Lawrence Chillrud

Research

I am a Ph.D. student in Electrical Engineering at Northwestern University, working in the Department of Electrical & Computer Engineering. Broadly, I'm interested in developing and applying interpretable, robust, and fair machine learning and artificial intelligence algorithms for problems in precision medicine, clinical healthcare, and public health.

Currently, I am lucky to be advised by both Dr. Lee Cooper, working as part of the Computational and Integrative Pathology Group at Northwestern's Feinberg School of Medicine, as well as Dr. Aggelos Katsaggelos, working in the Image and Video Processing Lab at Northwestern's Evanston campus. I am soon to begin work on two projects, one exploring weakly-supervised learning / multiple instance learning for a survival analysis of a cohort of patients suffering from gliomas of varying severity, and the other investigating deep learning models for brain tumor image segmentation.

Formerly, I was a senior programmer at Columbia University's Mailman School of Public Health, working in the Department of Environmental Health Sciences. While there, I was fortunate to have worked under the mentorship of Dr. Marianthi-Anna Kioumourtzoglou as a part of her group, makLab. My research at Mailman focused on the development of interpretable machine learning methods for assessing complex mixtures of environmental exposures. In this work, I had the pleasure of collaborating with many incredible colleagues, including Dr. Jeff Goldsmith and Dr. John Wright.

In 2020, I also conducted research in natural language processing at Columbia's Computer Science Department under Dr. Kathleen McKeown. I worked to develop automatic fact-checking models to combat misinformation surrounding COVID-19, climate change, and the 2020 U.S. presidential election.