Samuel Stanton

Drug discovery is a profoundly exciting application of ML, involving discrete, high-dimensional, multi-objective optimization problems. The @andrewgwils lab and @BigHatBio are proud to introduce LaMBO, a new method for biological sequence design. arxiv.org/abs/2203.12742 1/9

come by to chat about training LLMs to be black-box token sequence optimizers

& “WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales” by @DrewPrinster, @xinghan0, @anqi_liu33, & @suchisaria proposes a weighted generalization of conformal test martingales: arxiv.org/abs/2505.04608 (5/5)

There is so much deep engineering work that is far upstream of drug discovery and in vivo systems. If you have a strong technical background you can have a very high impact by contributing to things like sequencing instruments, imaging, lab robotics and so on.

If you, like me, felt frustrated after reviewing 6 papers for @NeurIPSConf and thought "there must be a better way" then this post is for you. Link 👇

i was asked by a few (inc. @YuanqingWang ) what i meant by this earlier tweet, and since i'm pretty busy, i decided to write a blog post to answer the question 🤦

I recently had the pleasure of speaking with my graduate alma mater @NYUDataScience about my personal experience building a lab-in-the-loop system for therapeutic antibody lead optimization with my amazing colleagues @genentech. Active learning is a leap of faith!

The two most common questions I get via cold email are 1) what should I work on, and 2) how do I get a job doing research, engineering, etc.? I wrote a new post summarizing my advice for people trying to enter Biology+ML, from undergrads to early career. 👇 (link below)

AI monitoring is key to responsible deployment. Our #ICML2025 paper develops approaches for 3 main goals: 1) *Adapting* to mild data shifts 2) *Quickly Detecting* harmful shifts 3) *Diagnosing* cause of degradation 🧵w/ @xinghan0 @anqi_liu33 @suchisaria arxiv.org/abs/2505.04608

i think you should be less concerned about how other people are (mis)using AI and more concerned about whether you are using AI to be more virtuous, productive, and empathetic.

AI is revolutionizing drug discovery right now at enterprise scale. It's not a hypothetical anymore 🚀

We're hiring! Come work with me, @timbitsz, and the fantastic teams @genentech Comp Bio / Disco Onc & @PrescientDesign as a postdoc. Link to apply below 👇

We are hiring a PhD research intern at FAIR w/ @marksibrahim @kamalikac to start this summer or Fall! Potential topics: trustworthy and reliable LLMs, multi-modal LLMs and agents, post-training, reasoning, with a focus on open science/sharing our findings in the paper at the end…

Sequencing should be a human right for those with possible rare disease. Clinical care should be -> start with maximal data and work backwards vs. (the current) start with minimal data -> then slowly add more, letting the disease progress

long on lobster

a lot of people think binder design is the bottleneck for drug discovery, but developability is arguably where wetlabs struggle more due to the cost of the assays. swing by Amy's poster to learn more!

There are no interpretability workshops @iclr_conf, so stop by @asalam_91 's poster (#504) during Poster Session 5 and we'll show you how to build interpretable Language Models by design.

I will be @iclr_conf in Singapore and I'm looking for a senior ML scientist to join my team @PrescientDesign @genentech! 🧬 If you have experience & interest in multi-modal biological foundation models and agents for science, reach out and let's meet up! Link to apply 👇