Moninder Singh

81 papers A* 11A 4B 4C 2Misc 1Journal 32Unranked 27
YearRankTypeTitle / Venue / Authors
2026 J jnl
AI Steerability 360: A Toolkit for Steering Large Language Models.
CoRR
Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Irene Ko, Pierre L. Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney
2025 — conf
Conceptual Diagnostics for Knowledge Graphs and Large Language Models.
ACL (6)
Rosario Uceda-Sosa, Maria Chang, Karthikeyan Natesan Ramamurthy, Moninder Singh
2024 J jnl
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.
CoRR
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney
2024 J jnl
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.
IEEE Internet Comput.
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney
2024 — conf
Ranking Large Language Models without Ground Truth.
ACL (Findings)
Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy
2024 J jnl
Ranking Large Language Models without Ground Truth.
CoRR
Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy
2024 J jnl
Reasoning about concepts with LLMs: Inconsistencies abound.
CoRR
Rosario Uceda-Sosa, Karthikeyan Natesan Ramamurthy, Maria Chang, Moninder Singh
2024 A* conf
SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models.
AAAI
Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini
2023 J jnl
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions.
CoRR
Manish Nagireddy, Moninder Singh, Samuel C. Hoffman, Evaline Ju, Karthikeyan Natesan Ramamurthy, Kush R. Varshney
2023 J jnl
SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models.
CoRR
Manish Nagireddy, Lamogha Chiazor, Moninder Singh, Ioana Baldini
2022 A* conf
AI Explainability 360: Impact and Design.
AAAI
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2022 J jnl
Anomaly Attribution with Likelihood Compensation.
CoRR
Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe
2022 A* conf
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach.
NeurIPS
Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth Daly, Moninder Singh
2022 J jnl
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach.
CoRR
Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth M. Daly, Moninder Singh
2022 J jnl
Write It Like You See It: Detectable Differences in Clinical Notes By Race Lead To Differential Model Recommendations.
CoRR
Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi
2022 C conf
Write It Like You See It: Detectable Differences in Clinical Notes by Race Lead to Differential Model Recommendations.
AIES
Hammaad Adam, Ming-Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi
2022 — conf
Your fairness may vary: Pretrained language model fairness in toxic text classification.
ACL (Findings)
Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, Mikhail Yurochkin
2021 — conf
AI Explainability 360 Toolkit.
COMAD/CODS
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021 J jnl
AI Explainability 360: Impact and Design.
CoRR
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021 J jnl
An Empirical Study of Accuracy, Fairness, Explainability, Distributional Robustness, and Adversarial Robustness.
CoRR
Moninder Singh, Gevorg Ghalachyan, Kush R. Varshney, Reginald E. Bryant
2021 A* conf
Anomaly Attribution with Likelihood Compensation.
AAAI
Tsuyoshi Idé, Amit Dhurandhar, Jirí Navrátil, Moninder Singh, Naoki Abe
2021 J jnl
Ground-Truth, Whose Truth? - Examining the Challenges with Annotating Toxic Text Datasets.
CoRR
Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh
2021 — conf
Introduction to AI Fairness.
CHI Extended Abstracts
Yunfeng Zhang, Rachel K. E. Bellamy, Q. Vera Liao, Moninder Singh
2021 — conf
Introduction to Explainable AI.
CHI Extended Abstracts
Q. Vera Liao, Moninder Singh, Yunfeng Zhang, Rachel K. E. Bellamy
2021 J jnl
Your fairness may vary: Group fairness of pretrained language models in toxic text classification.
CoRR
Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Mikhail Yurochkin, Moninder Singh
2020 J jnl
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.
J. Mach. Learn. Res.
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020 — conf
AI explainability 360: hands-on tutorial.
FAT*
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020 — conf
Introduction to AI Fairness.
CHI Extended Abstracts
Yunfeng Zhang, Rachel K. E. Bellamy, Moninder Singh, Q. Vera Liao
2020 — conf
Introduction to Explainable AI.
CHI Extended Abstracts
Q. Vera Liao, Moninder Singh, Yunfeng Zhang, Rachel K. E. Bellamy
2019 J jnl
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias.
IBM J. Res. Dev.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2019 J jnl
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.
CoRR
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2019 A* conf
Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration.
IJCAI
Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi
2019 J jnl
Teaching AI agents ethical values using reinforcement learning and policy orchestration.
IBM J. Res. Dev.
Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi
2019 J jnl
Think Your Artificial Intelligence Software Is Fair? Think Again.
IEEE Softw.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2019 J jnl
Understanding racial bias in health using the Medical Expenditure Panel Survey data.
CoRR
Moninder Singh, Karthikeyan Natesan Ramamurthy
2018 J jnl
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.
CoRR
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2018 A* conf
Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search.
AAAI
Jonathan Galsurkar, Moninder Singh, Lingfei Wu, Aditya Vempaty, Mikhail Sushkov, Devika Iyer, Serge Kapto, Kush R. Varshney
2018 J jnl
Estimating Fungibility Between Skills by Combining Skill Similarities Obtained from Multiple Data Sources.
Data Sci. Eng.
Shrihari Vasudevan, Moninder Singh, Joydeep Mondal, Michael Peran, Benjamin Zweig, Brian Johnston, Rachel Rosenfeld
2018 J jnl
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration.
CoRR
Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi
2017 — conf
A configurable, big data system for on-demand healthcare cost prediction.
IEEE BigData
Karthikeyan Natesan Ramamurthy, Dennis Wei, Emily Ray, Moninder Singh, Vijay S. Iyengar, Dmitriy A. Katz-Rogozhnikov, Jingwei Yang, Kevin N. Tran, Gigi Y. Yuen-Reed
2017 J jnl
Effectiveness of peer detailing in a diarrhea program in Nigeria.
IBM J. Res. Dev.
Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Jan Houdek, M. Abubakar, Abdulwahab Alharbi, Tiwadayo Braimoh, N. Ihebuzor, Aleksandra Mojsilovic, Kush R. Varshney
2017 — conf
Estimating Fungibility Between Skills by Combining Skill-Similarities Obtained from Multiple Data Sources.
ICDM Workshops
Shrihari Vasudevan, Moninder Singh, Joydeep Mondal, Michael Peran, Ben Zweig, Brian Johnston, Rachel Rosenfeld
2017 — conf
Propensity modeling for employee Re-skilling.
GlobalSIP
Moninder Singh, Karthikeyan Natesan Ramamurthy, Shrihari Vasudevan
2017 — conf
Statistical Analysis of Peer Detailing for Children's Diarrhea Treatments.
AAAI Spring Symposia
Yumeng Tao, Debarun Bhattacharjya, Aliza R. Heching, Aditya Vempaty, Moninder Singh, Felix Lam, Kush R. Varshney, Aleksandra Mojsilovic
2017 J jnl
Understanding the ecospace of philanthropic projects.
IBM J. Res. Dev.
H. Lamba, M. E. Helander, Moninder Singh, N. Lethif, Achyutram Bhamidipaty, S. A. Baset, Aleksandra Mojsilovic, Kush R. Varshney
2015 B conf
A talent management tool using propensity to leave analytics.
DSAA
Karthikeyan Natesan Ramamurthy, Moninder Singh, Yichong Yu, Jessica Aspis, Matthew Iames, Michael Peran, Qin S. Held
2015 — conf
Identifying Employees for Re-skilling Using an Analytics-Based Approach.
ICDM Workshops
Karthikeyan Natesan Ramamurthy, Moninder Singh, Michael Davis, J. Alex Kevern, Uri Klein, Michael Peran
2013 J jnl
An Algorithm for the Construction of Bayesian Network Structures from Data
CoRR
Moninder Singh, Marco Valtorta
2013 — conf
Quantile regression for workforce analytics.
GlobalSIP
Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Moninder Singh
2012 — conf
An Analytics Approach for Proactively Combating Voluntary Attrition of Employees.
ICDM Workshops
Moninder Singh, Kush R. Varshney, Jun Wang, Aleksandra Mojsilovic, Alisia R. Gill, Patricia I. Faur, Raphael Ezry
2012 — conf
Decision trees for heterogeneous dose-response signal analysis.
SSP
Kush R. Varshney, Moninder Singh, Jun Wang
2012 — conf
Does selection bias blind performance diagnostics of business decision models? A case study in salesforce optimization.
SOLI
Jun Wang, Moninder Singh, Kush R. Varshney
2012 C conf
Interactive Visual Salesforce Analytics.
ICIS
Kush R. Varshney, Jamie C. Rasmussen, Aleksandra Mojsilovic, Moninder Singh, Joan Morris DiMicco
2012 J jnl
Sales-force performance analytics and optimization.
IBM J. Res. Dev.
Moritz Baier, Jorge E. Carballo, Alice J. Chang, Yingdong Lu, Aleksandra Mojsilovic, M. Jonathan Richard, Moninder Singh, Mark S. Squillante, Kush R. Varshney
2011 — conf
Estimating Post-Event Seller Productivity Profiles in Dynamic Sales Organizations.
ICDM Workshops
Kush R. Varshney, Moninder Singh, Mayank Sharma, Aleksandra Mojsilovic
2011 Misc conf
MCMC inference of the shape and variability of time-response signals.
ICASSP
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Aleksandra Mojsilovic, Moninder Singh
2009 — conf
A framework for combined bayesian analysis and optimization for services delivery.
SOLI
Afsaneh Shirazi, Jianying Hu, Moninder Singh, Mark S. Squillante, Aleksandra Mojsilovic
2009 — conf
Winning the KDD Cup Orange Challenge with Ensemble Selection.
KDD Cup
Alexandru Niculescu-Mizil, Claudia Perlich, Grzegorz Swirszcz, Vikas Sindhwani, Yan Liu, Prem Melville, Dong Wang, Jing Xiao, Jianying Hu, Moninder Singh, Wei Xiong Shang, Yanfeng Zhu
2008 B conf
Categorization using semi-supervised clustering.
ICPR
Jianying Hu, Moninder Singh, Aleksandra Mojsilovic
2008 B conf
K-means clustering of proportional data using L1 distance.
ICPR
Hisashi Kashima, Jianying Hu, Bonnie K. Ray, Moninder Singh
2007 J jnl
Statistical methods for automated generation of service engagement staffing plans.
IBM J. Res. Dev.
Jianying Hu, Bonnie K. Ray, Moninder Singh
2005 A conf
Automated cleansing for spend analytics.
CIKM
Moninder Singh, Jayant Kalagnanam, Sudhir Verma, Amit J. Shah, Swaroop K. Chalasani
2004 A* conf
A system for automated mapping of bill-of-materials part numbers.
KDD
Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong
2004 J jnl
Data Protection and Data Sharing in Telematics.
Mob. Networks Appl.
Sastry Duri, Jeffrey Elliott, Marco Gruteser, Xuan Liu, Paul Moskowitz, Ronald Perez, Moninder Singh, Jung-Mu Tang
2003 — conf
Object Oriented XML Query by Example.
ER (Workshops)
Kathy Bohrer, Xuan Liu, Sean McLaughlin, Edith Schonberg, Moninder Singh
2002 J jnl
An architecture of diversity for commonsense reasoning.
IBM Syst. J.
John McCarthy, Marvin Minsky, Aaron Sloman, Leiguang Gong, Tessa A. Lau, Leora Morgenstern, Erik T. Mueller, Doug Riecken, Moninder Singh, Push Singh
2002 — conf
Framework for security and privacy in automotive telematics.
Workshop Mobile Commerce
Sastry Duri, Marco Gruteser, Xuan Liu, Paul Moskowitz, Ronald Perez, Moninder Singh, Jung-Mu Tang
2000 A conf
Algebra jam: supporting teamwork and managing roles in a collaborative learning environment.
CSCW
Mark K. Singley, Moninder Singh, Peter G. Fairweather, Robert G. Farrell, Steven Swerling
1997 — conf
An Expert System Using Nonmonotonic Techniques for Beneefits Inquiry in the Insurance Industry.
IJCAI (1)
Leora Morgenstern, Moninder Singh
1997 — conf
Learning Bayesian Networks from Incomplete Data.
AAAI/IAAI
Moninder Singh
1996 A* conf
Data Mining and Model Simplicity: A Case Study in Diagnosis.
KDD
Gregory M. Provan, Moninder Singh
1996 — conf
Dynamic Constraint-Based Planning in Trauma Management.
AAAI/IAAI, Vol. 2
Moninder Singh
1996 A* conf
Efficient Learning of Selective Bayesian Network Classifiers.
ICML
Moninder Singh, Gregory M. Provan
1996 — conf
Induction of Selective Bayesian Networks from Data.
AAAI/IAAI, Vol. 2
Moninder Singh
1996 A* conf
Learning Goal Oriented Bayesian Networks for Telecommunications Risk Management.
ICML
Kazuo J. Ezawa, Moninder Singh, Steven W. Norton
1996 J jnl
Path Consistency Revisited.
Int. J. Artif. Intell. Tools
Moninder Singh
1995 A* conf
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers.
ICML
Moninder Singh, Gregory M. Provan
1995 J jnl
Construction of Bayesian network structures from data: A brief survey and an efficient algorithm.
Int. J. Approx. Reason.
Moninder Singh, Marco Valtorta
1995 A conf
Learning Bayesian Networks Using Feature Selection.
AISTATS
Gregory M. Provan, Moninder Singh
1995 B conf
Path consistency revisited.
ICTAI
Moninder Singh
1993 A conf
An Algorithm for the Construction of Bayesian Network Structures from Data.
UAI
Moninder Singh, Marco Valtorta