Renée is an expert on the intersection between behavioral science and technology, and the implications for cognitive bias in human decision-making. She is a leading thinker on the science of digital brand strategy and her research and expertise have been published in various academic and trade publications.
Renée’s research examines how social structure and technology (e.g., Digital Customer Experience, Status, Social Media) affect performance and self-perception (as featured in her TEDx talk, “The Outsourced Mind”). Her projects have examined how cognitive style predicts preference for AI versus human input; the interaction of brand status and placebo effects in performance; how consumers determine real from fake products; the circumstances under which customers perceive value in platforms; and the effects of storytelling in social media on trust and persuasion.
Renée is a 2020 honoree on the Thinkers50 Radar List of thinkers who are “putting a dent in the universe,” and has been named one of the World’s Top 40 Professors under 40 by Poets and Quants.
Jeremy Howard is a data scientist, researcher, developer, educator, and entrepreneur. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible, and is an honorary professor at the University of Queensland. Previously, Jeremy was a Distinguished Research Scientist at the University of San Francisco, where he was the founding chair of the Wicklow Artificial Intelligence in Medical Research Initiative.
Jeremy was the founding CEO of Enlitic, which was the first company to apply deep learning to medicine, and was selected as one of the world’s top 50 smartest companies by MIT Tech Review two years running. He was the President and Chief Scientist of the data science platform Kaggle, where he was the top ranked participant in international machine learning competitions 2 years running. He was the founding CEO of two successful Australian startups (FastMail, and Optimal Decisions Group–purchased by Lexis-Nexis). Before that, he spent 8 years in management consulting, at McKinsey & Co, and AT Kearney. Jeremy has invested in, mentored, and advised many startups, and contributed to many open-source projects.
He has many media appearances, including writing for the Guardian, USA Today, and the Washington Post, appearing on ABC (Good Morning America), MSNBC (Joy Reid), CNN, Fox News, BBC, and was a regular guest on Australia’s highest-rated breakfast news program. His talk on TED.com, “The wonderful and terrifying implications of computers that can learn”, has over 2.5 million views. He is a co-founder of the global Masks4All movement.
Shan’s research focuses on the digital economy, social networks, and business analytics. Her current work investigates how new social media shapes the information environment and decision making that leads to non-negligible economic and social impacts. Specifically, her studies examine how social advertising and social referral affect product virality, how emotions shape online content diffusion, and how misinformation diffuses through weak ties in massive social networks.
Shan has a particular interest in understanding how certain phenomena vary across individuals, social ties, products, and markets, using population-scale datasets and large-scale field tests, and uses various research methodologies, including large-scale networked randomized field experiments, machine learning, and network analysis to pursue her research agenda.
Shan’s research has been published in prominent management journals, including Marketing Science and the Journal of Management Information Systems. She also collaborates with leading tech firms, such as Tencent, to understand cutting-edge digital phenomena and their implications for business and society.
She received a bachelor’s degree from Tsinghua University, a master’s degree from the University of British Columbia, and a Ph.D. from the MIT Sloan School of Management.
Xiang is deeply interested in understanding how efficiency and quality provision on such platforms could be enhanced through information design and platform strategies. He also examines the welfare impact of information technology and artificial intelligence in different fields.
Before joining WashU, Xiang was a postdoctoral associate at MIT Sloan Initiative on the Digital Economy. He received a Ph.D. in economics from Ohio State University.
Wang Jin is currently a research associate at the MIT Initiative on the Digital Economy and MIT Sloan School of Management. He was a former research fellow at IQSS Harvard University. Combining large-scale data from the Environmental Protection Agency and the Census,
Wang’s research concentrates on the impacts of information technology, structural management practices, and organizational structures on environmental performance and sustainability. He is also interested in identifying the effects of IT, management, and big data analytics on firms’ innovation capabilities.
Wang is currently involved in multiple Census projects, and has worked extensively within the U.S. Census Research Data Center, using business level confidential data protected under Title 13 and Title 26. He is also performing research on topics related to regulatory enforcement and firm compliance behavior.
Wang holds a Master’s degree in economics and recently received his PhD in economics from Clark University.
Sebastian is an assistant professor at the Stockholm School of Economics (House of Innovation) with an educational background in economics and management. He obtained his Ph.D. at the University of Geneva (Geneva School of Economics and Management) with his dissertation entitled “Artificial Intelligence in Organizations: Strategy and Decision Making in the Digital Age.” He has previously been a visiting researcher at Warwick Business School (Behavioural Science Group) and Stanford University (SCANCOR).
His research interests include digital transformation, organizational behavior, and strategy. Specifically, he explores how digital technologies like artificial intelligence impact organizational theory and applied strategy. His research uses varying methods and contexts to analyze how organizations create value through the adoption and development of digital technology, with a particular focus on the interaction between human beings and algorithms. He also explores societal and ethical aspects of digitalization. His research has been published in journals such as the Academy of Management Review and Strategic Management Journal.
Her research is empirically oriented, covering topics in market designs, digital platforms, and economics of digitization.
Her research centers on the use of information technology and data by firms, with an emphasis on strategy, organizational design, and process innovation. Her current focus is on data-driven decision making and how firms and individuals can use data to improve their performance. She is also actively investigating the economic and strategic impacts of cloud computing.
Kristina’s experience includes six years on the Harvard Business School faculty, as well as serving as a digital fellow at the MIT Initiative on the Digital Economy since 2013. She splits her time between Rotman, MIT, and the University of Toronto, Scarborough, where she teaches strategic management.
Prior to her academic career, Kristina worked for two early-stage technology ventures in Silicon Valley. She currently serves as a lab economist at the Creative Destruction Lab, one of Toronto’s premier seed-stage programs for technology startups.
Kristina’s work has been featured in Management Science, the American Economic Review, the Journal of Economics and Management Strategy, the Harvard Business Review, Sloan Management Review, Forbes, Rotman Magazine, and Communications of the ACM.
In addition to his role in the Digital Economy Lab, Christos holds several academic appointments, including as an Associate Research Professor at Arizona State University, Adjunct Associate Professor at the University of Nicosia, Non-resident fellow at Baylor University, and serves as a Senior Adviser on the National Artificial Intelligence Institute in the Department of Veterans Affairs. Christos’ primary academic research focuses on labor economics, the digital economy, and personal finance and well-being with articles in leading academic journals and a wide array of popular press media.
Representative articles:
Makridis, Christos A., Michael Froewis, Kiran Sridhar, and Rainer Boehme. (2023). The Rise of Decentralized Cryptocurrency Exchanges Evaluating the Role of Airdrops and Governance Tokens. Journal of Corporate Finance, 79.
Liu, Tim, Christos A. Makridis, Paige Ouimet, and Elena Simintzi. (2023). The Distribution of Non-Wage Benefits: Maternity Benefits and Gender Diversity. Review of Financial Studies, 36(1): 194–234.
Makridis, Christos A. (2022). The Social Transmission of Economic Sentiment on Consumption. European Economic Review, 148: 104232.
Makridis, Christos A., Anthony Boese, Rafael Fricks, Don Workman, Molly Klote, Joshua Mueller, Isabel Hildebrandt, Michael Kim, and Gil Alterovitz. (2023). Informing the Ethical Review of Human Subjects Research Utilizing Artificial Intelligence. Frontiers in Computer Science, 14(5).
Atkins, David, Christos A. Makridis, Rachel Ramoni, Gil Alterovitz, and Carolyn Clancy. (2022). Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration. Annual Review of Biomedical Data Science, 5: 393-413.
Hilary Mason is a data scientist in residence at Accel, where she has the opportunity to advise companies large and small on their data strategies. She spent four years as chief scientist at bitly, where she led a team that studied attention on the internet in realtime—incorporating a mix of research, exploration, and engineering. Hilary also co-founded HackNY, a non-profit that helps talented engineering students find their way into the startup community of creative technologists in New York City.
