Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Wei Lin

Wei Lin
Chief Data Scientist and Senior Manager, Dell EMC

Wei Lin is senior manager at Dell EMC and chief data scientist for the company’s Big Data Practice, where he is responsible for planning the company’s data science strategy and leading data science services delivery as well as leading data scientist project delivery and the hiring, training, and certification of new data scientists. He hosts Dell EMC’s data science mentorship program, which shares data scientists’ engagement findings, industry experience, techniques, and trends. His successes include developing Dell EMC’s data science field consulting methodology, Descriptive, Exploration, Predictive and Prescriptive (DEPP), which provides a practical analytics roadmap and approaches for an organization’s business initiatives and data and analytic requirements. Wei has over 20 years of experience in predictive analytics, including analytical modeling, architecture design, data warehousing, reporting, and marketing. Previously, he was the principal consultant at IBM, PwC, and Cooper & Lybrand. He has authored over 100 papers, and his work has been published or reported on in professional journals as well as Businessweek and Forbes. Wei holds both an MA and a PhD in electrical engineering, specializing in artificial intelligence, from the State University of New York at Binghamton and a BS in electrical engineering from National Taipei Institute of Technology, Taiwan.


11:00am11:40am Wednesday, March 7, 2018
Strata Business Summit
Location: 210 D/H
Mauro Damo (Dell EMC), Wei Lin (Dell EMC)
Average rating: ***..
(3.50, 2 ratings)
Image recognition classification of diseases will minimize the possibility of medical mistakes, improve patient treatment, and speed up patient diagnosis. Mauro Damo and Wei Lin offer an overview of an approach to identify bladder cancer in patients using nonsupervised and supervised machine learning techniques on more than 5,000 magnetic resonance images from the Cancer Imaging Archive. Read more.