Nidhi Hegde


I'm an Associate Professor in the department of Computing Science at the University of Alberta, Edmonton, Canada, and a PI at Amii.

My research interests are in probabilistic modelling and algorithmic design of machine learning for networked and multi-agent systems, and inference under bias and privacy constraints.

My current focus is on privacy, and fairness and bias in machine learning.

Publications (dblp, Google scholar)

Short Bio

Most recently I was a Research team lead at Borealis AI (a research institute at Royal Bank of Canada), where my team worked on privacy-preserving methods for machine learning models and other applied problems for RBC.

Prior to that I spent many years in industry research labs working on a variety of interesting and impactful problem. I was a researcher at Bell Labs, Nokia, in France from January 2015 to March 2018, where I was leading a new team focussed on Maths and Algorithms for Machine Learning in Networks and Systems, in the Maths and Algorithms group of Bell Labs. Before that I spent a few years at the Technicolor Paris Research Lab working on social network analysis, smart grids, privacy, and recommendations. And even before that I was at France Telecom (now Orange) R&D in Jim Robert's Performance analysis group working on scheduling and resource allocation. I also spent some years at CWI and Eurandom in the Netherlands, and at INRIA at Sophia Antipolis, France as a postdoc.

Associate Professor, Department of Computing SciencePI at AmiiUniversity of AlbertaEdmonton, AB, Canada