DiDi Lecture: AI for the Marketplace with Applications to Ride-Sharing
Featuring Hontgu Zhu, who is leading the Statistical Cognition team to develop AI solutions for the world’s largest transportation platform
In this talk, we will introduce a general analytical framework for large scale data obtained from two-sided markets, especially ride-sharing platforms like DiDi. This framework integrates classical methods including Experiment Design, Causal Inference and Reinforcement Learning, with modern machine learning methods, such as Graph Convolutional Models, Deep Learning, Transfer Learning and Generative Adversarial Network. We aim to develop fast and efficient approaches to address five major challenges for ride-sharing platform, ranging from demand-supply forecasting, demand-supply diagnosis, MDP-based policy optimization, A-B testing, to business operation simulation. Each challenge requires substantial methodological developments and inspires many researchers from both industry and academia to participate in this endeavor. Based on our preliminary results for the policy optimization challenge, we receive the Daniel Wagner Prize for Excellent in Operations Research Practice in 2019. All the research accomplishments presented in this talk are joint work by a group of researchers at Didi Chuxing and our collaborators.
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Didi Chuxing (“DiDi”) is the world’s leading mobile transportation platform. The company offers a full range of app-based transportation services for 550 million users across Asia, Latin America and Australia, including Taxi, Express, Premier, Luxe, Bus, Designated Driving, Enterprise Solutions, Bike Sharing, E-bike Sharing, Automobile Solutions and food delivery. Tens of millions of drivers who find flexible work opportunities on the DiDi platform provide 10 billion passenger trips a year.
Dr. Hongtu Zhu joined DiDi in 2018 as a Chief Scientist of Statistics from his position of Endowed Bao-Shan Jing Professorship in Diagnostic Imaging and a tenured professor of biostatistics at MD Anderson Cancer Center. He is also a tenured professor of biostatistics at University of North Carolina at Chapel Hill. In DiDi, he is leading the Statistical Cognition team with AI scientists and engineers to develop innovative solutions for the world’s largest transportation platform.
Featuring Hontgu Zhu, who is leading the Statistical Cognition team to develop AI solutions for the world’s largest transportation platform
In this talk, we will introduce a general analytical framework for large scale data obtained from two-sided markets, especially ride-sharing platforms like DiDi. This framework integrates classical methods including Experiment Design, Causal Inference and Reinforcement Learning, with modern machine learning methods, such as Graph Convolutional Models, Deep Learning, Transfer Learning and Generative Adversarial Network. We aim to develop fast and efficient approaches to address five major challenges for ride-sharing platform, ranging from demand-supply forecasting, demand-supply diagnosis, MDP-based policy optimization, A-B testing, to business operation simulation. Each challenge requires substantial methodological developments and inspires many researchers from both industry and academia to participate in this endeavor. Based on our preliminary results for the policy optimization challenge, we receive the Daniel Wagner Prize for Excellent in Operations Research Practice in 2019. All the research accomplishments presented in this talk are joint work by a group of researchers at Didi Chuxing and our collaborators.
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Didi Chuxing (“DiDi”) is the world’s leading mobile transportation platform. The company offers a full range of app-based transportation services for 550 million users across Asia, Latin America and Australia, including Taxi, Express, Premier, Luxe, Bus, Designated Driving, Enterprise Solutions, Bike Sharing, E-bike Sharing, Automobile Solutions and food delivery. Tens of millions of drivers who find flexible work opportunities on the DiDi platform provide 10 billion passenger trips a year.
Dr. Hongtu Zhu joined DiDi in 2018 as a Chief Scientist of Statistics from his position of Endowed Bao-Shan Jing Professorship in Diagnostic Imaging and a tenured professor of biostatistics at MD Anderson Cancer Center. He is also a tenured professor of biostatistics at University of North Carolina at Chapel Hill. In DiDi, he is leading the Statistical Cognition team with AI scientists and engineers to develop innovative solutions for the world’s largest transportation platform.