Feras Saad

PhD Student
Computer Science and Artificial Intelligence Laboratory (CSAIL)
Department of Electrical Engineering and Computer Science (EECS)
Massachusetts Institute of Technology (MIT)

fsaad [at] mit.edu    Github

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.

Publications

Time Series Structure Discovery via Probabilistic Program Synthesis
Schaechtle*, U., Saad*, F., Radul, A., and Mansinghka, V. arXiv preprint, arXiv:1611.07051, 2017. [Abstract, Paper]

Probabilistic Search for Structured Data via Probabilistic Programming and Nonparametric Bayes
Saad, F. Casarsa, L., and Mansinghka, V. arXiv preprint, arXiv:1704.01087, 2017. [Abstract, Paper]

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]

Software

My primary software projects, developed with colleagues at probcomp, involve:
= BayesDB, a probabilistic programming platform for probabilistic data analysis.
= cgpm, a library of composable probabilistic models, which serves as the main modeling and inference backed of BayesDB.
= iventure, an interactive, web-based front-end for BayesDB built on top of Jupyter.

Awards

Charles & Jennifer Johnson Computer Science Master of Engineering Thesis Award, MIT EECS 2017.

Teaching

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.

Writing

During undergrad I wrote various op-eds for The Tech, MIT's dwindling student newspaper.
Prior to that, I was a sports journalist at Goal.com.