Paul T Kim
@paultkim_ipd
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PhD Student, @UWproteindesign - excited to work on machine learning methods for rational protein design. Also core @DNADeviants.
Seattle
Joined November 2021
With David and the Baker Lab in the spotlight today, I wanted to share some insights into the @UWproteindesign and how it operates, a glimpse behind the curtain. I had planned to write this post-graduation, but now seems as good a time as any. (Got twitter blue free trial so this could all fit in less tweets!) First, the lab is enormous. ~60 grad students, ~60 postdocs, a handful of visitors, undergrads, and a surrounding institution of another 150 or so. Collaboration is strongly encouraged (even mandated) by David, who sets up pro-collaboration incentives. Notably, he's fine with grad students graduating without a sole first-author paper—it's acceptable to "only" have worked as a co-first author. This is a key ingredient in the secret sauce: the tight collaboration between wet lab and dry lab. It ensures that all our work is ultimately grounded in strong wet-lab validation—our "oracle" is the real world, not another computational model. While we have regular meetings for different subgroups and the entire group, much information travels through the lab via informal one-on-one interactions. In some ways, it reminds me of a classic "tribe of humans in the state of nature"—100-200 people with no clear hierarchy, passing information via "gossip". It’s maybe not the most complete way of ensuring everyone is on the same page, but saves time as we aren’t drowning in endless meetings. Does David stay in touch with all these grad students and post-docs? Remarkably, yes. Unlike some very large labs known for being run entirely by post-docs, he knows exactly what everyone is working on and the stage of their projects. Each member has monthly one-on-ones with him, and monthly subgroup meetings that David attends. If he suggests you try something at your previous one-on-one, you'd better have it done by the next. Does he actually contribute research ideas, or is he more of a detached big-picture project manager? Definitely the former. He understands the intricacies of a shocking range of topics. I'll be discussing some arcane deep learning concept with him, and then he'll turn around and talk to someone about the details of a catalytic mechanism. He's actually the most hands-on PI I've ever had—if anything, he verges on over-managing rather than being too detached. How does he keep track of everything? Partly, he's just a brilliant person with exceptional recall. But he has also built infrastructure above and below him in the lab to handle many of the details, bureaucracy, big picture, and management tasks. This allows him to spend most of his day doing what he's most passionate about and skilled at: walking around talking to people about science. He also lives very much in the moment and in his own words, “never thinks very far ahead". To keep up with tools, methods, and wet lab techniques, he does the occasional project and design campaign himself on the side when time allows. It's still a tremendous cognitive load to keep all this in his head, but as much as possible, he has offloaded non-scientific cognitive burdens. It helps that he’s in the lab in person most days of the year, rarely traveling for conferences or talks, instead doing them over Zoom or not attending. (1/2).
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”
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RT @pranamanam: FusOn-pLM is out in @NatureComms!!! 🎉 An INCREDIBLE effort (and a lot of sleepless nights! 🛏️) from my AMAZING 2nd year PhD…
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Evolution of the setup - personal laptop running separately w/ linked keyboard and mouse, ipad sidecar for terminal/calendar/todolist, poster board to not get distracted by people walking down the hall, logitech ergonomic keyboard and vertical mouse (saved my wrists)
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@internetvin @brandon_xyzw @KadriJibraan Lol it’s just an aggressive ass position to claim distinct superiority over three cities that are widely viewed as having some of the best food in the world
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@internetvin @brandon_xyzw @KadriJibraan Interesting. What I’m hearing is you guys are arguing that Toronto food scene is distinctly best in NA, above even other great food cities like SF/NY/LA. I have doubts, it’s a hard position to defend, but am open to the argument. Guess I gotta check out Toronto again soon.
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@internetvin @brandon_xyzw @KadriJibraan I’m guessing you and @KadriJibraan spent most of your time in SOMA/Downtown area and that’s why you believe this. Mission/Richmond/Sunset/Chinatown/North Beach is in league with any city on earth imo
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@katclone @Saraht0n1n You guys should check out the SF Commons for ideas, super cool community that I can’t wait to be a part of once I move back to the bay
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@ArtirKel I was inspired by this tweet (and quotes) to switch from morning intermittent fasting and having big dinners to no or light dinner and huge breakfasts. It’s been good! Definitely feel improved sleep.
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Basically the customer support experience with any Google produce. Idk what they are doing over there but it seems like anything that cannot be fully automated goes into a doom spiral of low level customer support reps saying they will try to escalate and then nothing happening.
I'm not able to get in touch with anyone except the automated chat, which just sends me a template-like email from a different name every 7 days (Venkatesh, Sai, Praveen, Abdullah). I'm also not eligible to upgrade to a higher support tier.
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@owl_posting @kulesatony @ZhongingAlong Super great post! My one suggestion would be maybe you could add a section on the promise of in situ tomography. The possibility to see what the cell is actually doing in real time is so cool, since there’s always so many unknown unknowns in cell biology.
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Great post, cryo is so cool.
A primer on ML in cryo-electron microscopy (cryo-EM) confused about cryo-EM??? i explain why people do it, how it works and some ML problems in the area via explanations of 3 @ZhongingAlong papers 7.9k words, 36 minutes reading time. ToC in thread❄️
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RT @soumithchintala: i rabbit-holed into the Genesis Sim codebase because the website is hypey and unclear; and I didn't want to just blind…
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this looks unreal
Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: . The Genesis physics engine and simulation platform is fully open source at We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: Project webpage: Documentation: 1/n
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RT @WorksInProgMag: Madrid’s metro was 71 miles long in 1995. That would be the world’s 51st longest today, reasonable considering Madrid i…
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Just IPD things ❤️ Another 160 gpus, brings the internal cluster up to 1079 gpus total.
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