I am a second-year PhD candidate at the Dyson School of Design Engineering, at Imperial College London. My primary research interests are Internet of Things (IoT), Deep Learning, Privacy, and their intersection. In particular, I am interested in preserving privacy in IoT. Recently I have been interested in preventing companies from collecting emotion data about users from voice-controlled applications.
In 2018, I received my Master’s degree in advanced computer science from the University of Leicester with distinction. During my graduate studies, I received intensive courses using Java programming in how to deal with concurrent and distributed systems (e.g., threads and RMI) and look at the primary models and principles behind the development of distributed applications.
- Paralinguistic Privacy Protection at the Edge (Paper), ArXiv 2020
- Privacy-preserving Voice Analysis via Disentangled Representations (Paper, Code), CCSW'20: Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security Workshop, CCS 2020
- Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants (Paper, Code, vice, medium), PPML: Privacy Preserving Machine Learning Workshop, CCS 2019
- Emotion Filtering at the Edge (Paper, Code), SenSys-ML 2019 Proceedings of the 1st Workshop on Machine Learning on Edge in Sensor Systems, SenSys 2019
- Poster: Privacy preserving speech analysis using emotion filtering at the edge, 17th ACM Conference on Embedded Networked Sensor Systems, SenSys 2019
- (2019) Awarded Black Hat Europe Student Scholarship
- (2019) Awarded Best Poster at ACM SenSys/BuildSys
- (2019) Awarded ACM SenSys/BuildSys Travel Grant