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Assistant Engineering

Location:
McLean, VA, 22102
Posted:
January 15, 2020

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Resume:

Poorya Mianjy

Contact

Information

Malone ***, *400 N Charles St 443-***-****

Baltimore, MD 21218 adbbdf@r.postjobfree.com

Website: http://cs.jhu.edu/ r3831/

Education Ph.D. in Computer Science 2014 - Present M.Sc.Eng. in Computer Science

Johns Hopkins University, Baltimore, MD

Major: Machine Learning

Advisor: Raman Arora, Ph.D

M.Sc. in Computer Engineering 2008 - 2011

Sharif University of Technology, Tehran, Iran

Major: Arti cial Intelligence

B.Sc. in Computer Engineering 2004 - 2008

Amirkabir University of Technology, Tehran, Iran

Major: Software Engineering

Publications Poorya Mianjy and Raman Arora. \On Dropout and Nuclear Norm Regularization" . Proceedings of the 36th International Conference on Machine Learning (ICML). 2019.

Enayat Ullah, Poorya Mianjy, Teodor Marinov, and Raman Arora. \Streaming Kernel PCA with ~

O(pn) Random Features" Advances in Neural Information Processing Systems (NeurIPS). 2018.

Poorya Mianjy, Raman Arora, and Rene Vidal. \On the Implicit Bias of Dropout" . Proceedings of the 35th International Conference on Machine Learning

(ICML). 2018.

Poorya Mianjy and Raman Arora. \Stochastic PCA with ‘2 and ‘ 1

Regularization." Proceedings of the 35th International Conference on Machine Learning (ICML). 2018.

(* Equal Contribution) *Teodor Marinov, *Poorya Mianjy, and Raman Arora.

\Streaming Principal Component Analysis in Noisy Settings." Proceedings of the 35th International Conference on Machine Learning (ICML). 2018.

(Alphabetical Order) Raman Arora, Teodor Marinov, Poorya Mianjy, and Nati Srebro. \Stochastic approximation for canonical correlation analysis." Advances in Neural Information Processing Systems (NeurIPS). 2017.

(Alphabetical Order)Raman Arora, Amitabh Basu, Poorya Mianjy, and Anirbit Mukherjee. \Understanding Deep Neural Networks with Recti ed Linear Units." 6th International Conference on Learning Representations (ICLR). 2017. Raman Arora, Poorya Mianjy, and Teodor Marinov. \Stochastic optimization for multiview representation learning using partial least squares" Proceedings of the 33th International Conference on Machine Learning (ICML). 2016. Honors and

Awards

Data Science Fellowship, Oct 2019

Mathematical Institute for Data Science

Baltimore, MD

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Best Poster Award,

Princeton Day of Optimization Oct 2018

Princeton, NJ

Travel Awards

ICML, Long Beach, CA Jun 2019

ICML, Stockholm, Sweden Jul 2018

ICLR, Vancouver, Canada May 2018

NeurIPS, Long Beach, CA Dec 2017

ICML, New York City, NY Jun 2016

Academic and

Professional

Service

Reviewer for JMLR, AISTATS, ALT, ICML, NeurIPS

JHU Ph.D. Admission Committee 2016 - Present

Reviewed ML/Theory applications and interviewed applicants Women in Science and Engineering (WISE) Spring 2017 Mentored a high-school senior student

JHU NACLO Committee 2014 { 2015

Held practice sessions

Supervised NACLO open-round competition

Presentations CMU Summer School on Human Language Technology Jun 2017 Multiview Representation Learning Lab

Carnegie Mellon University, Pittsburgh, PA.

CLSP Student Seminar Dec 2016

Stochastic Approximation for Partial Least Squares Johns Hopkins University, Baltimore, MD.

JHU Summer School on Human Language Technology Jun 2016 Representation Learning Lab

Johns Hopkins University, Baltimore, MD.

Work

Experience

Graduate Research Assistant 2014 { Present

Department of Computer Science, Johns Hopkins University

Stochastic approximation for subspace learning and its variants

Understanding the representational power of deep neural networks

Understanding the inductive bias due to algorithmic heuristics in deep learning Teaching Assistant

Department of Computer Science, Johns Hopkins University EN 600.675 - Statistical Machine Learning Fall 2017, Springs 2015 EN 600.679 - Representation Learning Fall 2016, Fall 2015 EN 600.475 - Introduction to Machine Learning Fall 2014 Department of Computer Engineering, Sharif University of Technology CE 40.725 - Statistical Pattern Recognition Springs 2014 CE 40.181 - Engineering Probability and Statistics Springs 2010 CE 40.725 - Stochastic Processes Fall 2009

Network Engineer 2012 { 2013

Research and Development Team, Pars Online Company Several large-scale ADSL projects

2 of 2



Contact this candidate