Ghazal Fazelnia

About me

I am a PhD candidate in Electical Engineering Department and Data Science Institute at Columbia University. I am working on Machine Learning and Optimization. In particular, my research is focused on probabilistic modeling and inference, optimization and convex relaxations, Bayesian models and deep learning. I am fortunate to be advised by Professor John Paisley. Here is my CV.

Email: ghazal(dot)fazelnia(at)columbia(dot)edu
Address: 500 West 120th St., Unit 416, New York, NY.

Google Scholar

Publications

Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John Paisley, "Mixed Membership Recurrent Neural Networks,".
Ghazal Fazelnia, John Paisley, "PrOMP: Probabilistic Orthogonal Matching Pursuit," submitted.
Ghazal Fazelnia, John Paisley, "CRVI: Convex Relaxation for Variational Inference," International Conference on Machine Learning (ICML), 2018.
Ghazal Fazelnia, Ramtin Madani, Abdulrahman Kalbat, Javad Lavaei, "Convex Relaxation for Optimal Distributed Control Problem," IEEE Transactions on Automatic Control, 2017.
Salar Fattahi, Ghazal Fazelnia, Javad Lavaei, Murat Arcak, "Transformation of Optimal Centralized Controllers into Near-Globally Optimal Static Distributed Controllers," IEEE Transaction on Automatic Control, 2017.
Ramtin Madani, Somayeh Sojoudi, Ghazal Fazelnia, Javad Lavaei, "Finding Low-rank Solutions of Sparse Linear Matrix Inequalities using Convex Optimization," SIAM Journal on Optimization, 2017.
Salar Fatahi, Ghazal Fazelnia, Javad Lavaei, "Transformation of Optimal Centralized Controllers Into Near-Global Static Distributed Controllers," Proc. of the 54th IEEE Conference on Decision and Control, 2015.
Ghazal Fazelnia, Ramtin Madani, Javad Lavaei, "Convex Relaxation for Optimal Distributed Control Problem," Proc. of the 53rd IEEE Conference on Decision and Control, 2014.
Ramtin Madani, Ghazal Fazelnia, Somayeh Sojoudi, Javad Lavaei, "Low-Rank Solutions of Matrix Inequalities With Applications to Polynomial Optimization and Matrix Completion Problems," Proc. of the 53rd IEEE Conference on Decision and Control, 2014. Best Paper Finalist.
Somayeh Sojoudi, Ramtin Madani, Ghazal Fazelnia, Javad Lavaei, "Graph-Theoretic Algorithms for Polynomial Optimization Problems," Proc. of the 53rd IEEE Conference on Decision and Control, 2014 (Invited tutorial paper).
Abdulrahman Kalbat, Ramtin Madani, Ghazal Fazelnia, Javad Lavaei, "Efficient Convex Relaxation for Stochastic Optimal Distributed Control Problem," Allerton Conference, 2014.
Mohammad. J. Salehi, Babak. H. Khalaj,Marcos Katz, Ghazal Fazelnia, Parishad Karimi, "Mobile Cloud Management: A New Framework," Proc. of IEEE Symposium on Personal, Indoor and Mobile Radioi Communications (PIMRC), 2012.
Mohammad J. Salehi, Babak H. Khalaj, Marcos Katz, Ghazal Fazelnia, Parishad Karimi, Javier Del Ser, "Mobile Clouds: How to Find Opportunities, " Proc. of IEEE Conference on Computer Aided Modeling and Design, 2012.

Awards

Travel Award for the International Conference on Machine Learning (ICML), 2018.
Microsoft Research Graduate Women's Scholarship , 2015. (one of the 10 students in the US and Canada to receive this award)
Best Paper Finalist at IEEE Conference on Decision and Control (CDC), 2014.
Iran four-year National Elite Foundation fellowship, 2009--2013.
Among top %0.06 students out of 350,000 participants in the national university entrance exam (Konkoor), Iran, 2009.
Bronze medalist in the National Mathematics Olympiad, Iran, 2008.

Professional Activities

Reviewer

ICML 2018, 2019
NIPS 2018
ICLR 2019
NIPS Workshop on Advances on Approximate Bayesian Inference (AABI) 2015--present
International Joint Conference on Artificial Intelligence (IJCAI) 2016
IEEE Transactions on Power Systems 2017
IEEE Transactions on Control of Network Systems 2015, 2016
International Workshop on Multimedia Signal Processing 2015
IEEE Conference on Decision and Control 2014--present
European Control Conference (ECC) 2014, 2015
System Science and Control Engineering Journal 2014
American Conference on Control 2014--present

Selected Teaching

Instructor for Machine Learning and Probabilistic Models in Columbia University Data Science Bootcamp, January 2018
Mentor in edX Online Program for Machine Learnign with More Than 200,000 Registered Students Worldwide, Spring 2017
Bayesian Models in Machine Learning, Fall 2016, Fall 2017, Fall 2018
Machine Learning, Spring 2016, Spring 2017, Spring 2018
Advanced Big Data Analytics, Spring 2015, Fall 2015
Convex Optimization, Fall 2014
Power Systems Analysis, Spring 2014
DSP: Digital Signal Processing, Fall 2012
Signals and Systems, Fall 2012
Linear Control and Lab., Fall 2012
Circuit Theory, Spring 2012, Fall 2012
Logic Circuits and Lab., Spring2012