Artificial Intelligence, Machine Learning, and Business Analytics


Virtual conference, 10-11 Dec 2020; Deadline 26 Oct


Author: Xueming Luo

2020 Conference on Artificial Intelligence, Machine Learning, and Business Analytics

December 10-11, 2020

 Virtual on Zoom  

Co-organized by Stern School of Business, New York University; Heinz College, Carnegie Mellon University; Fox School of Business, Temple University

Over five billion people worldwide actively engage with AI, bots, machine-to-machine connected solutions, wearables, Internet-of-Things, 5G, AR/VR, Fintech, Mooc, and blockchain. This conference will explore how digital, social, and mobile technologies affect business models, customer behavior, public policy, and social changes at large. Exemplar topics include:

AI automation/ Robotics AI adoption and user behavior/AI chatbot voice-mining for promo and recommendations/ Bot trading and AI advisor in financial markets/AI for ad creatives and publishers/ AI applications in worker training, hiring, and supervising/ ML applications in fintech, pharma, and e-commerce/ Privacy and new technologies/ Data breach and security/ Blockchain applications/ Future of work and unemployment/ Big data IoT, 5G, AR, and VR applications/ Public policy and regulation of AI technologies/ AI algorithm bias, interpretable ML/ Machine learning for causal inference/ ML and deep learning for statistics methods/ Machine learning for empirical IO/ Deep reinforcement learning for microeconomics theory / Healthcare applications of ML/ Multi-armed bandits for online advertising and pricing/ Contextual MAB for personalized dynamic recommendations/ MOOC education online with ML and AI NLP with social media text data for targeting/ ML for images, voice, and video data B2B markets with ML and AI

Confirmed Keynote Speakers: Alessandro Acquisti (CMU), Jonah Berger (Wharton), Anindya Ghose (NYU), John Hauser (MIT), Kartik Hosanagar (Wharton), Nan Jia (USC), Dokyun Lee (CMU), Harikesh Nair (Stanford), Beibei Li (CMU), Sridhar Narayan (Stanford), Xueming Luo (Temple), Puneet Manchanda (UMich), PK Kannan (UMaryland), Bin Gu (BostonU),  Roland Rust (UMaryland), Ravi Bapna (UMN), Ming-Hui Huang (NTU), Param Singh (CMU), Catherine Tucker (MIT), Olivier Toubia (Columbia), Shunyuan Zhang (Harvard)

Submission logistics: Submit either a 3-page abstract, full paper, or 10 PPT slides to; and cc the conference co-chairs:;;;

Submission deadline: October 26, 2020. Acceptance notification date: November 2, 2020 (Acceptance of submission requires one co-author to register and present at the conference)

This annual conference was hosted at Chicago Booth in 2014, NYU Stern in 2015 and 2017, Stanford GSB in 2016, CMU Tepper in 2018, and Temple in 2019. It has attracted a vibrant group of professors, industry people, and PhD students (each year max 150 people) working on cutting-edge ML AI models and data in inter-disciplinary fields. This conference serves as an intellectual bridge between computer science, economics, statistics, marketing, management, finance, strategy, IS, healthcare, education, public policy, and others.