Dr. Mohammad Malekzadeh

Mohammad Malekzadeh received his B.Eng. degree in Computer Engineering (Software) from Shahid Chamran University of Ahvaz in 2008, and M.Sc. degree in Information Technology (Networks) from Sharif University of Technology in 2011.  He worked for Persian Gulf University in Iran as a Lecturer in Computer Engineering as well as the Manager of the ICT Institute of Persian Gulf University, from 2012 to 2016. He, started his PhD in Computer Science as a member of Centre for Intelligent Sensing in the School of Electronic Engineering and Computer Science at Queen Mary University of London, in 2017.  His Ph.D. research focuses on privacy-preserving machine learning mechanisms for temporal data analysis, particularly for time-series data generated by the mobile and wearable devices. During the course of his PhD studies, he has completed two internships on the subject of privacy-preserving data sharing, one in Databox Project at Imperial College London, 2018, and one in the Brave Software Research in London, 2019. Currently, he is a Research Assistant at Information Processing and Communications Lab at Imperial College London working on reliable and privacy-preserving federated learning on the edge devices. Mohammad serves as a reviewer for Nature Communications, World Wide Web Journal, The Web Conference, and Symposium on Experimental Algorithms. 

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  • M. Malekzadeh, R. G. Clegg, A. Cavallaro, and H. Haddadi. “Privacy and Utility Preserving Sensor Data Transformations. Pervasive and Mobile Computing, Elsevier, Volume 63, Article 101132, 2020.
  • M. Malekzadeh, D. Athanasakis, H. Haddadi, and B. Livshits. “Privacy-Preserving Bandits”. In Proceedings of the Conference on Machine Learning and Systems (MLSys), March, 2020, Huston, Texas, USA.
  • L. Edoardo, M. Malekzadeh, H. Haddadi, F. Din-Houn Lau, and S. Flaxman. “Modelling and forecasting art movements with CGANs”. Royal Society Open Science 7, no. 4 (2020): 191569.
  • M. Malekzadeh, R. G. Clegg, A. Cavallaro, and H. Haddadi. “Mobile Sensor Data Anonymization”. In Proceedings of the IEEE/ACM International Conference on Internet of Things Design and Implementation (IoTDI), April, 2019, Montreal, Canada. 
  • S. M. Malekzadeh, R. G. Clegg, A. Cavallaro, and H. Haddadi. “Protecting Sensory Data Against Sensitive Inferences”. In Proceedings of the 1st ACM Workshop on Privacy by Design in Distributed Systems (W-P2DS), February, 2018, Porto, Portugal.
  • E. M. Malekzadeh, R. G. Clegg, and H. Haddadi. “Replacement Autoencoder: A Privacy-Preserving Algorithm for Sensory Data Analysis”. In Proceedings of the IEEE/ACM International Conference on Internet-of-Things Design and Implementation (IoTDI), April, 2018, Orlando, Florida, USA.
  • R. Gharibi,  M. Malekzadeh. Gamified Incentives: “A Badge Recommendation Model to Improve User Engagement in Social Media Sites”. International Journal of Advanced Computer Science and Applications 8(5), 2017.
  • M. Barghandan, M. Malekzadeh, A. Safdel, and I. Mazloomzadeh. “A multi-generational social learning model: The effect of information cascade on aggregate welfare”. In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), pp. 529-533. IEEE, 2014.
  • M., Malekzadeh, M., Fazli, P.J., Khalilabadi,  H.R. Rabiee, and M., Safari. “Social balance and signed network formation games”. In Proceedings of KDD workshop on Social Network Analysis (SNA-KDD), 2011, August.
  • N. M. Malekzadeh and M. Bohlool. “Persian CAPTCHA System to Prevent Automatic Subscribing of Software Robots in Web Pages”. 13th National CSI Computer Science, Kish, Iran, 2008.