Sep 9–12, 2019
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Jike Chong

Jike Chong
Chief Data Scientist, LinkedIn | Tsinghua University

Dr. Jike Chong is an accomplished executive and professor with experience across industry and academia.

Jike currently heads Data Science, Hiring Marketplace at LinkedIn. He was most recently the chief data scientist at Acorns, the leading micro-investment 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. Previously, Jike 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 Simply Hired, a leading job search engine in Silicon Valley; advised the Obama administration on using AI to reducing 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 also 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

1:45pm2:25pm Thursday, September 12, 2019
Location: LL21 A/B
Jike Chong (LinkedIn | Tsinghua University), Yue Cathy Chang (TutumGene)
Average rating: ****.
(4.00, 2 ratings)
Domain insights are crucial for successful AI/ML initiatives. This talk discusses three areas of concerns: clarification of business context, awareness of nuances of data sources, and navigating organizational structure. Read more.
  • Intel AI
  • O'Reilly
  • Amazon Web Services
  • IBM Watson
  • Dataiku
  • Dell Technologies
  • Intuit
  • Gamalon
  • H2O.ai
  • Hewlett Packard Enterprise
  • MapR Technologies
  • Sisu Data
  • Intuit

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