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, where we design and build probabilistic systems. My research interests are in probabilistic AI, computational formalisms of probability theory, and algorithmic approaches to statistical data analysis.
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, preprint at arXiv:1608.05347. [Abstract, Paper]
Charles & Jennifer Johnson Computer Science Master of Engineering Thesis Award, MIT EECS 2017.
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.