2021 IEEE International Conference on Digital Society and Intelligent Systems (IEEE-DSInS 2021)
Prof. Yu Zheng

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Biography:
Dr. Yu Zheng is the Vice President of JD.COM, leading the JD Intelligent Cities Business Unit and JD Intelligent Cities Research. He also serves as the Chief Data Scientist at JD Technology, passionate about using big data and AI technology to tackle urban challenges. Before Joining JD.COM, he was a senior research manager at Microsoft Research, with research interests across big data analytics, spatio-temporal data mining, machine learning and artificial intelligence.

Zheng is also a Chair Professor at Shanghai Jiao Tong University and an Adjunct Professor at Hong Kong University of Science and Technology. He served as the Editor-in-Chief of ACM Transactions on Intelligent Systems and Technology from 2015 to 2021, and a member of Editorial Advisory Board of IEEE Spectrum. He is also an Editorial Board Member of IEEE Transactions on Big Data and the Chair-elected of SIGKDD China Chapter. He has served as chair on over 10 prestigious international conferences, e.g. as the program co-chair of ICDE 2014 (Industrial Track), CIKM 2017 (Industrial Track) and IJCAI 2019 (industrial track) as well as the area chair of AAAI 2019/2022.

Zheng publishes referred papers frequently as a leading author at prestigious conferences and journals, such as KDD, IJCAI, AAAI, VLDB, UbiComp, and IEEE TKDE. Those papers have been cited over 36,000 times (Google Scholar H-Index: 85 by Sept. 2021). He received the SIGSPATIAL 10-Year Impact Award twice, in 2019 and 2020 respectively, and five best paper awards from ICDE’13 and ACM SIGSPATIAL’10, etc. He has been invited to give keynote speeches at international conferences and forums (e.g. AAAI 2019, KDD 2019 Plenary Keynote Panel, IJCAI 2019 Industrial Days, MDM 2021 and SSTD2021) and guest lectures in universities like MIT, CMU, and Cornell. His book, titled “Computing with Spatial Trajectories”, has been used as a text book in universities worldwide and honored as the Top 10 Most Popular Computer Science Book authored by Chinese at Springer. His monograph, entitled "Urban Computing" (MIT Press), is the first text book in this field.

Zheng has received 3 technical transfer awards from Microsoft and 24 granted/filed patents. His technology has been transferred to Microsoft Products like Bing Maps. One of his projects, entitled Urban Air, has been deployed with the Chinese Ministry of Environmental Protection, predicting air quality for over 300 Chinese cities based on big data. He also leads a China pilot project on urban big data platform, which has been deployed in Guiyang City.

Zheng has been featured multiple times by influential journals. In 2013, he was named one of the Top Innovators under 35 by MIT Technology Review (TR35) and featured by Time Magazine for his research on urban computing. In 2014, he was named one of the Top 40 Business Elites under 40 in China by Fortune Magazine, because of the business impact of urban computing he has been advocating since 2008. In 2016, Zheng was honored as an ACM Distinguished Scientist. In 2017, he was recognized as the one of the Top 10 AI Innovators in China. In 2020, he was elevated to an IEEE Fellow for his contributions to spatio-temporal data mining and urban computing.


Speech title: Urban Computing: Building Intelligent Cities Using Big Data and AI


Abstract: Urban computing is a synergy among cloud computing, big data and AI models in the context of cities, tackling urban challenges, such as air pollution, energy consumption and traffic congestion, to create win-win-win solutions that improve urban environment, human life quality and city operation systems. This talk presents the vision of urban computing, demonstrating how AI technology helps to build intelligent cities. A series of AI-driven applications, such as location selection for business, forecasting air and water quality, and reducing energy consumption are also introduced in this talk. More information can be found through the website: http://icity.jd.com/.