Data analytics provides a path for examining the institutional barriers that lead to students leaving or stopping their higher education journey—and sheds light on what institutional supports are effective in moving student success practices forward.
David Kil is CEO at Healthmantic, focusing on prescriptive and causal machine learning analytics going beyond predictive models to help lower equity gaps. He also advises startups in AI/ML areas. He’s been leading a team in connecting predictive models to prescriptive action opportunities, followed by intervention design and impact analysis for continuous process improvement. Prior to Healthmantic, he held Chief Science Officer and similar roles at Civitas Learning, Healthcrowd, Humana, SKT Americas, and Accenture Tech Labs, building both enterprise and consumer health and learning applications leveraging big data, social network, and networked sensors. That work led to a 3-year NIH grant on building social networks to help spread good health behaviors. His research interests encompass all aspects of data processing, machine learning, complex event processing, nudging, behavior science, and multi-level impact analysis. He has published over 50 papers in various journals and conferences, as well as a book entitled (with Frances Shin) “Pattern Recognition and Prediction with Applications to Signal Characterization” by Springer-Verlag. He holds 15 US and international patents and is active as a reviewer for journals and grant agencies. He received BS in EE and Chemistry at the U. of Illinois at Urbana-Champaign (Highest Honor), and MSEE from NYU, and MBA from Arizona State University.
Preventing a Winter of Disillusionment: Artificial Intelligence and Human Intelligence in Student Success
Using artificial intelligence to better inform human intelligence, higher education can prevent a winter of disillusionment and ensure tangible student success outcomes.