Mohammad Malekzadeh

Previously, I was a Senior Research Scientist at Nokia Bell Labs, and I led the Device Intelligence team in the Pervasive Systems department. In our team, we developed machine learning solutions for private data and personal devices. Our mission was to advance research and development in personalized healthcare applications through multimodal sensing and on-device machine learning. In our solutions, we prioritize multi-modality, data and compute efficiency, individual privacy, and personalization. We brought together leading research scientists, brilliant PhD interns and visitors, as well as expert collaborators to drive innovations that elevate human well-being. Explore our latest research papers and open-source code: CLEF, PaPaGei, CroSSL, PRIMUS, AdaBet, SoundCollage, Centaur, and Salted DNNs.

Before that, I was a Research Associate at Imperial College London, collaborating with Prof. Deniz Gunduz on Privacy-Preserving and Trustworthy Machine Learning. I earned my PhD in Computer Science at Queen Mary University of London while concurrently holding a Research Assistant position at Imperial College London. I had the opportunity to work with Prof. Hamed Haddadi, Dr. Richard G. Clegg, and Prof. Andrea Cavallaro. My PhD research focused on developing machine learning algorithms for privacy-preserving personal data analytics, particularly for data captured by mobile and wearable devices. During my PhD, I also interned at Brave Software Research, where I explored privacy-preserving techniques to enhance content personalization.