Practicing the Art of Data Science
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Jian Pei
School of Computing Science
Simon Fraser University
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Abstract
Data science embraces interdisciplinary methodologies and tools, such as those in statistics, artificial intelligence/machine learning, data management, algorithms, and computation.
The art of practicing data science to empower innovative applications, however, remains an art due to many factors beyond technology, such as sophistication of application scenarios, business demands, and the central role of human being in the loop.
In this talk, I will share with the audience some experience and lessons I learned from my practice of data science research and development.
First, I will illustrate the core value of building domain-oriented, end-to-end data science solutions that can help people gain new interpretable domain knowledge.
Second, using network embedding as an example, I will demonstrate that the nature of data science practice is to connect challenges in vertical applications with general scientific principles and tools.
If time permits, I will also discuss some future directions, particularly about data strategies for enterprises and organizations on data as assets, privacy, fairness, accountability, and transparency.
Biography
Jian Pei's professional interest is to facilitate efficient, fair, and sustainable usage of data for social, commercial and ecological good.
Through inventing, implementing and deploying a series of data mining principles and methods, he produced remarkable values to academia and industry.
His algorithms have been adopted by industry, open source toolkits and textbooks.
His publications have been cited over 97,500 times.
He is also an active and productive volunteer for professional community services, such as chairing ACM SIGKDD and the steering committee of WSDM, running many premier academic conferences in his areas, and being editor-in-chief or associate editor for the flagship journals in his fields.
He is recognized as a fellow of the Royal Society of Canada (i.e., the national academy of Canada), a fellow of the Canadian Academy of Canada, a fellow of ACM, and a fellow of IEEE.
He received a series of prestigious awards, such as the ACM SIGKDD Innovation Award, the ACM SIGKDD Service Award, and the IEEE ICDM Research Award.
Currently he is a full professor at Simon Fraser University.
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