Applied Data Science Invited Speakers

The Applied Data Science Invited Talks will provide a venue for leading experts in the world of applied data mining and knowledge discovery. These invited talks will feature highly influential speakers who have directly contributed to successful data mining applications in their respective fields. The talks and discussions will focus on innovative and leading-edge, large-scale industry or government applications of data mining in areas such as finance, health-care, bio-informatics, public policy, infrastructure, telecommunications, social media and computational advertising.


Keynote: Jieping Ye

Jieping Ye

Didi Chuxing & University of Michigan, Ann Arbor

Transportation: A Data Driven Approach

Didi Chuxing is the world’s leading mobile transportation platform that offers a full range of app-based transportation options for 550 million users. Every day, DiDi’s platform receives over 100TB new data, processes more than 40 billion routing requests, and acquires over 15 billion location points. Machine learning has been used in numerous components of DiDi’s platform to improve travel safety, experience and efficiency. This talk systematically presents the challenges and opportunities in the core area of modern transportation systems, and highlights some of our recent works on order dispatching and fleet management via deep reinforcement learning.


Jieping Ye is Head of DiDi AI Labs, a VP of Didi Chuxing and a DiDi Fellow. He is also a Professor at the University of Michigan, Ann Arbor. His research interests include data mining and machine learning with applications in transportation and biomedicine. He has served as a Senior Program Committee/Area Chair/Program Committee Vice Chair of many conferences including NIPS, ICML, KDD, IJCAI, AAAI, ICDM, and SDM. He serves as an Associate Editor of Data Mining and Knowledge Discovery and IEEE Transactions on Knowledge and Data Engineering. He won the NSF CAREER Award in 2010. His papers have been selected for the outstanding student paper at ICML in 2004, the KDD best research paper runner up in 2013, and the KDD best student paper award in 2014.

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