Predictive Analytics Innovation Fellows
A home for faculty members interested in using analytical data to advance student learning, success, retention, and graduation at UCF, Predictive Analytics Innovation Fellows are selected based on a competitive proposal review process; all full-time UCF faculty are eligible to apply. Throughout the academic year, these Fellows form a community of scholars who support one another’s work examining UCF student performance at the course, program, college, or university level. Our goal is to leverage UCF data and faculty expertise to identify opportunities for improving student success.
Our Inaugural 2017-2018 Fellows Cohort
Ryan Goodwin, Ph.D.
Anna Drake, Ph.D.
Albert Xianling Liu, Ph.D.
Assistant Professor, Health Management and Informatics, College of Health and Public Affairs
Project Title: “Predicting risk for excess credit hours among undergraduates at UCF”
Haiyan Bai, Ph.D.
Associate Professor, Educational and Human Sciences, College of Education and Human Performance
Project Title: “Using analytical data to investigate multilevel predictors of undergraduate retention”
Ivan Garibay, Ph.D.
Assistant Professor, Industrial Engineering and Management Systems, College of Engineering and Computer Science
Project Title: “Curriculum navigator: Leveraging big data to improve student success”
Sumit Kumar Jha, Ph.D.
Associate Professor, Computer Science, College of Engineering and Computer Science
Project Title: “Deep learning-based automated student advisor for data-driven class registration guidance”
Adan Ernesto Vela, Ph.D.
Assistant Professor, Industrial Engineering and Management Systems College of Engineering and Computer Science
Project Title: “Rethinking degree plans in STEM fields”
Jacquelyn Chini, Ph.D.
Assistant Professor, Physics, College of Science
Project Title: “Assessing barriers to timely completion of the Physics major for transfer and FTIC students”