Research Interests
My research can be categorised in the following two broad themes:Developing systems and mechanisms that empower individuals by providing control over their data. Specifically, I work on addressing the emergent challenges in such systems (e.g., scalability, incentive alignment, data quality, representation, and fairness).
Developing human-centred AI systems. Specifically, I investigate how various human, organizational and social factors interact with AI systems, with particular attention on outcomes that may be undesired by different stakeholders. I also work on mitigating these issues, through interventions at different stages of the AI pipeline.
Preprints/Working Papers
On The Truthfulness of 'Surprisingly Likely' Responses of Large Language Models
Naman Goel
[Paper]Decentralised, Scalable and Privacy-Preserving Synthetic Data Generation
Vishal Ramesh, Rui Zhao, Naman Goel
[Paper][Code]Libertas: Privacy-Preserving Computation for Decentralised Personal Data Stores
Rui Zhao, Naman Goel, Nitin Agrawal, ..., Tim Berners-Lee, Nigel Shadbolt
[Paper][Code]Whose Preferences? Differences in Fairness Preferences and Their Impact on the Fairness of AI Utilizing Human Feedback
Emilia Agis Lerner, Florian Dorner, Elliott Ash, Naman Goel
[Paper][Code][Data]FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition
Dalia Gala, Milo Phillips-Brown, Naman Goel, ..., Ray Eitel-Porter
[Paper][Demo][Video][Code]
Publications
SocialGenPod: Privacy-Friendly Generative AI Social Web Applications with Decentralised Personal Data Stores
(Forthcoming) Companion Proceedings of the ACM Web Conference, TheWebConf (WWW) 2024. (Demonstration)
Vidminas Vizgirda, Rui Zhao, Naman Goel
[Paper][Code]WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
Proceedings of the 37th Conference on Neural Information Processing Systems, NeurIPS, 2023.
Elliott Ash*, Naman Goel*, Nianyun Li*, Claudia Marangon*, Peiyao Sun*
[Paper][Data][Poster][Video]Human-Guided Fair Classification for Natural Language Processing
Proceedings of the International Conference on Learning Representations, ICLR, 2023.
Florian Dorner, Momchil Peychev, Nikola Konstantinov, Naman Goel, Elliott Ash, Martin Vechev
[Paper][Poster][Code][Video]
Notable Top 25% Incentive Mechanism Design for Responsible Data Governance: A Large Scale Field Experiment
ACM Journal of Data and Information Quality, ACM JDIQ 2023.
Christina Timko, Malte Niederstadt, Naman Goel, Boi Faltings
[Paper][Code and Data]'You are you and the app. There’s nobody else.': Building Worker-Designed Data Institutions within Platform Hegemony
Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, CHI, 2023.
Jake Stein, Vidminas Vizgirda, ..., Naman Goel, ..., Nigel Shadbolt
[Paper][Video]Nianyun Li, Naman Goel, Elliott Ash
Data-Centric Factors in Algorithmic Fairness
Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics and Society, AAAI/ACM AIES, 2022.
[Paper][Poster][Video]Naman Goel, Alfonso Amayuelas, Amit Deshpande, Amit Sharma
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective
Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI, 2021.
[Paper][Poster][Supplementary Material][10 min Video][15 min Video][30 min Video]Naman Goel
Truthful, Transparent and Fair Data Collection Mechanisms
PhD Thesis, EPFL, 2020.
[Thesis]Naman Goel*, Cyril van Schreven*, Aris Filos-Ratsikas, Boi Faltings
Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain
Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI, 2020.
[Paper][Poster][Medium Blog][Short Video][Long Video]Naman Goel, Aris Filos-Ratsikas, Boi Faltings
Peer-Prediction in the Presence of Outcome Dependent Lying Incentives
Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI, 2020.
[Paper][Poster][Short Video][Long Video]Naman Goel, Maxime Rutagarama, Boi Faltings
Tackling Peer-to-Peer Discrimination in the Sharing Economy
Proceedings of the 12th ACM Web Science Conference, ACM WebSci, 2020.
[Paper][Video]
Best Paper Award Naman Goel, Boi Faltings
Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data
Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, UAI, 2019.
[Paper][Poster][Short Video]Naman Goel, Boi Faltings
Deep Bayesian Trust: A Dominant and Fair Incentive Mechanism for Crowd
Proceedings of the 33rd AAAI Conference on Artificial Intelligence, AAAI, 2019.
[Paper][Supplementary Material][Poster]Naman Goel, Boi Faltings
Crowdsourcing with Fairness, Diversity and Budget Constraints
Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics and Society, AAAI/ACM AIES, 2019.
[Paper][Poster]Naman Goel, Mohammad Yaghini, Boi Faltings
Non-Discriminatory Machine Learning through Convex Fairness Criteria
Proceedings of the 32nd AAAI Conference on Artificial Intelligence, AAAI, 2018.
[Paper][Poster]DA Waguih, Naman Goel, HM Hammady, L Berti-Equille
AllegatorTrack: Combining and reporting results of truth discovery from multi-source data
Proceedings of the 31st IEEE International Conference on Data Engineering, ICDE, 2015. (Demonstration)
[Paper][Code][Demo]Naman Goel, Divyakant Agrawal, Sanjay Chawla, Ahmed Elmagarmid
Parameter Database: Data-centric Synchronization for Scalable Machine Learning
QCRI Technical Report, 2015.
[Paper]