CV

Education

• Postdoc, The Alan Turing Institute, 2022
• Postdoc, Vector Institute, 2021
• Ph.D in Electrical Engineering and Computer Science, Queen Mary University of London, 2021
• M.S. in Electrical Engineering (Digital), Sharif University of Technology, 2016

Work experience

• 2020: Internship
  • Inria
  • Project: Intersection of differential privacy and adversarial audios
  • Supervisors: Aurelien Bellet, Emmanuel Vincent, Marc Tommasi
• 2020: Research Assistant
  • Queen Mary University of London, University of Lisbon, Carnegie Mellon University
  • Project: FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances
  • Goal: Generate and conceal the adversarial perturbation within the original audio files
  • Supervisors: Alberto Abad, Bhiksha Raj, Andrea Cavallaro, Isabel Trancoso
• 2019: PhD Enrichment
  • The Alan Turing Institute
• 2018: Internship
  • The Alan Turing Institute
  • Project: Privacy-aware neural network classification & training
  • Goal: To invent new encrypted methods for neural network training and classification
  • Supervisors: Matt Kusner, Adria Gascon, Varun Kanade
• 2017: Research Assistant
  • Sharif University of Technology in Digital Media Lab (DML)
  • Duties included: Privacy-Preserving in Deep Learning
  • Supervisor: Hamid Reza Rabiee

Skills

• Programing
  • Python (PyTorch, Keras, Tensorflow, Caffe2, Caffe)
  • C/C++ (ABY (Multi-Party Computation), SEAL and HElib (Homomorphic Encryption))
  • Matlab
  • Verilog

Publications

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytic

Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi. (March 2017). "A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytic." ArXiv 1. 1(1).

A New Algorithm for Training Sparse Autoencoders

Ali Shahin Shamsabadi, Massoud Babaie-Zadeh, Seyyede Zohreh Seyyedsalehi, Hamid R Rabiee, Christian Jutten. (August 2017). "A New Algorithm for Training Sparse Autoencoders." 25th European Signal Processing Conference (EUSIPCO) 1. 1(2).

Privacy-Preserving Deep Inference for Rich User Data on The Cloud

Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi. (October 2017). "Privacy-Preserving Deep Inference for Rich User Data on The Cloud." ArXiv. 1710.01727.

Deep Private-Feature Extraction

Seyed Ali Osia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee. (Feb 2018). "Deep Private-Feature Extraction." IEEE Transactions on Knowledge and Data Engineering.

Private and Scalable Personal Data Analytics using Hybrid Edge-Cloud Deep Learning

Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Hamed Haddadi. "Private and Scalable Personal Data Analytics using Hybrid Edge-Cloud Deep Learning." IEEE Computer, Special Issue on Mobile and Embedded Deep Learning, May 2018.

Distributed One-Class Learning

Ali Shahin Shamsabadi, Hamed Haddadi, Andrea Cavallaro. "Distributed One-Class Learning." 25th IEEE International Conference on Image Processing (ICIP), October 7-10, 2018, Athens, Greece.

Providing Occupancy as a Service with Databox

Poonam Yadav, John Moore, Qi Li, Richard Mortier, Anthony Brown, Andy Crabtree, Chris Greenhalgh, Derek McAuley, Yousef Amar, Ali Shahin Shamsabadi, Hamed Haddadi. "Providing Occupancy as a Service with Databox." The 1st ACM International Workshop on Smart Cities and Fog Computing (CitiFog), November 4, 2018, Shenzhen, China.

SCENE PRIVACY PROTECTION

Chau Yi Li*, Ali Shahin Shamsabadi*, Ricardo Sanchez-Matilla*, Riccardo Mazzon, Andrea Cavallaro. "SCENE PRIVACY PROTECTION." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 12-17, 2019, Brighton, UK.
(*=authors contributing equally)

QUOTIENT: Two-Party Secure Neural Network Training and Prediction

Nitin Agrawal*, Ali Shahin Shamsabadi*, Matt J. Kusner, Adrià Gascón. "QUOTIENT: Two-Party Secure Neural Network Training and Prediction." ACM Conference on Computer and Communications Security (CCS), November 11-15, 2019, London, UK.
(*=authors contributing equally)

PrivEdge: From Local to Distributed Private Training and Prediction

Ali Shahin Shamsabadi, Adria Gascon, Hamed Haddadi, Andrea Cavallaro. "PrivEdge: From Local to Distributed Private Training and Prediction." IEEE Transactions on Information Forensics and Security (TIFS), April, 2020.

EdgeFool: An Adversarial Image Enhancement Filter

Ali Shahin Shamsabadi, Changjae Oh, Andrea Cavallaro. "EdgeFool: An Adversarial Image Enhancement Filter." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 4-8, 2020, Barcelona, Spain.

ColorFool: Semantic Adversarial Colorization

Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Andrea Cavallaro. "ColorFool: Semantic Adversarial Colorization." IEEE Conference on Computer Vision and Pattern Recognition (CVPR), May 14-19, 2020, Seattle, Washington, US.

Talks

A New Algorithm for Training Sparse Autoencoders

August 30, 2017

Poster at 25th European Signal Processing Conference (EUSIPCO), 2017, Kos island, Greece

Distributed One-Class Learning

August 29, 2018

Presentation at Summer school, 2018, Centre for Intelligent Sensing, Queen Mary University of London

Privacy-Aware Neural Network Classification & Training

September 10, 2018

Presentation at Alan Turing Institute, 2018, Alan Turing Institute, London

EdgeFool: an adversarial image enhancement filter

May 01, 2020

Presentation at International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020, Barcelona, Spain

ColorFool: Semantic Adversarial Colorization

June 01, 2020

Presentation at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, Washington, USA

Deep Learning for Privacy in Multimedia

June 01, 2020

Tutorial at ACM Multimedia Conference, 2020, Seattle, Washington, USA

Teaching

Advanced Mathematics

Neural Network

Machine Learning