Mar 15–18, 2020
Jike Chong

Jike Chong
Director, Data Science, Hiring Marketplace, LinkedIn

Jike Chong is the director of data science, hiring marketplace at LinkedIn. He’s an accomplished executive and professor with experience across industry and academia. Previously, he was the chief data scientist at Acorns, the leading microinvestment app in US with over four million verified investors, which uses behavioral economics to help the up-and-coming save and invest for a better financial future; was the chief data scientist at Yirendai, an online P2P lending platform with more than $7B loans originated and the first of its kind from China to go public on NYSE; established and headed the data science division at SimplyHired, a leading job search engine in Silicon Valley; advised the Obama administration on using AI to reduce unemployment; and led quantitative risk analytics at Silver Lake Kraftwerk, where he was responsible for applying big data techniques to risk analysis of venture investment. Jike is also an adjunct professor and PhD advisor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, where he established the CUDA Research Center and CUDATeaching Center, which focus on the application of GPUs for machine learning. Recently, he developed and taught a new graduate level course on machine learning for Internet finance at Tsinghua University in Beijing, China, where he is serving as an adjunct professor. Jike holds MS and BS degrees in electrical and computer engineering from Carnegie Mellon University and a PhD from the University of California, Berkeley. He holds 11 patents (six granted, five pending).

Sessions

9:00am12:30pm Monday, March 16, 2020
Location: 210A
Jike Chong (LinkedIn), Yue Cathy Chang (TutumGene)
More than 85% of data science projects fail. This high failure rate is a main reason why data science is still a "science." As data science practitioners, reducing this failure rate is a priority. Jike Chong and Yue Cathy Chang explain the three key steps of applying data science technology to business problems and three concerns for applying domain insights in AI and ML initiatives. Read more.
11:50am12:30pm Tuesday, March 17, 2020
Location: LL21 D
Jike Chong (LinkedIn), Yue Cathy Chang (TutumGene)
More than 85% of data science projects fail. This high failure rate is a main reason why data science is still a science. Jike Chong and Yue "Cathy" Chang outline how you can reduce this failure rate and improve teams' confidence in executing successful data science projects by applying data science technology to business problems: scenario mapping, pattern discovery, and success evaluation. Read more.

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