Eric Sun

I’m very excited to be joining MIT Biological Engineering @MITdeptofBE as an Assistant Professor and the Ragon Institute @ragoninstitute as a member in January 2026! I will be recruiting students and postdocs (see more info below).

#CellVoyager is published in @NatureMethods! 🔬 Autonomous comp bio agent 🧬 Analyzes bio data to make new discoveries 💻 Runs in Jupyter notebooks → interactive & reproducible 📊 Generated expert-validated insights on COVID-19, cell–cell communication and aging

Aging may feel gradual… but what if it’s not? In our paper out today, we tracked fish continuously from puberty until death. This gave us a unique view of how aging unfolds across the adult lifespan. 🧵

We have posted a Research Assistant (LSRP1) position to work on aging and 'rejuvenation' using mouse models!! 🐭 careersearch.stanford.edu/jobs/life-scie… Apply and join our awesome lab!! (please share) 😎

How to get AI to make discoveries on open scientific problems? Most methods just improve the prompt with more attempts. But the AI itself doesn't improve. With test-time training, AI can continue to learn on the problem it’s trying to solve: test-time-training.github.io/discover.pdf

We recently organized #Agents4Science, the 1st conference where LLMs are both authors and reviewers🤖 It was an open experiment to assess how well AI can lead research and review papers. Today we report what we learned in @NatureBiotech Highlights in 🧵

Great collaborative work with @abuen_dia @BrunetLab @james_y_zou

Our preprint can be accessed here: biorxiv.org/content/10.648…. The API and analysis code for SpatialProp can be found at: github.com/abuendia/spati….

Can we predict the spatial effects of single-cell perturbations? Excited to share our preprint introducing SpatialProp, which computationally propagates single-cell transcriptomic perturbations across tissues, along with key frameworks for evaluating spatial perturbation models.

The SpatialProp pipeline is simple, involving a GNN for predicting gene expression from the spatial microenvironment and a series of post-processing steps (SparseRenorm) to calibrate for prediction errors in the perturbation context.

Can we predict the spatial effects of single-cell perturbations? Excited to share our preprint introducing SpatialProp, which computationally propagates single-cell transcriptomic perturbations across tissues, along with key frameworks for evaluating spatial perturbation models. pic.twitter.com/qeQVZ6pko7

#Agents4Science received over 300 submissions and accepted 48 papers. Check them out here: #tab-accept" target="_blank" rel="nofollow noopener">openreview.net/group?id=Agent… Many of these AI agent-written papers are quite interesting! The online conference will be on Oct 22; you can register for free at stanford.zoom.us/webinar/regist…

@BrunetLab Thanks Anne!!

Congratulations @EricDSun!! Well deserved!!

@BoXia7 @MITdeptofBE @ragoninstitute Thanks Bo!

@EricDSun @MITdeptofBE @ragoninstitute Congrats Eric! And welcome back to Cambridge!

I’m very excited to be joining MIT Biological Engineering @MITdeptofBE as an Assistant Professor and the Ragon Institute @ragoninstitute as a member in January 2026! I will be recruiting students and postdocs (see more info below).

@MichaelShadpour @MITdeptofBE @ragoninstitute Thanks Michael!

@EricDSun @MITdeptofBE @ragoninstitute Congrats Eric!