Lyle Ungar, professor in the department of computer and information science in Penn’s School of Engineering, is a member of the newest class of Leshner Fellows selected by the American Association for the Advancement of Science. He is being recognized for his work using machine learning and text mining on social media messages to study physical and mental health.

Leshner Fellows are chosen for having demonstrated leadership and excellence in their research careers and an interest in promoting meaningful dialogue between science and society. Each cohort is focused on a different pressing social issue; previous classes have covered climate change, human augmentation and infectious disease. The fellows of the 2020–2021 class work in a range of fields, but each is focused on developing and studying machines and algorithms that augment or mimic human abilities, learn from and adjust to new situations and perform tasks.

Dr. Ungar is a member of the Penn Research in Machine Learning Group and a principal investor in the World Well Being Project, which seeks to develop “new techniques for psychological well-being and physical health based on language in social media.” His 2015 TedxPenn talk, “Using Twitter to Predict Heart Disease,” showcases his research and explains how text from Twitter and Facebook posts can be used as qualitative insight into the health of a community.