Every other week we spotlight an OMSCS TA, so you can get to know who's behind the screen. Here are four questions for Jake Knigge who TAs CS 7642: Reinforcement Learning.
What do you do professionally?
I work for a technology company called OneChronos. We’re building an alternative trading system for equities (stocks) based on combinatorial auctions and optimization, so we get to play in a few fun sandboxes: finance/capital markets, machine learning, (all flavors of) optimization, and mechanism/market design among others.
Why do you TA for OMSCS?
I see it as an opportunity to simultaneously pay it back and (hopefully) pay it forward, where it is the positive experience that I’ve had in the program, which is undoubtedly a function of the TA teams for the courses I’ve taken—especially the RLDM (CS 7642) team from the spring of 2020. Also, being a TA forces me to clean up my thoughts and (mis)understandings about a topic; to put a Bayesian spin on it, my posterior is consistently being updated. And last, but certainly not least, it’s fun!
What's your advice for future students in OMSCS?
Run your own race and do your own time. Along those lines, I’ve found it useful to specify my OMSCS goals and pursue them in a way that pushes me and keeps me engaged and curious. Like Billy Madison said, "I'm here to learn," and I try to embrace that ethos (in its humor and its humility). I’ll augment Adam Sandler’s wisdom with that of Gauss: "It is not knowledge, but the act of learning, not possession but the act of getting there, which grants the greatest enjoyment."
What hobby or activity are you looking forward to getting back to once you're done with OMSCS?
I’m looking forward to a lot of things:
– spending more time with my wife, our families, and friends;
– focusing on work and putting what I’ve learned into practice; and
– resuming a few personal projects—working on a book on Markov chains, volunteering on (French mathematician) Michel Talagrand’s book on quantum field theory, training jiu-jitsu (aka getting rolled in my case), and playing music (albeit poorly).
