Updates

2022

October 2022

I was invited to give a remote talk about privacy-preserving machine learning on graphs for the course “Socially Responsible AI” by Lu Cheng at University of Illinois at Chicago. The slides are available here.

August 2022

I was invited to give a remote talk about our work “GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation” at L3S Research Center. The slides can be downloaded from here.

March 2022

I started my research internship at Brave Software working on decentralized privacy-preserving machine learning for ads and news recommendation.

2021

July 2021

I was invited to give a talk about our work “Locally Private Graph Neural Networks” at Graph Neural Networks User Group Meetup run by Amazon Web Services and NVIDIA AI. The recording is available on Youtube and the slides can be downloaded from here.

June 2021

I presented our recent CCS paper “Locally Private Graph Neural Networks” at AI4Media Workshop on Explainability, Robustness and Privacy in AI. Slides can be downloaded from here.

January 2021

I delivered a remote talk on our recent work, “Locally Private Graph Neural Networks” at Twitter Machine Learning Seminar. You can download the slides from here.

2020

June 2020

Our recent paper on integrating differential privacy with graph neural networks is out! Check it out on arXiv.

May 2020

I successfully passed my PhD candidacy examination!

2019

May 2019

I started as a research assistant at the Social Computing group in Idiap Research Institute, Martigny, Switzerland.

February 2019

I was offered a PhD admission to the electrical engineering program at EPFL.

2018

2017

2016

2014