Brian L Trippe
@brianltrippe
Assistant Professor at @Stanford Statistics and @StanfordData | Prev postdoc @UWproteindesign and @Columbia. PhD from @MIT.
🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods for motif scaffolding. Why does this matter? Reproducibility & consistent evaluation have been lacking—until now. Paper: arxiv.org/abs/2502.12479 | Repo: github.com/blt2114/MotifB… A thread ⬇️
Super excited about this progress and next steps! Come chat with us at our poster tomorrow morning if you’re at #ICML2025
Predicting how mutations affect protein binding is key for drug design—but deep learning tools lag behind physics. StaB-ddG closes the gap: combining stability models + smart pretraining to match FoldX accuracy at >1000× the speed. Paper: arxiv.org/abs/2507.05502 Code:…
Actually happening at **11 AM ET** !
Next Tues (4/22) at 4PM ET, we will have @Zhuoqi_Zheng present "MotifBench: A standardized protein design benchmark for motif-scaffolding problems" Paper: arxiv.org/abs/2502.12479 Sign up on our website for zoom links!
Interested in functional protein design or motif-scaffolding? We propose a standardized protein design benchmark, MotifBench aimed at tackling key challenges in the field. Preprint: arxiv.org/abs/2502.12479 Code: github.com/blt2114/MotifB… (1/N)
Have a look at our shiny new benchmark for motif-scaffolding in computational protein design! New (and harder) tasks, including a reproducible evaluation pipeline
🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods for motif scaffolding. Why does this matter? Reproducibility & consistent evaluation have been lacking—until now. Paper: arxiv.org/abs/2502.12479 | Repo: github.com/blt2114/MotifB… A thread ⬇️
We made a new, reproducible, fair, (and much harder) motif scaffolding benchmark! With Zhuoqi Zheng, Bo Zhang, @DidiKieran @json_yim @_JosephWatson Hai-Feng Chen, @brianltrippe
🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods for motif scaffolding. Why does this matter? Reproducibility & consistent evaluation have been lacking—until now. Paper: arxiv.org/abs/2502.12479 | Repo: github.com/blt2114/MotifB… A thread ⬇️
I'm recruiting PhD students for Fall 2025! CS PhD Deadline: Dec. 15th. I work on safe/reliable ML and causal inference, motivated by healthcare applications. Beyond myself, Johns Hopkins has a rich community of folks doing similar work! Come join us!
I am pleased to share that I have accepted a position @Stanford to start as an assistant professor in the department of statistics, with an affiliation in @StanfordData, this fall!
Conditioning diffusion-based generative models for motif scaffolding? Come check out our talk at 11.05 in Room 242 at @AI4D3, or visit our poster in the break. @DidiKieran Francisco Vargas @vdutor @MathieuEmile @julia_tweeting_
Come check out our poster today at 4pm! We find that with a sequential Monte Carlo technique known as twisting we can use conditional sampling heuristics, like reconstruction guidance, to get exact inferences with additional compute.
Twisted Diffusion Sampling - Practical and Asymptotically Exact Conditional Sampling for Diffusion Models Theoretically grounded conditional sampling for diffusion models with applications to inpainting, Bayesian inverse problems, protein design, ... arxiv.org/abs/2306.17775
Where better than Hawaii to talk about oceans?🌊 Excited to present our work on ocean current modeling using Gaussian processes at @ICML - join me at poster #214, Thursday, 10:30am🦭 Also, interested in Bayesian statistics, diffusion models, optimal transport? I’d love to chat!
I'm at ICML next week presenting FrameDiff in main conference and our regularized protein optimization method in the workshops arxiv.org/abs/2307.00494. Reach out if you want to meet-up and chat!
Researchers from @MIT_CSAIL developed “FrameDiff,” a computational tool that uses generative AI to craft new protein structures, aiming to accelerate drug development and improve gene therapy. news.mit.edu/2023/generativ…
Just a reminder that RFdiffusion is free and publicly available, and thanks to @sokrypton, accessible through Google Colab! He's done an incredible job making it user friendly - no need to shell out the big $$$ colab.research.google.com/github/sokrypt…