Daniel Neill

Congratulations to Daniel’s PhD student Dylan Fitzpatrick (at Carnegie Mellon’s Joint PhD Program in Machine Learning and Policy) for the successful defense of his doctoral dissertation, “Predicting Health and Safety: Essays in Machine Learning for Decision Support in the Public Sector”. Dylan will be joining the University of Chicago Crime Lab as a Research Director.

Congratulations to Daniel’s PhD student William Herlands (at Carnegie Mellon’s Joint PhD Program in Machine Learning and Policy) for the successful defense of his doctoral dissertation, “Change Modeling for Understanding our World and the Counterfactual One(s)”.

Daniel is delighted and honored to be part of several new communities, as Affiliated Faculty in the NYU Center for Data Science and as part of the inaugural Editorial Board of the newly formed INFORMS Journal on Data Science.

… on two new publications!

Luo, M., Du, B., Klemmer, K., Zhu, H., Ferhatosmanoglu, H., & Wen, H. (2020). D3P: Data-driven Demand Prediction for Fast Expanding Electric Vehicle Sharing Systems. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(1), 1-21. (link)

Klemmer, K., Yeboah, G., Porto de Albuquerque, J., Jarvis, S. (2020). Population Mapping in Informal Settlements with High-Resolution Satellite Imagery and Equitable Ground-Truth. ML-IRL Workshop, ICLR 2020, Addis Ababa, Ethiopia. (link)

Our latest publications: new approaches for finding spatial hotspots of disease infection risk using Twitter data, and performing counterfactual causal inference with change surfaces.