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Deep Learning at NVIDIA

The modern superpower of deep learning and where it has the largest impact, past, present and future, filtered through the lens of Michelle Gill's work at NVIDIA.

Apr 2018

About Michelle Gill


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Guest
Michelle Gill

Michelle's career in data science has spanned from basic research to management consulting. She currently works in NVIDIA's Professional Services group where she assists clients across all sectors who want to get started with deep learning. Prior to joining NVIDIA, Michelle was a Senior Data Scientist at Metis, where she taught quarterly bootcamps and conducted corporate training focused on data science, machine learning, big data, and related technologies. As a scientist at the National Cancer Institute, she developed parallelized software utilizing machine learning and compressed sensing algorithms that increased experimental throughput up to 10X. As a postdoctoral fellow at Columbia University Medical School, Michelle utilized nuclear magnetic resonance (NMR) spectroscopy to study the biological activity of cancer-associated enzymes with atomic resolution. Michelle was also a consultant for The Boston Consulting Group, where she advised clients in industries ranging from the pharmaceutical to financial services on strategic growth and organizational streamlining.

She has a Ph.D. in Molecular Biophysics & Biochemistry from Yale University and a B.S. in Biochemistry from the University of Kansas. Outside of work, Michelle enjoys cooking, spending time with her spouse and two cats, watching college basketball (Go Jayhawks!), and tweeting (@modernscientist).

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