Pranay Lohia

Microsoft Research (United Kingdom) — United Kingdom

Social Sciences · Social Sciences

10h-index1.7kcitations27works1.02yr avg
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Research Topics

Ethics and Social Impacts of AI(7), Explainable Artificial Intelligence (XAI)(7), Anomaly Detection Techniques and Applications(6), Adversarial Robustness in Machine Learning(5), Scientific Computing and Data Management(5)

Publications27 total

High Significant Fault Detection in Azure Core Workload Insights
arXiv (Cornell University)·2024Open Access
High Significant Fault Detection in Azure Core Workload Insights
Proceedings of the AAAI Conference on Artificial Intelligence·2024· 2 citedOpen Access
SPASE: Spatial Saliency Explanation For Time Series Models
2024· 1 cited
SPASE: SPAtial Saliency Explanation for time series models in Microsoft Azure products
Research Square (Research Square)·2023Open Access
Beyond Fairness: Reparative Algorithms to Address Historical Injustices of Housing Discrimination in the US
2022 ACM Conference on Fairness, Accountability, and Transparency·2022· 28 citedOpen Access
Counterfactual Multi-Token Fairness in Text Classification
arXiv (Cornell University)·2022· 2 citedOpen Access
Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets
arXiv (Cornell University)·2021· 21 citedOpen Access
Priority-based Post-Processing Bias Mitigation for Individual and Group Fairness
arXiv (Cornell University)·2021· 3 citedOpen Access
Ranking Marginal Influencers in a Target-labeled Network
2020· 2 cited
Design diagrams as ontological source
2019
Black box fairness testing of machine learning models
2019· 177 cited
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
IBM Journal of Research and Development·2019· 747 cited
On Efficiently Processing Workflow Provenance Queries in Spark
2019· 4 cited
Think Your Artificial Intelligence Software Is Fair? Think Again
IEEE Software·2019· 35 cited
Bias Mitigation Post-processing for Individual and Group Fairness
2019· 113 cited
Bias Mitigation Post-processing for Individual and Group Fairness
arXiv (Cornell University)·2018· 3 citedOpen Access
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
arXiv (Cornell University)·2018· 265 citedOpen Access
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and\n Mitigating Unwanted Algorithmic Bias
arXiv (Cornell University)·2018· 259 citedOpen Access
Automated Test Generation to Detect Individual Discrimination in AI Models
arXiv (Cornell University)·2018· 24 citedOpen Access
Efficiently Processing Workflow Provenance Queries on SPARK
arXiv (Cornell University)·2018Open Access
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Frequent Co-authors

Diptikalyan Saha(10), Sameep Mehta(9), Kuntal Dey(6), Kalapriya Kannan(6), Karthikeyan Natesan Ramamurthy(6), Kush R. Varshney(6), Seema Nagar(5), Rachel Bellamy(4), Michael Hind(4), Samuel C. Hoffman(4), Stephanie Houde(4), Prasanna Sattigeri(4), Vijay Srinivas Agneeswaran(4), Aleksandra Mojsilović(3), John T. Richards(3), Moninder Singh(3), Naveen Panwar(3), Rema Ananthanarayanan(3), Srikanta Bedathur(3), Himanshu Gupta(3)