Author

Orion Li

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Genomics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Approach:deep learning· 2 Research Focus:gene regulatory network inference· 2 Research Focus:perturbation response prediction· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Approach:transformer / foundation model· 2 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Ashwin GopinathiD· 3 shared Timothy KassisiD· 2 shared Vinayak AgarwaliD· 2 shared Christopher A. PettyiD· 1 shared David A. SinclairiD· 1 shared David Yu ZhangiD· 1 shared Ekansh Mittal· 1 shared Elon LitmaniD· 1 shared

Activity by Year

2023-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersGenomics

Ashwin GopinathORCID

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Author profile →

3 papers

Recent·Most cited

GeneJEPA: A Predictive World Model of the Transcriptome

Elon Litman, Tyler D. Myers, Vinayak Agarwal, Ekansh Mittal, Orion Li, Ashwin Gopinath, Timothy Kassis

This paper introduces a self-supervised foundation model for single-cell transcriptomes that predicts gene sets from context and outperforms baselines in downstream tasks.

bioRxiv · Oct 14, 2025 · PreprintGenomics

Guided multi-agent AI invents highly accurate, uncertainty-aware transcriptomic aging clocks

Vinayak Agarwal, Orion Li, Christopher A. Petty, Timothy Kassis, Paul Wilhelm Karl Rothemund, David A. Sinclair, Ashwin Gopinath

The paper introduces K-Dense, an AI system that creates accurate transcriptomic aging clocks with uncertainty estimates, showing continuous evolution of aging signatures.

bioRxiv · Sep 8, 2025 · PreprintSystems Biology

BIOFORMERS: A SCALABLE FRAMEWORK FOR EXPLORING BIOSTATES USING TRANSFORMERS

Siham Amara-Belgadi, Orion Li, David Yu Zhang, Ashwin Gopinath

The paper introduces BIOFORMERS, a transformer-based framework for analyzing biological systems, demonstrating its ability to capture biological insights from single-cell transcriptomics data.

bioRxiv · Nov 29, 2023 · PreprintBioinformatics