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My TEDx talk on the importance of building interpretable, open box machine learning models and using domain-informed detective work to accelerate discovery in genomics, biology, and medicine: youtube.com/watch?v=uC3Sfn…
Barbara Engelhardt
@BeEngelhardt
Machine learning, statistical genomics, ML4 health, senior investigator
at Gladstone Institutes, professor at Stanford, single mom to four kids. she/her
at Gladstone Institutes, professor at Stanford, single mom to four kids. she/her
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Stop by our #NeurIPS2025 poster today! We would love to tell you about our work!! Thanks to @CIFAR_News for the funding that made this work happen.
Excited to present our work on multi-objective scientific discovery at #NeurIPS2025! 🎉
We present Preference-Guided Diffusion, a novel method to sample diverse designs from a diffusion model that corresponds to the Pareto Front of black-box objectives.
Most (if not all) problems in scientific discovery, from drug design to material design, are multi-objective. Balancing factors like toxicity and activity or stability and synthesizability requires finding the optimal Pareto Front of trade-offs. Preference-Guided diffusion uses preference pairs from just an offline dataset to sample optimal designs from a diffusion model.
W/ amazing co-authors @syrineblk, @StefanoErmon, @stefanAbauer, and @BeEngelhardt.
Find out more:
🗓️ Poster #915 | Wednesday | 4:30 PM PST
Pdf: openreview.net/pdf?id=moiVS9A…
Project: github.com/yannadani/pgd_…View quoted post on X
Our neighborhood nonnegative matrix factorization preprint just dropped! Try it out for matrix decomposition and hard clustering for your spatial transcriptomic data! Blue-hued tweetorial: bsky.app/profile/thebee…
We’re thrilled to announce the workshop “Experimental Design: AI for Science” happening at Stanford University on 3rd and 4th April 2025. The workshop focuses on theory and methodology of AI-based experimental design and its application to science. edai4science.github.io
My NIH Study Section (MABS) was cancelled a little more than 24 hours before the start. With 35 members, & 45 h of reviews/member, that wasted 1575 hours of scientists' unpaid time. @NIH, protect scientists right now & cancel all study sections until you get clarity. @NIHDirector