Congratulations to Owen and Zaixi for having their papers accepted as spotlights at NeurIPS! These papers, which are among the top 3% of all submissions, focus on explaining sequence models through self-supervised learning and the full-atom design of protein pockets.

Excited to share our perspectives on current and future directions in network biology.

New paper on the role of artificial intelligence in scientific discovery is published in Nature.

PINNACLE is a contextual AI model for protein understanding that dynamically adjusts its outputs based on biological contexts in which it operates. Project website.

Excited to join Kempner’s inaugural cohort of associate faculty to advance Kempner’s mission of studying the intersection of natural and artificial intelligence.

An enthusiastic welcome to Shanghua Gao who is joining our group as a postdoctoral research fellow.

Excited to share our new study on language model pretraining and general-purpose methods for biological sequences. Project website.

Congrats to PhD student Michelle on being selected as the 2023 Albert J. Ryan Fellow and also to participate in the Heidelberg Laureate Forum. Congratulations to PhD student Ada for being selected as the Kempner Institute Graduate Fellow!

New paper introducing the first model for closed-set and universal domain adaptation on time series accepted at ICML 2023. Raincoat addresses feature and label shifts and can detect private labels. Project website.

Undergraduate researchers Ziyuan, Nick, Yepeng, Jiali, Julia, and Marissa are moving onto their PhD research in Computer Science, Systems Biology, Neuroscience, and Biological & Medical Sciences at Harvard, MIT, Carnegie Mellon University, and UMass Lowell. We are excited for the bright future they created for themselves.

An enthusiastic welcome to Tianlong Chen, our newly appointed postdoctoral fellow.

New paper in Nature Machine Intelligence introducing the blueprint for multimodal learning with graphs.

New paper with NASA in Nature Machine Intelligence on biomonitoring and precision health in deep space supported by artificial intelligence.

New paper with NASA in Nature Machine Intelligence on biological research and self-driving labs in deep space supported by artificial intelligence.

New study on zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design. Check out our project website and TxGNN Explorer.

Our approach evaluating explainability of geometric deep learning models is published in Scientific Data. Project website.

A warm welcome to postdoctoral fellows Wanxiang Shen and Ruth Johnson. Congratulations to Ruthie for being named a Berkowitz Fellow.

New preprint on domain adaptation for time series under feature and label shifts. Project website.

Our multimodal knowledge graph for precision medicine is published in Scientific Data. Project website.

New paper on machine unlearning for graph neural networks accepted at ICLR 2023. Project website.