I am an assistant professor in the Department of Electrical and Systems Engineering (as of July 2017). I hold a secondary appointment in the Department of Computer and Information Systems. I am also a faculty affiliate of the Warren Center for Network and Data Sciences.
Before joining Penn, I was a research fellow at the Simons Institute, UC Berkeley (program: Foundations of Machine Learning). Prior to that, I was a post-doctoral scholar and lecturer in the Institute for Machine Learning at ETH Zürich. I received my Ph.D. degree in Computer and Communication Sciences from EPFL.

Some Recent Publications

M. Fazlyab, A. Robey, H. Hassani, M. Morari, G. Pappas Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks, 2019.

A. Robey, A. Adibi, B. Schlotfeldt, G. Pappas, H. Hassani Optimal Algorithms for Submodular Maximization with Distributed Constraints, 2019.

Z. Shen, H. Hassani, A. Ribeiro Hessian Aided Policy Gradient, 2019.

M. Zhang, L. Chen, A. Mokhtari, H. Hassani, A. Karbasi Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization, 2019.

H. Hassani, A. Karbasi, A. Mokhtari, Z. Shen Stochastic Conditional Gradient++, 2019.

A. Gotovos, H. Hassani, A. Krause, S. Jegelka, Discrete Sampling Using Semigradient-based Product Mixtures, 2018.

A. Mokhtari, H. Hassani, A. Karbasi, Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization, 2018.

Y. Balaji, H. Hassani, R. Chellappa, S. Feizi, Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs, 2018.

K. Gatsis, H. Hassani, G. J. Pappas, Latency-Reliability Tradeoffs for State Estimation, 2018.

A. Mokhtari, H. Hassani, A. Karbasi, Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings, 2018.

M. Fereydounian, V. Jamali, H. Hassani, H. Mahdavifar, Channel Coding at Low Capacity, 2018.

A. Fazeli, H. Hassani, M. Mondelli, A. Vardy, Binary Linear Codes with Optimal Scaling: Polar Codes with Large Kernels, 2018.

H. Hassani, S. Kudekar, O. Ordentlich, Y. Polyanskiy, R. Urbanke, Almost Optimal Scaling of Reed-Muller Codes on BEC and BSC Channels, 2018.

L. Chen, C. Harshaw, H. Hassani, A. Karbasi, Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity, 2018.

M. Hayhoe, F. Barreras, H. Hassani, V. M. Preciado, SPECTRE: Seedless Network Alignment via Spectral Centralities, 2018.

Y. Chen, S. H. Hassani, A. Krause, Near-optimal Bayesian Active Learning with Correlated and Noisy Tests, 2017.


ICML 2019: We will present our work on Hessian-Aided Policy Gradient and A Statistical Approach to Compute Sample Likelihoods in GANs.

Data Science Summer School, Ecole Polytechnique, 2019: I will be giving 6 lectures on "Theory and Applications of Submodularity: From Discrete to Continuous and Back".

Allerton 2018: We will be hoding a session on "Submodular Optimization" with 5 great speakers.

ICML 2018: We will present our work on Decenteralized Submodular Maximization and Projection-Free Online Optimization.

ISIT 2018: We will present our work on The Scaling of Reed-Muller Codes and A New Coding Paradigm for the Primitive Relay Channel.

Invited talk at the workshop on local algorithms (MIT) on "Submodular Maximization: The Decentralized Setting" (June 15th).

AISTATS 2018: We will present our work on The Stochastic Frank-Wolfe Method and Online Submodular Maximization.

Invited talk at the workshop on coding and information theory (Harvard, CSMA) and the University of Maryland (ECE) on "Non-asymptotic Analysis of Codes and its Practical Significance" (April 13th and March 29th).

NSF CISE Research Initiative (NSF-CRII) award, 2018.

Invited talk at the Santa Fe Institute on "Sequential Information Maximization: From Theory to Designs" (Feb 21st).

Talk at the Dagstuhl Seminar and ITA 2018 on "Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings" (Feb 16th).

Talk at UPenn ESE on "Coding for IoT" (Jan 26th).

We are organizing a session on "Submodular Optimization" at the 2018 INFORMS Optimization Society Conference.

AAAI 2018: We will present our work Learning to Interact with Learning Agents.

I will serve as a program committe member for IEEE International Symposium on Information Theory (ISIT'18). Please consider submitting your work to ISIT!

NIPS 2017: We will present our works on Stochastic Submodular Maximization and Gradient Methods for Submodular Maximization.

Invited talk at MIT EECS on "Recent Advances in Channel Coding" (Nov 1st).

Invited talk at Yale Institute for Networking Science (YINS) on "K-means: A Nonconvex problem with Fast and Provable Algorithms" (Oct 25th).


In person :465C (3401 Walnut st.)
Cell :650 666 5254
email :hassani@seas.upenn.edu
mail:Dept. of Electrical & Systems Engineering
 University of Pennsylvania
 Room 465C
 3401 Walnut Street
 Philadelphia, PA 19104