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Bio

I am working as a postdoctoral scholar at Network Security Lab, University of Washington. I received my Ph.D. degree in Computer Science from Oregon State University (OSU) under supervision of Prof. Rakesh B. Bobba. My Ph.D. project focused on Image Privacy and intersection of Machine Learning and Cybersecurity. I collaborated with Prof. Wuchi Feng and Prof. Charles Wright at Portland State University on my image privacy project. In this project we exploed the practical adversarial perturbations for my image privacy in image sharing platforms project. I also worked with Dr. Mahdieh Abbasi, from Univertie’ Laval in Quebec, on our dependable and secure deep neural networks project in which we tended to detect and reject adversarial and out-distribution examples. I also worked as gradurate research assistant at Digital Media Lab and conducted research on complex networks analysis methods and graph theories. I received my Master’s and Bachelor’s degrees in Computer Engineeing and Computer Science at Sharif University of Technology. In general, my research areas of intrerest are:

• Robust and Private Deep Learning
• Reinforcement Learning
• Natural Language Processing
• Cybersecurity

Education

• Ph.D. Candidate in Computer Science (2014 – 2021)
  Oregon State University, Corvallis, Oregon, USA.
  Thesis: Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

• Master of Science (M.S.) in Computer Engineering (Software engineering) (2011 – 2013)
  Sharif University of Technology, Department of Computer Engineering
  Thesis: Local Community Detection in Social Networks

• Bachelor of Science (B.S.) in Computer Science (2005 – 2010)
  Sharif University of Technology, Department of Computer Science
  Thesis: Community Detection in Complex Networks

Certificates

• Spark Fundamentals II, Cognitive Class (An IBM Initiative)
• Data Science Foundation - Level 2, Cognitive Class (An IBM Initiative)
• Spark MLlIB, Cognitive Class (An IBM Initiative)
• Exploring Spark’s GraphX, Cognitive Class (An IBM Initiative)
• Data Science Methodology, Cognitive Class (An IBM Initiative)
• Data Science Hands-On with Open Source Tools, Cognitive Class (An IBM Initiative)

Please click here to see certificates.

News

• My paper, “Adversarial Images Against Super-Resolution Convolutional Neural Networks for Free”, was accepted in Privacy Enhancing Technologies Symposium 2022.
• Attended [10th Montréal Industrial Problem Solving]
• Presented my poster in S&P 2021
• Joined NSL, University of Washington as Postdoctoral Scholar my PhD, March. 2021.
• Joined the Network Security Lab (NSL) group at University of Washington, March 2021.
• Defended my PhD, Feb. 2021.
• My paper, “Resilience Against Data Manipulation in Distributed Synchrophasor-Based Mode Estimation”, was accepted in IEEE Transaction on Smart Grid.
• Attended 10th Montréal Industrial Problem Solving Workshop and worked on Data Anonymization and Synthesis project (Desjardins Group). The report will be available soon.
• First place winner at Grad show case poster presentation, ”Towards Dependable Deep CNNs with Out-distribution Learning ” 2018
• Won student scholarship from CREDC summer school, 2017
• Won student travel award from GREPSECIII Workshop and IEEE Symposium on Security and Privacy,2017
• Won student travel award from Conference on Computer and Communications Security (CCS), 2017
• Won student travel award from Annual Computer Security Applications Conference (ACSAC), 2016