Assistant Prof @ Johns Hopkins CS. Interested in theory of ML, secure computation. All cat pictures are my own and do not represent the cats of my employer.
Joined March 2024
- Tweets 361
- Following 901
- Followers 1,282
- Likes 1,589
52 Photos and videos
Jess Sorrell retweeted
Jun 10
The de facto lockdown of CAISI is extremely disheartening. Wish more AI industry leaders would speak out, and not merely through policy documents but to POTUS directly.
@sama @elonmusk @demishassabis
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Congrats all!
Honoured that our 2016 paper, Robust Estimators in High Dimensions without the Computational Intractability, w/ Ilias Diakonikolas, Daniel Kane, Jerry Li, Ankur Moitra, Alistair Stewart, was awarded the 2026 Gödel Prize
This is the highest award for papers in theoretical CS. 1/7
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Jess Sorrell retweeted
May 29
Humans don’t follow a values list. We make predictions about how a community will respond to a behavior. That capacity, normative competence, is what we should be building into AI. Talked about it on Ethical Machines.
podcasts.apple.com/us/podcas…
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Jess Sorrell retweeted
@RLtheory makes a come back, with expanded scope, an awesome lineup of talks! This is going to be fun!
The RL Theory Seminar returns in June, one hour earlier. We're broadening the scope a bit, including RL for LLMs and robotics, and featuring a few more applied papers alongside foundations-oriented work. Please share widely!
We start next Tuesday with Daniel Russo.
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May 27
Awesome lineup @SimonsInstitute this week! Looking forward to the recordings. simons.berkeley.edu/workshop…
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May 19
Printing and framing this tweet for my office
Mar 5
things are gonna get weird. you must get commensurately weird.
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Jess Sorrell retweeted
May 19
We have a last-minute internship opening for summer/fall 2026---working with Samy Jelassi, who just joined us! Apply here: apply.careers.microsoft.com/…
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Jess Sorrell retweeted
Excited to announce our workshop on "Learning in an Agentic World" at COLT 2026!
We invite submissions for our Call for Abstracts (due June 1, 2026): tinyurl.com/mvwrvn7b
Thanks to my great co-organizers: Hedyeh Beyhaghi, Avrim Blum and @HanShao16!
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Jess Sorrell retweeted
Attention @arxiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents were generated. 1/
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Jess Sorrell retweeted
May 12
We just released the full course materials of the Iliad Intensive — a month-long, full-time AI alignment course for mathematicians, physicists, and theoretical computer scientists.
~20 contributors, 19 modules, at a depth that doesn't exist elsewhere for most of these topics. 🧵
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Jess Sorrell retweeted
May 8
Nobel laureate Al Roth has a great piece in @washingtonpost today on why we should compensate kidney donors. Kidney failure disproportionately hits Black and low-income Americans, costs Medicare $55B /yr, and most people who need a transplant will die without one. 🧵
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The birding slack channel is my favorite DSAI slack channel, don't tell Mark
May 7
Apparently, my students have brought binoculars to their office to bird watch during the day. The advantages of our new beautiful @HopkinsDSAI office space. 🦜🦆🕊️
Should I be worried about productivity?
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Jess Sorrell retweeted
Apr 28
alignment theory: we need fifty years worth of shard theory progress in five years
alignment practice: lets make sure to tell it no goblins twice so we're absolutely sure there's no goblins
gpt-5.5 prompt for codex seems to have a duplicated line trying to get it to not talk about creatures?
Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user's query.
[...]
Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user's query
gh link:
github.com/openai/codex/blob…
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Apr 28
Alessa is one of the most preternaturally productive, independent, and curious undergrads I've had the pleasure of meeting. If you have the opportunity to work with her, I cannot recommend taking it enough!
Alessa Carbo’s AI-powered translation of sign language videos earned her first authorship at a major natural language processing conference. Learn about her path to publishing: hub.jhu.edu/2026/04/21/an-un…
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Jess Sorrell retweeted
Apr 24
Proud to have contributed to this!
anthropic.com/news/election-…
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Apr 22
I took ~7 years off during undergrad. Worked at Starbucks, the postal service, a diner. Wasn't until making friends with some CS PhD students at UW Madison, who suggested sitting in on Eric Bach's class on the physics of computation, that I decided to go back (and then get a PhD)
Apr 22
I need more examples of people in academia who haven't had a linear path at all and missed years on the way to PhD and still did their PhD. I don't wanna feel all isolated here
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Apr 22
I got insanely lucky at multiple points along the way, and eternally grateful to the people who gave me a shot. It bums me out that non-traditional paths seem less and less viable every year
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Apr 21
If you're at ICLR and interested in stability in RL, go hunt down @marcel_hussing!
In “Replicable Reinforcement Learning with Linear Function Approximation,” @JessSorrell, @EricREaton, @marcel_hussing, @mkearnsupenn, @Aaroth, & @sikatasengupta develop replicable methods for linear function approximation in reinforcement learning: arxiv.org/abs/2509.08660 (5/13)
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Jess Sorrell retweeted
Apr 16
I've recently been getting invitations to talk about how to use AI tools to assist with TCS research. Its something I've been doing a lot, but don't have structured thoughts about how to explain process. But I'm going to try -- first such talk is tomorrow: cics.umass.edu/events/resear…
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Day 2 starting off with @kbanihas telling us about bounds for adaptive and non-adaptive replicable composition. Can get DP-like composition in non-adaptive setting by going through perfect generalization instead of DP!
Kicking off day 1 of the @EnCOREInstitut workshop on the Foundations of Replicability and Verifiability in AI with an excellent introduction to pseudodeterministic algorithms by the inimitable Shafi Goldwasser!
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Learning about causal inference from @AnayMehrotra, who's telling us about average treatment effect identification beyond assumptions of unconfoundedness and overlap!
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And wrapping up day 2 of talks, we have Mohammad Hossein Bateni talking about resilient algorithms!
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