About AIBA

The mission of this Global Institute for Artificial Intelligence and Business Analytics (AIBA), formally known as Global Center for Big Data in Mobile Analytics, is to become an inter-disciplinary leader in artificial intelligence and machine learning applications for research and education in Marketing, IS, Finance, Accounting, Strategy, Management, and other business disciplines. Internally, AIBA will empower faculty and doctoral students with a library of cutting-edge AI/ML models and algorithms via hands-on coding exercises, real-world business problems, and top journal publication for higher research productivity and contributions to their respective disciplines. Externally, AIBA will collaborate with academic scholars and industry practitioners world-wide to leverage unstructured text/audio/image/video data and explore AI, 5G, AR, VR, IoT, blockchain applications in social media, banking, health care, education, digital commerce, sharing economy platforms, and other domains to benefit consumers, companies, and society.

Global Institute for Artificial Intelligence & Business Analytics
Fox School of Business
1801 Liacouras Walk – Alter Hall A506J
Philadelphia, PA 19122
Center Email: [click-for-email]

AIBA Conferences

• November 2013, ‘Big Data Mobile Analytics Symposium’ at Temple University, Philadelphia
• July 2014, ‘Big + Small Data Marketing Analytics Conference’ at Fudan University, Shanghai, China
• October 2014, ‘Big Data Marketing Analytics Conference’ at University of Chicago, ChicagoBooth School, Chicago
• March 2015, ‘Mobile Big Data Marketing Analytic Conference’ at LMU Munich, Germany
• October 2015, ‘Smart Life Big Data Marketing Analytic Conference’ at New York University, Stern School of Business, New York
• June 2016, ‘Mobile Big Data Conference’ at Chinese University of Hong Kong Business School, Hong Kong, China
• December 2016, ‘Digital Marketing Conference’ at Stanford University, Stanford Business School, Stanford
• December 2017, ‘Digital, Mobile Marketing, Social Media Analytics Conference’ at New York University, Stern School of Business, New York
• December 2018, ‘Digital Marketing and Machine Learning Conference’ at Carnegie Mellon University, Tepper School of Business
• December 2019, ‘Artificial Intelligence, Machine Learning, and Business Analytics Conference‘ at Temple University Fox School of Business (co-chaired with NYU Stern and CMU Heinz)
• December 2020, ‘Virtual Conference on Artificial Intelligence, Machine Learning, and Business Analytics‘ (co-chaired with NYU Stern and CMU Heinz)
• December 2021, ‘Virtual Conference on Artificial Intelligence, Machine Learning, and Business Analytics‘

Director

XUEMING LUO

• Curriculum Vitae (PDF)
• SSRN Profile
• Website

Xueming Luo is Charles Gilliland Distinguished Chair Professor of Marketing, Professor of Strategy, and Professor of Management Information Systems. He is the Founder/Director of the Global Center for big data in mobile analytics in the Fox School of Business at Temple University.

Recently, Xueming Luo has been ranked as the top 15^th among all authors around the world (2008-2017 period) in the two premier AMA Journals (Journal of Marketing Research, Journal of Marketing): see the list here.  His name has also been ranked as the top 21^th among all authors around the world in the same period in the top four premier Journals (Journal of Consumer Research, Journal of Marketing, Journal of Marketing Research, Marketing Science) in the marketing discipline: see the list here.

Assistant Director

YANG WANG

Yang Wang is Assistant Professor of Marketing and Assistant Director of the Global Center for Artificial Intelligence & Business Analytics in the Fox School of Business at Temple University. His work has been published in Journal of Marketing Research and disseminated in Harvard Business Review. Yang has methodological expertise in econometric causal inference and applications of machine learning, including deep learning, natural language processing, and analysis of audio and visual data. Yang is also actively involved in the large scale collection and collation of online reviews, social media, geographic tracking datasets for academic research.