SynBioBetaLive! – Lab data to machine learning in 30 seconds with Riffyn

SynBioBetaLive

Want to go from lab data to machine learning in 30 seconds? Join us for the launch of SynBioBetaLive!, a web event we’re premiering on Wednesday, May 23 at 8 am Pacific. Our first event is with Timothy Gardner of Riffyn, who will show us how biological researchers can spend less time organizing their experimental data and more time asking important questions about it.

What will you learn?

Riffyn will demonstrate how pioneering biotech companies are transforming traditional experimental designs and data into AI-ready datasets in seconds.

Today’s research and development breakthroughs lie deep in the midst of complex, multivariate data sets. Experimental anomalies and fundamental discoveries often go unnoticed because they are buried in uninterpretable spreadsheets, inaccessible databases, or excessive experimental noise. Riffyn SDE software structures experimental designs and links it to measurement data for machine learning within seconds after it is collected in the lab.

May 23, 2018 8:00 AM Pacific Time (US and Canada)

Speaker

Tim Gardner

Tim Gardner is the Founder and the CEO of Riffyn. Previously he was Vice President of Research & Development at Amyris, where he led the engineering of yeast strain and processes technology for large-scale bio-manufacturing of renewable chemicals. He was also Assistant Professor of Biomedical Engineering at Boston University, the Founder of Cellicon Biotechnologies, and a Programmer at ALK Associates. Tim has been recognized for his pioneering work in synthetic biology by Scientific American, the New Scientist, Nature, Technology Review, and the New York Times. He served as an advisor to the European Union Scientific Committees and the Boston University Engineering Alumni Advisory Board. He holds BS in Mechanical Engineering from Princeton University and a PhD in Biomedical Engineering from Boston University. Tim enjoys hockey, running, mountain biking, and being beaten by his sons in almost everything.

 

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