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IADS PhD Student Forum Webinar: "Privacy-Preserving Machine Learning on Distributed Data" with Dr Mohammad Malekzadeh

Date: 11 May 2021   Time: 11:00 - 12:00

The next talk of the IADS PhD forum seminars will be by Dr Mohammad Malekzadeh. Mohammad will talk about privacy preserving machine learning. Privacy is one of the trending topics in machine learning research and we're sure many of you will find this talk interesting. Please don't forget to attend! This will take place on the 11th of May at 11 am on this Zoom link. You can add this talk and the rest of the forum events to your calendar from here.

Please contact one of the organisers if you are interested to present your research at future IADS PhD forum seminars. We also have a nomination form, if you are interested to nominate someone you know please fill the form and we'll contact them.

Title: Privacy-Preserving Machine Learning on Distributed Data

Abstract: While rich datasets are hosted in distributed environments, concerns on data owners' privacy are a barrier against utilizing such data to train and utilize machine learning models for automated services. For instance, behavioral patterns observed in data generated by users' devices are used by many applications, such as wellness monitoring or service personalization. However, sensitive information may be inferred from these data when they are shared with cloud-based services. In this talk, we discuss the design and evaluation of machine learning algorithms that allow the inference of information required for desired services while preventing the inference of privacy-sensitive information.

Bio: Mohammad Malekzadeh is a postdoctoral researcher in Information Processing and Communications Lab at Imperial College London where he works on privacy-preserving machine learning in distributed environments. He studied for his Ph.D. in computer science at EECS Centre for Intelligent Sensing at Queen Mary University of London. His Ph.D. thesis was on privacy-preserving machine learning algorithms for behavioral data analysis, particularly for time-series data generated by mobile and wearable devices. More information about his background and recent work can be found at https://mmalekzadeh.github.io/

PhD forum Slack and mailing list.

Saeid Ghafouri (s.ghafouri@qmul.ac.uk)

Hanlin Sun (hanlin.sun@qmul.ac.uk)

Lucille Calmon (m.l.calmon@qmul.ac.uk)

Location:  Webinar via Zoom
Contact:  Saeid Ghafouri
Email:  s.ghafouri@qmul.ac.uk