I am a PhD student (MEng/SB 2016) in Computer Science and Artificial Intelligence. I am a member of the Probabilistic Computing Project, advised by Vikash Mansinghka. My research is centered around the design and implementation of probabilistic systems; algorithmic approaches to statistical data analysis; and computational formalisms of probability theory.
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes
Saad, F. and Mansinghka, V. Artificial Intelligence and Statistics (AISTATS), 2017. [Abstract, Paper, Supplement]
A Probabilistic Programming Approach To Probabilistic Data Analysis
Saad, F. and Mansinghka, V. Advances In Neural Information Processing Systems (NIPS), 2016 [Abstract, Paper]
Journal version in review at the Journal of Machine Research, preprint at arXiv:1608.05347. [Abstract, Paper]
Charles & Jennifer Johnson Computer Science Master of Engineering Thesis Award, MIT EECS 2017.
Summer 2017: Instructor at the
Probabilistic Programming for Advanced Machine Learning Summer School
in Washington, DC.
Fall 2016: TA for 9.S915, Introduction to Probabilistic Programming, a graduate seminar at MIT.
Summer 2015: Instructor at the Probabilistic Programming for Advanced Machine Learning Summer School in Portland, Oregon.