SynBioBeta Speaker
Le Cong
Stanford University
Associate Professor
Dr. Cong's group is developing technology for large-scale genome editing and gene insertion for gene&cell therapy, integrating advance from metagenomics, computational biology, and high-throughput engineering. In parallel, the group also leverages these gene-editing tools for single-cell functional screening, to probe the molecular mechanisms of innate immunity in cancer and neuro-immune diseases. To accelerate these efforts, Dr. Cong's team integrates AI and machine learning into genome technologies, to design and evolve gene-editing proteins and RNAs in silico, significantly enhancing the efficiency and capabilities of these therapeutic molecules.
Dr. Cong's work has led to one of the first CRISPR/Cas9 gene-editing tools for in vivo gene therapy. More recently, his group invented tools for cleavage-free large gene insertion with novel recombination proteins (SSAP editor), and developed machine-learning optimized single-cell methods (DAISY) for studying cancer and immune diseases. Dr. Cong is a recipient of the NHGRI Genomic Innovator Award, Baxter Foundation Faculty Scholar, Genetic Engineering and Biotechnology News (GEN) Top 10 Under 40, Clinical OMICs Pioneers Under 40, and Clarivate Web of Science Highly Cited Researcher.
SynBioBeta 2026 Tickets are Live
Confirmed Speakers
Sessions Featuring
Le
This Year
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Tools & Tech
AI Co-Scientists: From Pipettes to Protocols
Biology is entering an era where AI agents don’t just analyze data — they co-design, plan, and execute experiments. Multi-agent systems like CRISPR-GPT demonstrate how AI can act as a true lab co-pilot: decomposing complex genome editing projects into stepwise workflows, selecting tools, troubleshooting, and even drafting protocols that allow junior researchers to perform sophisticated edits on their first attempt . Beyond CRISPR, new systems like BioMARS integrate reasoning agents with robotics, while biotech companies are testing “AI lab assistants” that monitor and adjust experiments in real time. This session explores how multi-agent copilots are making biology more reproducible, democratizing complex workflows, and pushing the boundaries of lab autonomy. The central question: when AI can plan, troubleshoot, and validate experiments end-to-end, how should scientists and institutions govern this new power?
Purchase Pass
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Tools & Tech
AI Co-Scientists: From Pipettes to Protocols
Biology is entering an era where AI agents don’t just analyze data — they co-design, plan, and execute experiments. Multi-agent systems like CRISPR-GPT demonstrate how AI can act as a true lab co-pilot: decomposing complex genome editing projects into stepwise workflows, selecting tools, troubleshooting, and even drafting protocols that allow junior researchers to perform sophisticated edits on their first attempt . Beyond CRISPR, new systems like BioMARS integrate reasoning agents with robotics, while biotech companies are testing “AI lab assistants” that monitor and adjust experiments in real time. This session explores how multi-agent copilots are making biology more reproducible, democratizing complex workflows, and pushing the boundaries of lab autonomy. The central question: when AI can plan, troubleshoot, and validate experiments end-to-end, how should scientists and institutions govern this new power?
Purchase Pass
Session lineup still growing
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Featuring
Speaker Coming Soon
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Human Health
From Cells to Patients: Solving the Scale Mismatch in Virtual Biology
Drug discovery often measures biology at the cell level while interventions work at the tissue, organ, or whole-patient scale. This mismatch can make accurate cell-level predictions irrelevant in the clinic. This session dives into strategies to bridge that gap: multiscale modeling that nests single-cell dynamics within organ-level simulations, spatial transcriptomics that preserve context, and surrogate models that translate cell-level outputs into clinical biomarkers. Speakers will ask: how do we ensure virtual biology reflects not just what cells do in isolation, but how biology behaves in the real complexity of patients?
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Featuring
Speaker Coming Soon
