Research Scientist @NVIDIA | PhD @Mila_Quebec, BS @FudanUniversity | Deep Generative Learning | Proteins and Molecules. Views are my own.
Santa Clara, California, USA
Joined September 2021
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Our latest progress on binder design is here, now backed by massive-scale wet-lab validation! 🧬 Proud to contribute to this amazing team pushing the boundaries of what’s possible.
📢📢 Proteina-Complexa 📢📢
Atomistic Binder Design with Generative Pretraining and Test-Time Compute + Experimental Validation at Scale
⭐️ Project page (research.nvidia.com/labs/gen…) for:
📜 Method paper (ICLR 2026 Oral)
🧬 Wet lab paper
🛠️ Code & models
📁 Data
🧵 Thread
(1/n)
Zuobai Zhang retweeted
🚀 Excited to share BindClaw! 🦀
Starting from a prompt or research paper, BindClaw connects biological mechanisms to protein design: identify targets and binding sites → build mechanism-specific computational assays → generate and assess binders → refine designs using the results.
We use agents to evaluate whether designs fit the intended biological objective, including competition with a native partner and preference for a particular molecular state. 🧬
In a human-guided calmodulin campaign, 15 of 18 designs showed binding to calcium-loaded CaM, including subnanomolar binders supported by both BLI and SPR.
This work is an incredible team effort together with @DidiKieran , @saint__ai, @ Kyle Gion and @sacdallago and many others!
📄paper/project: research.nvidia.com/labs/dbr…
💻code: will be released in a few weeks!
Zuobai Zhang retweeted
As usual, stellar work by my colleagues, @julberner, Chao Liu, @amsabour , @ArashVahdat! 🔥
FastGan can accelerate any diffusion model! 🚀
The release also includes, finally, our "Align Your Flow" flow map code and weights, huggingface.co/nvidia/FastGe…, following popular demand! 🛠️
Tired of waiting for your diffusion models?
🚢 We just shipped a major FastGen update:
- new models: H3, LTX-2.5, LingBot-World, Cosmos 3, FLUX.2
- new methods: PDD, AYF, AnyFlow, Causal Forcing
- new features: multimodal distillation, image editing, camera conditioning, KV cache management, ComfyUI
🔗 Try it out here: github.com/NVlabs/fastgen
Zuobai Zhang retweeted
RFD4-Proteina on HuggingFace, both in Diffusers and interactive spaces to work with, try it out and let us know what you think!
Zuobai Zhang retweeted
Tired of waiting for your diffusion models?
🚢 We just shipped a major FastGen update:
- new models: H3, LTX-2.5, LingBot-World, Cosmos 3, FLUX.2
- new methods: PDD, AYF, AnyFlow, Causal Forcing
- new features: multimodal distillation, image editing, camera conditioning, KV cache management, ComfyUI
🔗 Try it out here: github.com/NVlabs/fastgen
Zuobai Zhang retweeted
Hi! We just released Mol-1, the frontier open-source cofolding. Try and benchmark it for your research and real-world problems: built for science, agents, and workflows.
Sign-up and cook. lab.molence.com
Open-sourced for all: github.com/molence/Mol-1
you're gonna like it
Introducing Mol-1: Open Frontier Biomolecular Intelligence 🚀🚀🚀
📊 75.0% on FoldBench-AB, near IsoDDE's reported 75.58%!!!
🧬 60k-token assemblies on one single H20, outperforming Anthropic 8/10.
🎯 VHHs binding hit rate as high as 63% with best SPR KD at 43 pM.
GitHub: github.com/molence/Mol-1
Try it: lab.molence.com
Zuobai Zhang retweeted
📢 RFD4-Proteina talks 📢
Great seeing @kpowgerade introduce RFD4-Proteina at @nvidia GTC Berlin, and fun presenting it with @nscorley at the GTC Biopharma summit!
Next up: our own little Eurotour - with guest appearances from David himself in the UK. Come by if you’re around! 🧵 1/3
Zuobai Zhang retweeted
🚀 Are you a PhD student pushing the boundaries of AI, robotics, graphics, or accelerated computing?
NVIDIA's Graduate Fellowship offers up to $60K in funding, mentorship from NVIDIA researchers, and a summer research internship!
⏳ Apply by October 30!
blogs.nvidia.com/blog/applic…
Zuobai Zhang retweeted
🚀 Today at GTC Berlin we introduced RFD4-Proteina! A close one-year collaboration between GenAIR and David Baker's group at @UWproteindesign !
🧬 Design proteins faster and send fewer, better candidates to the lab.
Introducing RFD4-Proteina, a new NVIDIA BioNeMo open model co-developed with @UWproteindesign.
▫️Fast: 13× faster generation than RFdiffusion3 at 200 residues
▫️ Smart: state-of-the-art across 12+ protein design tasks
▫️ Programmable: set your design inputs and use test-time compute on harder problems
Start with our binder-design tutorial nvda.ws/3VK9Uvr
Kieran is a beast 🔥 Go check out RFD4-Proteina!
Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org
Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30
Zuobai Zhang retweeted
Please help spread the word!
We’re hiring Research Scientists and Research Interns at NVIDIA Research to work on some of the most exciting problems in generative AI:
🌎 World Models & Video Diffusion
🧠 Diffusion Language Models
🧬 Biomolecule Design
If your research aligns with any of these areas, please apply directly through the links below.
Open positions + application links:
research.nvidia.com/labs/gen…
Zuobai Zhang retweeted
📢📢 Join us as a Research Scientist or Research Intern!
🛠️ Fundamental gen AI & practical applications
🧬 Text diffusion & protein flows
🌎 World models & molecule models
...and, although being slightly biased, with an amazing team 😃
For details, see @ArashVahdat 's message.
Please help spread the word!
We’re hiring Research Scientists and Research Interns at NVIDIA Research to work on some of the most exciting problems in generative AI:
🌎 World Models & Video Diffusion
🧠 Diffusion Language Models
🧬 Biomolecule Design
If your research aligns with any of these areas, please apply directly through the links below.
Open positions + application links:
research.nvidia.com/labs/gen…
Zuobai Zhang retweeted
We're hiring at NVIDIA, interns (2027) and full time. If you're interested in video and world models, discrete diffusion LLMs, or structural biology, apply using the links below!! 🔥
Please help spread the word!
We’re hiring Research Scientists and Research Interns at NVIDIA Research to work on some of the most exciting problems in generative AI:
🌎 World Models & Video Diffusion
🧠 Diffusion Language Models
🧬 Biomolecule Design
If your research aligns with any of these areas, please apply directly through the links below.
Open positions + application links:
research.nvidia.com/labs/gen…
Our team is hiring! Come and work with us on some exciting GenAI directions🔥
Please help spread the word!
We’re hiring Research Scientists and Research Interns at NVIDIA Research to work on some of the most exciting problems in generative AI:
🌎 World Models & Video Diffusion
🧠 Diffusion Language Models
🧬 Biomolecule Design
If your research aligns with any of these areas, please apply directly through the links below.
Open positions + application links:
research.nvidia.com/labs/gen…
Zuobai Zhang retweeted
💫 Large Language Continuous Diffusion Models
Presenting Sigma, the first large-scale (3B/8B) continuous diffusion LM (dLM) trained with likelihood.
📈 Comparable with discrete dLMs and AR on math and coding
🎛️ Enables meaningful study of inference-time interventions
Jointly led with Wei Guo (@WeiGuo01), Jean-Marie Lemercier (@jm_lemercier), Simon Welker (@_cobalamin)
Team: @YongganFu @mmkamani7 Sajad Norouzi @julberner @tomasgeffner @karsten_kreis @YongxinChen1 @MoleiTaoMath @jwthickstun @PavloMolchanov Ante Jukic @ArashVahdat @MardaniMorteza
Zuobai Zhang retweeted
Our wet-lab validation campaign for Proteina-Complexa is now on bioRxiv! It includes some new exciting experimental results, from large protein structures (fully codesigned!) to functional carbohydrate binders.
biorxiv.org/content/10.64898…
Thread with some of the additions 🧵1/n
Zuobai Zhang retweeted
Love seeing ideas travel this fast. 🚀
We haven’t released the code or even submitted the paper yet, but our Parallel Decoding Distillation (PDD) has already been independently implemented and used to accelerate MiniMax-H3. ⚡
More on FastGen-PDD: research.nvidia.com/labs/gen…
Another cool stuff from Alibaba!
MiniMax-H3 Acc LoRAs.
Parallel Decoding Distillation for efficient video gen in a few steps.
FL2VA + Ref2VA
huggingface.co/alibaba-pai/M…
Zuobai Zhang retweeted
Great to see our Parallel Decoding Distillation (PDD) already being applied to MiniMax-H3🚀
Alibaba scaled it up just a month after our paper release (before our code even dropped) - guess that proves how simple it is to implement!
Learn more about PDD: teapaw.org/julberner/status/20825…
Another cool stuff from Alibaba!
MiniMax-H3 Acc LoRAs.
Parallel Decoding Distillation for efficient video gen in a few steps.
FL2VA + Ref2VA
huggingface.co/alibaba-pai/M…
🧬 Agents for protein design are coming.
Great to see Proteina-Complexa in the mix as one of the seven designated binder generators 🔥! Building good open tools and building agents that can use them well turn out to be complementary problems.
Many drugs work by binding to a specific target in the body and blocking or changing what it does. An important first step in the drug development process is designing a molecule that can bind tightly to its target. Traditionally, that's meant weeks or months of expert work per target, sifting through a large number of candidates to identify the few that work.
We wanted to test if Claude could successfully design novel protein binders from scratch (also called de novo design). With a protein design prompt written by a human expert, Claude autonomously designed protein binders against 14 out of 15 targets.
We then worked with Adaptyv Bio and Twist Bioscience, who independently built and tested the proteins Claude designed.
Zuobai Zhang retweeted
@muni_bio now gives agents access to the wet-lab. Using @NVIDIAHealth's Proteina-Complexa + @adaptyvbio validation, muni found 3 sub-nanomolar binders, all of which were better than our hackathon winners.
Even if assays take days or weeks, the results automatically feed back into the agent, allowing you to orchestrate autonomous scientific research in parallel.
Zuobai Zhang retweeted
Very exciting to see how Proteina-Complexa in the hands of muni's agentic autoresearch pipeline produces sub-nanomolar binders for TREM2, scoring at the top of the leaderboard.
More about NVIDIA's Proteina-Complexa here: research.nvidia.com/labs/gen….
@muni_bio now gives agents access to the wet-lab. Using @NVIDIAHealth's Proteina-Complexa + @adaptyvbio validation, muni found 3 sub-nanomolar binders, all of which were better than our hackathon winners.
Even if assays take days or weeks, the results automatically feed back into the agent, allowing you to orchestrate autonomous scientific research in parallel.