Jackson Killian is a PhD student studying Computer Science at Harvard University, with a B.S. in Physics and Computer & Information Science from The Ohio State University (OSU). At Harvard, he is advised by Prof. Milind Tambe. His research currently lies at the intersection of machine learning, optimization and public health, leading him to technical interests in sequential planning paradigms including Markov Decision Processes and Restless Bandits, particularly in online learning settings. His application-based interests are in the challenges that arise from making AI tools work for community health workers in the field, especially in low-resource contexts. He is also broadly interested in data science problems that leverage human-generated behavioral data to derive insights focused on improving health.
Jackson is currently funded by a National Science Foundation Graduate Research Fellowship and was previously a Pelotonia Research Fellow in 2016.