I am a Senior Lecturer (~Associate Professor) and the the Director of Postgraduate Studies in the Dyson School of Design Engineering, at The Faculty of Engineering at Imperial College London. I am also a Visiting Professor at Brave.
My research interest are in User-Centered Systems, IoT, Applied Machine Learning, Privacy, and Human-Data Interaction. At Imperial College, I lead the Systems and Algorithms Laboratory (SysAl). I am also an Academic Fellow of the Data Science Institute as a member of the Algorithmic Society Lab. As part of the Institute for Security Science and Technology (ISST), I am an Associate member of the Academic Centre of Excellence in Cyber Security Research.
PhD Scholarship: We currently have a fully-funded PhD studentship (fees and stipend) in the intersection of machine learning and cyber-physical systems (sensing, privacy, and IoT) for UK/EU students. Please see the advert an get in touch if interested
I am keen to hear from strong students interested in doing their masters project or PhD research with me, or postdoctoral fellows interested in being hosted at Imperial College London. Please get in touch!
We are currently looking for exceptional candidates for the Imperial College Research Fellowships, the Imperial President’s PhD Scholarships, China Scholarship Council, the Islamic Development Bank – Imperial College Scholarship, UKRI AI for Healthcare CDT, the London Interdisciplinary Social Science Doctoral Training Partnership (LISS DTP), and various other Scholarships and Centres for Doctoral Training in Imperial College London.
Septempber 2019: I participated in preperaing the government’s Centre for Data Ethics and Innovation first series of three snapshot papers on ethical issues in AI including Smart Speakers and Voice Assistants.
August 2019: At Brave, we have released Privacy-Preserving Product Analytics (P3A). Exciting to see our platform ship to millions of users worldwide this year.
August 2019: Ranya’s paper “Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants”, appearing in ACM CCS 2019 Privacy Preserving Machine Learning workshop, has been covered in articles on Vice and Medium.
July 2019: Our study of IoT devices, “Information Exposure From Consumer IoT Devices: A Multidimensional, Network-Informed Measurement Approach” has been accepted to ACM Internet Measurement Conference (IMC 2019). (paper and code and dataset, Financial Times article, The Times article, Vice article, Ars Technica)
July 2019: We are Building Systems for Privacy-Preserving Data Analytics, Machine Learning, and behavioural interaction systems, as part of the newly funded £20M new Care Research & Technology Centre at Imperial College. Read about it here on the FT: How smart tech is helping people with dementia
June 2019: The first evolution of Databox Project is released as the BBC Box. We are really excited about this development and its potential to improve individuals’ privacy. This is part of the Personal Data Stewardship project at the BBC R&D. (Also on BBC News, Gizmodo )
April 2019: Congratulations to Katrin Hänsel for having passed her PhD viva!
March 2019: Our paper “Deep Learning in Mobile and Wireless Networking: A Survey”, has been accepted to appear in IEEE Communications Surveys & Tutorials. (Paper Available on ArXiv)
Jan 2019: We are part of the new £20m UK DRI Care Research & Technology programme, developing privacy-preserving technologies for demantia patients over the next six years. Job ads will be out soon!
December 2018: Our article “Decentralised AI has the potential to upend the online economy” has been published in Wired.
December 2018: Databox Project has been featured as a case study at the Royal Academy of Engineering report “Towards trusted data sharing: guidance and case studies”.
October 2018: Our paper “Deep Private-Feature Extraction” has been accepted to IEEE Transactions on Knowledge and Data Engineering.
August 2018: We have received a generous grant from Huawei Technologies. Stay Tuned for the job advert!
March 2018: Our EPSRC Digital Economy NetworkPlus grant on Human-Data Interaction has been funded! Watch out for announcements regarding events and calls for projects in this space. (EPSRC Ref, Press Release)
Feb 2018: Our paper “Private and Scalable Personal Data Analytics using a Hybrid Edge-Cloud Deep Learning” with Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, and Hamid R. Rabiee has been accepted to the IEEE Computer Magazine Special Issue on Mobile and Embedded Deep Learning.
Jan 2018: Two papers on privacy in IoT applications have been accepted to the ACM/IEEE International Conference on Internet-of-Things Design and Implementation 2018. See publications’ page for details.