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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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portfolio
Portfolio item number 1
Published:
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Portfolio item number 2
Published:
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publications
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytic
Published in IEEE Internet of Things Journal, 2017
A New Algorithm for Training Sparse Autoencoders
Published in 25th European Signal Processing Conference (EUSIPCO), 2017
Privacy-Preserving Deep Inference for Rich User Data on The Cloud
Published in ArXiv, 2017
Deep Private-Feature Extraction
Published in IEEE Transactions on Knowledge and Data Engineering (TKDD), 2018
Private and Scalable Personal Data Analytics using Hybrid Edge-Cloud Deep Learning
Published in IEEE Computer, Special Issue on Mobile and Embedded Deep Learning, 2018
Distributed One-Class Learning
Published in 25th IEEE International Conference on Image Processing (ICIP), 2018
SCENE PRIVACY PROTECTION
Published in 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Published in ACM Conference on Computer and Communications Security (CCS), 2019
Exploiting vulnerabilities of deep neural networks for privacy protection
Published in IEEE Transactions On Multimedia (TMM), 2020
PrivEdge: From Local to Distributed Private Training and Prediction
Published in IEEE Transactions on Information Forensics and Security (TIFS), 2020
EdgeFool: An Adversarial Image Enhancement Filter
Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
DarkneTZ: Towards Model Privacy on the Edge using Trusted Execution Environments
Published in 18th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), 2020
ColorFool: Semantic Adversarial Colorization
Published in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances
Published in 46th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Semantically Adversarial Learnable Filters
Published in IEEE Transactions on Image Processing (TIP), 2021
A Zest of LIME: Towards Architecture-Independent Model Distances
Published in The 10th International Conference on Learning Representations (ICLR), 2022
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection
Published in 36th Conference on Neural Information Processing Systems (NeurIPS), 2022
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation
Published in 8th IEEE European Symposium on Security and Privacy (EuroS&P), 2023
When the curious abandon honesty: Federated learning is not private
Published in 8th IEEE European Symposium on Security and Privacy (EuroS&P), 2023
Private Multi-Label Classification
Published in the 23rd Privacy Enhancing Technologies symposium (PETs), 2023
Differentially Private Speaker Anonymization
Published in the 23rd Privacy Enhancing Technologies symposium (PETs), 2023
Losing Less: A Loss for Differentially Private Deep Learning
Published in the 23rd Privacy Enhancing Technologies symposium (PETs), 2023
Tubes Among Us: Analog Attack on Automatic Speaker Identification
Published in 32nd USENIX Security (USENIX Security), 2023
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation
Published in 32nd USENIX Security (USENIX Security), 2023
Confidential-PROFITT: Confidential PROof of FaIr Training of Trees
Published in 11th International Conference on Learning Representations (ICLR) notable top 5% of accepted papers , 2023
Mnemonist: Locating Model Parameters that Memorize Training Examples
Published in 39th Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Confidential-DPproof : Confidential Proof Of Differentially Private Training
Published in 12th International Conference on Learning Representations (ICLR) spotlight, top 5% , 2024
teaching
Neural Network
Postgraduate Course, Sharif University of Technology, Computer Engineering, 2016
Machine Learning
Postgraduate Course, Queen Mary University of London, Electrical Engineering and Computer Science, 2018
Lecturer: An Introduction to Trustworthy Machine Learning
Postgraduate Course, International Artificial Intelligence Doctoral Academy (AIDA), 2022
An Overview of Differential Privacy, Membership Inference Attacks, and Federated Learning
Seminar, University of Cambridge, 2023