
Terry Kim
@thtrkim
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@ucberkeley, @berkeleyML
Berkeley, CA
Joined February 2024
RT @namrata_anand2: šWeāre excited to launch DSG2-mini, our newest AI protein design model, now available in DiffuseSandboxā³š, our new appā¦.
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Iām especially grateful to Prof. Jamie Cate and Dr. Conner Langeberg for their early guidance in helping me get involved in research. Looking forward to meeting other researchers and learning at RECOMB!.#RECOMB2025 #EMBC2025 #AI4Science #MLforBio.
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(4/5). Especially want to thank the Innovative Genomics Institute for providing funding to travel and attend RECOMB 2025. And to the organizers @RECOMB_conf @IEEEembs.
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(3/5).Iāll be presenting our poster on Day 2 of @RECOMBconf 2025!.This project is one of my first experiences leading a research effort from start to finish, and I am still in the process of learningāboth technically and conceptuallyāabout the intersection of biology and ML.
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(1/5).Iām pleased to share that my research with @seowondeog12052 has been accepted to RECOMB 2025 (Poster) and IEEE EMBC 2025 (Paper)!.Preprint: We introduce a generative approach to pesticide designāoptimizing small molecules to reduce toxicity.
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RT @aakarshv1: Join us on Monday 3/10 for our latest installment of the BioML @ Berkeley seminar series! We'll be learning from the exceptiā¦.
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RT @MeTownOfficial: MeTown is at CES šššš!. Come experience our hyper-realistic fashion 3D digitization service in person - EVOVA 3D ShowRoā¦.
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RT @alishbaimran_: Excited to share work I had the opportunity to co-lead at @czbiohub! We introduce DynaCLR, a self-supervised framework fā¦.
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RT @henryHM_ko: The largest protein generative model, ESM-3, was released this morning and one of its training breakthroughs involves FP8 pā¦.
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RT @henryHM_ko: I drew a GPU timeline that includes the evolution of features starting from the Volta series all the way up to the recent Bā¦.
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RT @namrata_anand2: Iām excited to share some of our progress at @Diffuse_Bio today, about a year and a half into our journey! 1/.
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My research interests or topics are genomics structure prediction and protein therapeutics, Ā I learned so much by reading Abhiās substack. I wanted to share these resources + knowledge I personally earned with more Korean readers who are entering this field.
for any of my Korean followers: my primer on ML for antibody engineering post has been translated to Korean!. massive s/o to Terry Kim for doing this:
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RT @alishbaimran_: How does AlphaFold3 predict the structures of proteins, DNA/RNA, ligands and other biomolecules? I did a deep dive intoā¦.
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RT @evocryptid: Snaps from last night's BioML lecture on protein engineering with AlphaFold2, ProteinMPNN, and RFdiffusion, led by the incrā¦.
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RT @SeyoneC: Come to Berkeley tomorrow to learn about the architectures behind the latest advancements in protein design from @aakarshv1! Lā¦.
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RT @BerkeleyML: Come hear @aakarshv1 talk about machine learning for protein engineering! The talk will give an overview of AlphaFold2, RFDā¦.
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RT @jajoosam: Join us on Monday, Feb 12 for a seminar from the team at @ArcadiaScience, on how they've been using ML to accelerate biologicā¦.
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