A multi-generational social learning model: The effect of information cascade on aggregate welfare. - Marziyeh Barghandan; Mohammad Malekzadeh; Atefeh Safdel; Iren Mazloomzadeh (ASONAM, 2014)

Protecting Sensory Data against Sensitive Inferences. - Mohammad Malekzadeh; Richard G. Clegg; Andrea Cavallaro; Hamed Haddadi (P2DS@EuroSys, 2018)

Replacement AutoEncoder: A Privacy-Preserving Algorithm for Sensory Data Analysis. - Mohammad Malekzadeh; Richard G. Clegg; Hamed Haddadi (IoTDI, 2018)

Mobile sensor data anonymization. - Mohammad Malekzadeh; Richard G. Clegg; Andrea Cavallaro; Hamed Haddadi (IoTDI, 2019)

Modeling and Forecasting Art Movements with CGANs. - Edoardo Lisi; Mohammad Malekzadeh; Hamed Haddadi; F. Din-Houn Lau; Seth R. Flaxman (CoRR, 2019)

Privacy-Preserving Bandits. - Mohammad Malekzadeh; Dimitrios Athanasakis; Hamed Haddadi; Benjamin Livshits (MLSys, 2020)

Deep Learning for Privacy in Multimedia. - Andrea Cavallaro; Mohammad Malekzadeh; Ali Shahin Shamsabadi (ACM Multimedia, 2020)

Running Neural Networks on the NIC. - Giuseppe Siracusano; Salvator Galea; Davide Sanvito; Mohammad Malekzadeh; Hamed Haddadi; Gianni Antichi; Roberto Bifulco (CoRR, 2020)

Layer-wise Characterization of Latent Information Leakage in Federated Learning. - Fan Mo 004; Anastasia Borovykh; Mohammad Malekzadeh; Hamed Haddadi; Soteris Demetriou (CoRR, 2020)

Privacy and utility preserving sensor-data transformations. - Mohammad Malekzadeh; Richard G. Clegg; Andrea Cavallaro; Hamed Haddadi (Pervasive Mob. Comput., 2020)

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs. - Mohammad Malekzadeh; Anastasia Borovykh; Deniz Gündüz (CCS, 2021)

Dopamine: Differentially Private Federated Learning on Medical Data. - Mohammad Malekzadeh; Burak Hasircioglu; Nitish Mital; Kunal Katarya; Mehmet Emre Ozfatura; Deniz Gündüz (CoRR, 2021)

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs can be Secretly Coded into the Entropy of Classifiers' Outputs. - Mohammad Malekzadeh; Anastasia Borovykh; Deniz Gündüz (CoRR, 2021)

Quantifying Information Leakage from Gradients. - Fan Mo 004; Anastasia Borovykh; Mohammad Malekzadeh; Hamed Haddadi; Soteris Demetriou (CoRR, 2021)

Efficient Hyperparameter Optimization for Differentially Private Deep Learning. - Aman Priyanshu; Rakshit Naidu; Fatemehsadat Mireshghallah; Mohammad Malekzadeh (CoRR, 2021)

DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data. - Mohammad Malekzadeh; Richard G. Clegg; Andrea Cavallaro; Hamed Haddadi (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021)

Re-architecting Traffic Analysis with Neural Network Interface Cards. - Giuseppe Siracusano; Salvator Galea; Davide Sanvito; Mohammad Malekzadeh; Gianni Antichi; Paolo Costa; Hamed Haddadi; Roberto Bifulco (NSDI, 2022)

Centaur: Federated Learning for Constrained Edge Devices. - Fan Mo; Mohammad Malekzadeh; Soumyajit Chatterjee; Fahim Kawsar; Akhil Mathur (CoRR, 2022)

Vicious Classifiers: Data Reconstruction Attack at Inference Time. - Mohammad Malekzadeh; Deniz Gündüz (CoRR, 2022)

Latent Masking for Multimodal Self-supervised Learning in Health Timeseries. - Shohreh Deldari; Dimitris Spathis; Mohammad Malekzadeh; Fahim Kawsar; Flora D. Salim; Akhil Mathur (CoRR, 2023)

Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge Computing. - Mohammad Malekzadeh; Deniz Gündüz (BMVC Workshops, 2024)

Poster: Test-time Training for Sensor Data Classification via Time-series Change Identification. - Soumyajit Chatterjee; Fahim Kawsar; Mohammad Malekzadeh (HotMobile, 2024)

Salted Inference: Enhancing Privacy while Maintaining Efficiency of Split Inference in Mobile Computing. - Mohammad Malekzadeh; Fahim Kawsar (HotMobile, 2024)

CroSSL: Cross-modal Self-Supervised Learning for Time-series through Latent Masking. - Shohreh Deldari; Dimitris Spathis; Mohammad Malekzadeh; Fahim Kawsar; Flora D. Salim; Akhil Mathur (WSDM, 2024)

Deep Unlearn: Benchmarking Machine Unlearning. - Xavier F. Cadet; Anastasia Borovykh; Mohammad Malekzadeh; Sara Ahmadi-Abhari; Hamed Haddadi (CoRR, 2024)

Deep Unlearn: Benchmarking Machine Unlearning for Image Classification. - Xavier F. Cadet; Anastasia Borovykh; Mohammad Malekzadeh; Sara Ahmadi-Abhari; Hamed Haddadi (EuroS&P, 2025)

SoundCollage: Automated Discovery of New Classes in Audio Datasets. - Ryuhaerang Choi; Soumyajit Chatterjee; Dimitris Spathis; Sung-Ju Lee; Fahim Kawsar; Mohammad Malekzadeh (ICASSP, 2025)

PRimuS: Pretraining IMU Encoders with Multimodal Self-Supervision. - Arnav M. Das; Chi Ian Tang; Fahim Kawsar; Mohammad Malekzadeh (ICASSP, 2025)

PaPaGei: Open Foundation Models for Optical Physiological Signals. - Arvind Pillai; Dimitris Spathis; Fahim Kawsar; Mohammad Malekzadeh (ICLR, 2025)