Kirandeep Kaur

PhD in Computer Science

kaur13 [AT]


Hi! I am a first-year PhD student at the Paul G. Allen School of Computer Science, University of Washington. I am associated with Infoseeking Lab, RAISE and advised by Chirag Shah. My research interests span building lawful, ethical and privacy-preserving machine learning models for societal good. I also like to work on understanding and mitigating various challenges in democratising AI. I am fortunate to be supported by Microsoft Endowed Fellowship.

Before joining PhD, I was a research intern at the Responsible AI group, MPI-SP, where I worked under the supervision of Asia Biega at the intersection of GDPR's Data Minimization Principle and Federated Learning. I completed my Master's in Computer Science & Engineering at IIT, Ropar, and was extremely fortunate to be advised by Shweta Jain and Sujit Gujar. I will always be thankful to them for being my first mentors, introducing me to research and guiding me throughout my journey to PhD. My Master's thesis aimed at improving fairness and communication efficiency in Federated Recommendation Systems.


Most recent publications on Google Scholar.

Towards Efficient Adaptation of LLMs for Robust and Fair Recommendations

Kirandeep Kaur, Chirag Shah

Evaluating Demographic Disparity in Computational Interpretations of GDPRs Data Minimization Principle in Two-Sided Online Platforms

Kirandeep Kaur, Athina Kyriakou, Andrew Zhang, Anthony Wise, Franziska Roesner, Chirag Shah

Investigating the Importance of Data Minimization under the Federated Learning Paradigm

Kirandeep Kaur, Alessandro Fabris, Asia Biega

Towards Fairness in Provably Communication Efficient Federated Recommendation Systems

Kirandeep Kaur, Sujit Gujar, Shweta Jain

EqBal-RS: Mitigating Popularity Bias in Recommendation Systems

Shivam Gupta, Kirandeep Kaur, Shweta Jain

Journal of Intelligent Information Systems. 2023.

Improving the Resolution of Protein Structure Imaging

Mustafa Arikan, Dan Burrows, Kirandeep Kaur, Osian Shelley, Nayef Shkeir, Jesse Spielman, Lorenzo Toniazzi, Xiaochen Yang, Naya Yerolemou, Kit Windows-Yule, Leonard Nicusan

Data Study Group Report, Alan Turing Institute,UK.


Battle of Neighborhoods
Clustering based Recommender System for House Recommendations.
Lion in Mazeworld
A Game Model Environment for navigation.
The 8 Queen Puzzle
Implementation of 8 Queen Chess Problem using Genetic Algorithm.
Wordoku AI Agent
AI Agent to solve Wordoku puzzle using Constraint Satisfaction Problem.
XMen Game
Markov Decision PRocess based Implementation.
Intelligent Fake News Reasoner
A Reasoner based on Description Logic and Fuzzy Logic.
Text Recognition
A Neural Network-Based Model.


Full Resume in PDF.