SynBioBeta Speaker
Xuecheng Jiao
Asymchem
Vice GM
Xuecheng Jiao, PhD has journeyed through academia and into a pivotal role at Asymchem Life Science Technology Co. Ltd showcasing a steadfast dedication to biochemical engineering, marked by progressive leadership positions, and a commitment to innovation in enzyme engineering. He joined Asymchem as a Senior Scientist in 2016. He holds degrees from East China University of Science and Technology (State Key Lab of Bioreactor Engineering) and Hebei University of Technology.
SynBioBeta 2026 Tickets are Live
Confirmed Speakers
Sessions Featuring
Xuecheng
This Year
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Tools & Tech
From Experience to Intelligence - Building Practical Vertical AI for Industrial Enzyme Engineering
While foundation models have demonstrated broad potential in protein engineering, their generic nature often falls short at the industrial "last mile"—where narrow tolerance windows, non-natural substrates, and harsh process conditions prevail. To adapt to these challenges, we integrate decades of enzyme engineering experience with proprietary high-fidelity domain-specific datasets, powered by our CFPS‑driven high‑throughput screening platform (>100× throughput over traditional directed evolution, enabling precise domain-specific annotation). This approach enables us to build practical vertical AI models that have been validated in real‑world production settings, demonstrating improved accuracy over general‑purpose models and paving the way toward an integrated Enzyme Co‑Pilot for reliable, data‑driven biocatalysis.
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Tools & Tech
From Experience to Intelligence - Building Practical Vertical AI for Industrial Enzyme Engineering
While foundation models have demonstrated broad potential in protein engineering, their generic nature often falls short at the industrial "last mile"—where narrow tolerance windows, non-natural substrates, and harsh process conditions prevail. To adapt to these challenges, we integrate decades of enzyme engineering experience with proprietary high-fidelity domain-specific datasets, powered by our CFPS‑driven high‑throughput screening platform (>100× throughput over traditional directed evolution, enabling precise domain-specific annotation). This approach enables us to build practical vertical AI models that have been validated in real‑world production settings, demonstrating improved accuracy over general‑purpose models and paving the way toward an integrated Enzyme Co‑Pilot for reliable, data‑driven biocatalysis.
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Session lineup still growing
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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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