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
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