
SynBioBeta Speaker
Xiaojing Gao
Stanford University
Assistant Professor
Dr. Xiaojing Gao is an Assistant Professor of Chemical Engineering from Stanford University. He received a B.S. in Biology from Peking University and a Ph.D. in Biology from Stanford University. He received his postdoctoral training from Biology and Biological Engineering at Caltech. His lab works on mammalian synthetic biology. Some of his recent recognitions include BioInnovation Institute & Science Prize for Innovation and NIH’s New Innovator Award (DP2). He co-founded Radar Tx.
Sessions Featuring
Xiaojing
This Year
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Tools & Tech
Genome as a Canvas: Composing Life at Scale
Reading, writing, and editing DNA were just the prelude. The next frontier is composition, designing complex genetic systems and large DNA architectures from first principles using AI-driven models and scalable synthesis technologies. As datasets grow and design tools mature, biology is shifting from incremental editing toward intentional genome-scale engineering. This new paradigm treats DNA not simply as a sequence to modify but as a programmable substrate where genes, regulatory elements, and entire genomic regions can be composed, tested, and iterated like engineered systems. Advances in generative design, large-scale DNA assembly, and precision integration technologies are enabling researchers to construct increasingly complex genetic structures with higher predictability and functional intent. From next-generation recombinases and genome restructuring platforms to AI-guided design workflows that bridge computation and physical DNA construction, the emerging toolkit is redefining how biological complexity is created. The session explores how compositional genome engineering could unlock new capabilities across therapeutics, industrial biology, and synthetic life design.
Featuring

Xiaojing Gao
Stanford University
Assistant Professor

Kaihang Wang
Caltech
Assistant Professor
Building synthetic genomes to create new life forms.

Samuel King
Stanford University
BioEng Doctoral Candidate
Genome language models designing new bacteriophages

Andrew Hessel
Human Genome Project
Chairman
Genome-writing pioneer, Singularity University visionary
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Tools & Tech
Genome as a Canvas: Composing Life at Scale
Reading, writing, and editing DNA were just the prelude. The next frontier is composition, designing complex genetic systems and large DNA architectures from first principles using AI-driven models and scalable synthesis technologies. As datasets grow and design tools mature, biology is shifting from incremental editing toward intentional genome-scale engineering. This new paradigm treats DNA not simply as a sequence to modify but as a programmable substrate where genes, regulatory elements, and entire genomic regions can be composed, tested, and iterated like engineered systems. Advances in generative design, large-scale DNA assembly, and precision integration technologies are enabling researchers to construct increasingly complex genetic structures with higher predictability and functional intent. From next-generation recombinases and genome restructuring platforms to AI-guided design workflows that bridge computation and physical DNA construction, the emerging toolkit is redefining how biological complexity is created. The session explores how compositional genome engineering could unlock new capabilities across therapeutics, industrial biology, and synthetic life design.
Featuring

Xiaojing Gao
Stanford University
Assistant Professor

Kaihang Wang
Caltech
Assistant Professor
Building synthetic genomes to create new life forms.

Samuel King
Stanford University
BioEng Doctoral Candidate
Genome language models designing new bacteriophages

Andrew Hessel
Human Genome Project
Chairman
Genome-writing pioneer, Singularity University visionary
Session lineup still growing
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?
Featuring
Speaker Coming Soon





































