Zahra Shakeri

Research Scientist

Meta Inc

Email: zshakeri at meta dot com

About Me

I am currently a Research Scientist at the Modern Recommendation Systems team in Meta where I specialize in leveraging deep multimodal and graph neural networks for user understanding to improve recommendations for the Facebook Discovery Engine. Previously, I was part of Meta AI, where I worked on developing neural networks to address integrity-related problems on the Meta platform and ensure safety of users.

Prior to joining Meta, I was a Sr. AI Scientist at the EA Data Plaform AI Applications team at Electronic Arts where I worked on developing data-driven AI solutions to game team problems. More specifically, I worked on leveraging sequence-to-sequence deep learning models for text to speech synthesis and voice conversion.

I received my PhD degree in Electrical and Computer Engineering from Rutgers University in 2019. I was part of the INSPIRE lab, working under the supervision of Prof. Waheed Bajwa. I received my MS in Electrical and Computer Engineering from Rutgers University in 2016 and my BS in Electrical Engineering from Sharif University of Technology in Iran in 2013.

My Google Scholar Profile.

My CV.

Experience

Research Scentist - Nov. 2021 to Present

Meta, Menlo Park, CA

Sr. AI Scientist - Jun. 2019 to Oct. 2021

Electronic Arts, Redwood City, CA

Graduate Assistant - Sept. 2013 to May 2019

Department of Electrical and Computer Engineering, Rutgers University, NJ

Data Science Research Intern - May 2018 to Sept. 2018

Adobe Research, San Jose, CA

Intern - May 2017 to Sept. 2017

Technicolor Artificial Intelligence Lab, Los Altos, CA

Preprints

S. Gururani, K. Gupta, D. Shah, Z. Shakeri, J. Pinto, “Prosody Transfer in Neural Text to Speech Using Global Pitch and Loudness Features", arXiv preprint arXiv:1911.09645, 2020.

Book Chapters

Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample Complexity Bounds for Dictionary Learning from Vector- and Tensor-valued Data", in Information-Theoretic Methods in Data Science, UK: Cambridge University Press, 2020.

Journal Publications

M. Ghassemi, Z. Shakeri, A.D. Sarwate, W.U. Bajwa, "Learning Mixtures of Separable Dictionaries for Tensor Data: Analysis and Algorithms", in IEEE Trans. Signal Process., vol. 68, pp. 33-48, Nov. 2019. Matlab Codes.
Z. Shakeri, A.D. Sarwate, W.U. Bajwa, "Identifiability of Kronecker-structured Dictionaries for Tensor Data", in IEEE Journal of Special Topics in Signal Processing, vol. 12, no. 5, pp. 1047-1062, Oct. 2018.
Z. Shakeri, W.U. Bajwa, A.D. Sarwate, "Minimax lower bounds on dictionary learning for tensor data", in IEEE Trans. Inf. Theory, vol. 64, no. 4, pp. 2706-2726, April 2018.

Conference Publications

M. Ghassemi, Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, "Sample Complexity Bounds for Low-Separation-Rank Dictionary Learning", Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2019.
Z. Shakeri, B. Taki, A. L. F. de Almeida, M. Ghassemi, and W. U. Bajwa, "Revisiting Sparse Channel Estimation in Massive MIMO-OFDM Systems", Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2019.
Z. Shakeri, A.D. Sarwate, W.U. Bajwa, "Identification of Kronecker-structured dictionaries: An asymptotic analysis", Proc. 7th IEEE Int. Workshop on Computational Advances in Multi-sensor Adaptive Processing (CAMSAP), 2017.
M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, "STARK: Structured dictionary learning through rank-one tensor recovery", Proc. 7th IEEE Int. Workshop on Computational Advances in Multi-sensor Adaptive Processing (CAMSAP), 2017. (Nominated for best student paper award)
Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, "Minimax lower bounds for dictionary learning from tensor data", Proc. Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS), Lisbon, Portugal, June 5-8, 2017.
Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, "Sample complexity bounds for dictionary learning of tensor data", Proc. 41st IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), New Orleans, LA, Mar. 5-9, 2017, pp. 4501-4505.
Z. Shakeri, W.U. Bajwa, A.D. Sarwate, "Minimax lower bounds for Kronecker-structured dictionary learning", Proc. IEEE Int. Symp. Information Theory (ISIT), 2016, pp. 1148 - 1152.
Z. Shakeri, W.U. Bajwa, "Revisiting maximal response-based local identication of overcomplete dictionaries", Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016.
Z. Shakeri, W.U. Bajwa, "Deterministic selection of pilot tones for compressive estimation of MIMO-OFDM channels", Proc. 48th Annu. Conf. Information Sciences and Systems (CISS), Baltimore, MD, Mar. 18-20, 2015, pp. 1-6.
Z. Shakeri, H. Raja, W.U. Bajwa, "Dictionary learning based nonlinear classier training from distributed data", Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP), Symposium on Network Theory, Atlanta, GA, Dec. 3-5, 2014, pp. 759-763.
Z. Shakeri, A. Fazeli Chaghooshi, M. Mirmohseni, and M. R. Aref, "Degrees of Freedom in a Three-User Cognitive Interference Channel", Proc. Iran Workshop on Communication and Information Theory (IWCIT), IEEE, 2013, pp. 1-6.

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