theory of affordances for agents who learn and plan in Markov Decision Processes. Affordances play a dual role. On one hand, they allow faster planning. On the other hand, they facilitate more efficient learning of transition models from data. 2/4
Jul 2, 2020 • 4 tweets • 3 min read
Humans have a remarkable understanding of which states afford which behaviors. We provide a framework that enables RL agents to represent and reason about their environment through the lens of affordances bit.ly/31qjlSv
#ICML2020 paper from my internship @DeepMind 1/4
In this work, we develop a theory of affordances for agents who learn and plan in Markov Decision Processes. Affordances play a dual role. On one hand, they allow faster planning. On the other hand, they facilitate more efficient learning of transition models from data. 2/4
