Dr. Razane Tajeddine received her B.Sc. in Electrical Engineering from Notre Dame University-Louaize, Faculty of Engineering, Lebanon, in 2012, and her M.Sc. in Electrical and Computer Engineering from the American University of Beirut, Lebanon, in 2014. She received her doctorate degree from the department of Mathematics and Systems Analysis at Aalto University in 2019. From 2014 to 2017, she was a PhD student at the Electrical and Computer Engineering Department at the Illinois Institute of Technology. In 2016, she came for a research visit to Aalto University to work in collaboration with the ANTA group. She was invited to the Algebraic Coding Theory for Networks, Storage, and Security, Dagstuhl in December 2018 and to the Oberwolfach Workshop on Contemporary Coding Theory, Leibniz in March 2019. Currently, Tajeddine is working as an HIIT Postdoctoral Fellow at the University of Helsinki.
Tajeddine’s research focuses on developing effective privacy preserving methods for machine learning, mainly where data is partitioned between multiple parties. Her doctoral research focused on private information retrieval (PIR), where schemes were developed to allow users to retrieve a file from a distributed storage system without revealing what file is being retrieved.
During the year 2020, Tajeddine published a preprint [1] for the work on private data sharing on vertically partitioned data, and presented the work as a poster in the AI day 2020.
Publications in 2020:
[1] Razane Tajeddine, Joonas Jälkö, Sami Kaski, Antti Honkela. Privacy-preserving data sharing on vertically partitioned data. ArXiv preprint, 2020.