Ask the Experts Panel
AI and ML
Friday, April 25th | 10:30 AM EDT

Biography

Louis Tay is the William C. Byham Associate Professor of Industrial-Organizational Psychology at Purdue University. His substantive research interests include well-being (subjective well-being, psychological well-being), character strengths, and vocational interests. His methodological research interests include measurement, item response theory, latent class modeling, multilevel analysis, and data science. He is a co-editor of the books Big Data in Psychological Research (APA Books) and Handbook of Well-Being (DEF Publishers). He has contributed to the United Nations’ research reports on well-being and serves in consulting roles to top tech companies and Fortune 500 organizations. Consultations have involved topics such as better understanding customer and employee well-being, improving recruitment and selection processes, and understanding biases in measurement, machine learning, and AI. He is the founder of the tech-startup ExpiWell (www.expiwell.com) that advances the science and capture of daily life experiences through experience sampling methodology.

As an I-O psychologist embedded within the broader field of psychology, my goal is to programmatically pursue cross-disciplinary lines of inquiry in methodology (i.e., measurement, continuum specification, latent class modeling, Big Data / data science) and well-being (i.e., societal well-being, wellness programs, work – leisure [e.g., arts/humanities activities] interface). I have co-edited the following books: Big Data in Psychological Research, Handbook of Well-Being, Handbook of Positive Psychology Assessment, The Oxford Handbook of the Positive Humanities, and Technology and Measurement around the Globe. My greatest joy comes from mentoring students and post-docs.

Biography

Dr. Richard Landers, Ph.D., is an Associate Professor of Psychology, and holds the John P. Campbell Distinguished Professorship of Industrial-Organizational

Psychology at the University of Minnesota. His research concerns the use of innovative technologies in assessment, employee selection, adult learning, and

research methods. Recent topics have included big data, game-based learning, game-based assessment, gamification, unproctored Internet-based testing, mobile

devices, virtual reality, and online social media. His work has been published in Journal of Applied Psychology, Industrial and Organizational Psychology Perspectives, Computers in Human Behavior, Simulation & Gaming, Social Science Computer Review, and Psychological Methods, among others, and his research and writing have been featured in Forbes, Business Insider, Science News, Popular Science, Maclean’s, and the Chronicle of Higher Education, among others. He is also author of a statistics textbook, A Step-by-Step Introduction to Statistics for Business, editor of Social Media in Employee Selection, and editor of the upcoming Cambridge Handbook of Technology and Employee Behavior. He currently serves as Associate Editor of Simulation & Gaming and the International Journal of Gaming and Computer-Mediated Simulations, and he is also part of the steering committee of the Coalition for Technology in Behavioral Science.

Biography

Dr. Tianjun Sun’s research primarily focuses on personnel selection, individual differences, psychometrics, and using advanced technology and quantitative methods to enhance staffing decisions, improve candidate/employee experiences, and solve organizational problems.

Dr. Sun actively publishes in reputable, high-impact journal outlets, and her projects have been supported by the National Science Foundation (NSF), the National Institutes of Health (NIH), and the Society for Industrial and Organizational Psychology (SIOP) Foundation.

Dr. Sun has been recognized as a Rising Start by the Associate for Psychological Science (APS) and has received a series of awards from SIOP, the American Psychological Association (APA), and the Academy of Management (AOM).

On the applied side, Dr. Sun has broad experience working in consulting, testing, and tech industries, as well as in areas of people analytics, learning and testing, and talent assessment.

RESEARCH INTEREST GROUP