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Divya Nori
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Divya Nori
@divnori
CS PhD @Stanford @ArcInstitute | @MIT alum | AI x Bio
Palo Alto, CA
divnori.github.io
Joined July 2020
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  • user avatar
    Divya Nori
    @divnori
    Jul 6, 2024
    Introducing RNAFlow, a protein-conditioned RNA🧬generative model for structure and sequence design. Excited to present this work, mentored by @WengongJin, @icmlconf in a few weeks! Paper: arxiv.org/pdf/2405.18768 Thread: ⬇️🧵
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    Divya Nori
    @divnori
    Jul 10, 2025
    🔥 Introducing BindEnergyCraft (BECraft), the BindCraft pipeline you know and love, now enhanced with an energy-based loss to boost in silico binder success! Thrilled to present this as an oral at ICML @genbio_workshop next week 📄 Paper: arxiv.org/abs/2505.21241 🧵Thread⬇️
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    Divya Nori
    @divnori
    Dec 12, 2023
    How well do zero-shot in silico metrics predict experimental success of AI-designed antibodies? I’ll be at @NeurIPSConf this week with @abscibio, presenting work that explores this question. Paper: arxiv.org/abs/2312.05273 Collaborators: @amirshanehsaz @SimMat20 🧵Thread:👇 1/5
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    arxiv.org
    Evaluating Zero-Shot Scoring for In Vitro Antibody Binding...
    The success of therapeutic antibodies relies on their ability to selectively bind antigens. AI-based antibody design protocols have shown promise in generating epitope-specific designs. Many of...
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  • user avatar
    Divya Nori
    @divnori
    Oct 24, 2025
    for the past few years, pushing the frontier of generative biology has been my driving goal. this summer as part of the team @valthostech, i realized that as these capabilities advance, it’s more important than ever to deploy and operationalize them to safeguard humanity against
    user avatar
    Valthos
    @ValthosTech
    Oct 24, 2025
    Valthos builds next-generation biodefense. Of all AI applications, biotechnology has the highest upside and most catastrophic downside. Heroes at the frontlines of biodefense are working every day to protect the world against the worst case. But the pace of biotech is against
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  • user avatar
    Divya Nori
    @divnori
    Jul 25, 2024
    Poster #109 at 1:30 pm today!
    user avatar
    Divya Nori
    @divnori
    Jul 6, 2024
    Introducing RNAFlow, a protein-conditioned RNA🧬generative model for structure and sequence design. Excited to present this work, mentored by @WengongJin, @icmlconf in a few weeks! Paper: arxiv.org/pdf/2405.18768 Thread: ⬇️🧵
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    5.1K
  • user avatar
    Divya Nori
    @divnori
    Sep 27, 2024
    Replying to @AnirudhValiveru
    send the playlist 👀
    201
  • user avatar
    Divya Nori
    @divnori
    Dec 12, 2023
    Replying to @divnori
    This experimental insight shows that the development of robust, zero-shot filters is an important research gap. Excited to chat about new strategies for antibody scoring and design this week! Check out our poster at @workshopmlsb @AI4D3 @genbio_workshop 5/5
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  • user avatar
    Divya Nori
    @divnori
    Sep 10, 2025
    Had some downtime before starting my PhD and decided to get back into creative writing. Ended up with a short essay on taste—in writing, in research, and why it feels hard to cultivate yet more important in the AI era. Sharing if you’d like to read :) divnori.github.io/blog/
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  • user avatar
    Divya Nori
    @divnori
    Jul 6, 2024
    Replying to @divnori
    RNAs can be engineered to perform versatile functions, particularly through their interactions with specific protein binding partners.
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  • user avatar
    Divya Nori
    @divnori
    Oct 17, 2023
    Replying to @cory
    Interested!
    60
  • user avatar
    Divya Nori
    @divnori
    Jul 6, 2024
    Replying to @divnori
    If you’d like to chat about RNAFlow, or ML for biology in general, please reach out! Excited to connect @icmlconf 🧬🤓
    667
  • user avatar
    Divya Nori
    @divnori
    Jul 6, 2024
    Replying to @divnori
    We evaluate whether RNAFlow can design the sequence and structure of an aptamer that binds to GRK2, a target of interest for chronic heart failure. We provide a known binding motif of 4-nucleotides. RNAFlow’s predictions resemble the true aptamer’s sequence and structure!
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  • user avatar
    Divya Nori
    @divnori
    Dec 12, 2023
    Replying to @divnori
    AI-based antibody design protocols have shown success in generating highly-specific binders, but due to prohibitive screening costs, the diverse candidate designs need to be filtered. 2/5
    416
  • user avatar
    Divya Nori
    @divnori
    Jul 6, 2024
    Replying to @divnori
    Further, we model the dynamic nature of RNA. Over the course of flow matching inference, RNAFlow generates a trajectory of structures. The final RNA sequence design is conditioned on the last few inference outputs which approximate a conformational ensemble.
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    383

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