Kush R. Varshney
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
79
Venues
29
Active years
2008–2026
Best venue rank
A*
Where they publish
- MulticonferenceICASSP14 papers
- A*AAAI9 papers
- CAIES9 papers
- A*IJCAI5 papers
- A*ICML4 papers
- A*KDD4 papers
- A*ICDM4 papers
- A*ACL2 papers
- ANAACL2 papers
- A*ICLR2 papers
- NationalCOMAD2 papers
- NationalAMIA2 papers
- NationalCISS2 papers
- NationalITA2 papers
- ASDM2 papers
- A*EMNLP1 paper
- AIUI1 paper
- A*SIGMOD1 paper
- AUAI1 paper
- BPersuasive1 paper
- AAISTATS1 paper
- A*CHI1 paper
- AMICCAI1 paper
- AICWSM1 paper
- BBigData1 paper
- ARecSys1 paper
- BMOBIHOC1 paper
- CICIS1 paper
- CFUSION1 paper
Papers
79 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | The Shepherd Test: How Will Super Intelligent Agents Balance Care and Control in Asymmetric Relationships? | Djallel Bouneffouf, Matthew Riemer, Kush R. Varshney |
| 2026 | ACL | AI Steerability 360: A Toolkit for Steering Large Language Models. | Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Ching-Yun Ko, Pierre L. Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney |
| 2025 | AIES | Exposing AI Bias by Crowdsourcing: Democratizing Critique of Large Language Models. | Hangzhi Guo, Pranav Narayanan Venkit, Eunchae Jang, Mukund Srinath, Wenbo Zhang, Bonam Mingole, Vipul Gupta, Kush R. Varshney, S. Shyam Sundar, Amulya Yadav |
| 2025 | ICASSP | Contextual Value Alignment. | Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf |
| 2025 | NAACL | Evaluating the Prompt Steerability of Large Language Models. | Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Kush R. Varshney, Eitan Farchi, Pierre L. Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu, Prasanna Sattigeri |
| 2025 | NAACL | Granite Guardian: Comprehensive LLM Safeguarding. | Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martn Santilln Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri |
| 2024 | AIES | Individual Fairness in Graphs Using Local and Global Structural Information. | Yonas Sium, Qi Li, Kush R. Varshney |
| 2024 | AIES | Decolonial AI Alignment: Openness, Visesa-Dharma, and Including Excluded Knowledges. | Kush R. Varshney |
| 2024 | AIES | Racial and Neighborhood Disparities in Legal Financial Obligations in Jefferson County, Alabama. | scar Lara Yejas, Aakanksha Joshi, Andrew Martinez, Leah Nelson, Skyler Speakman, Krysten Thompson, Yuki Nishimura, Jordan Bond, Kush R. Varshney |
| 2024 | EMNLP | Value Alignment from Unstructured Text. | Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney |
| 2024 | IJCAI | Using Causal Inference to Investigate Contraceptive Discontinuation in Sub-Saharan Africa. | Victor Akinwande, Megan MacGregor, Celia Cintas, Ehud Karavani, Dennis Wei, Kush R. Varshney, Pablo A. Nepomnaschy |
| 2024 | IJCAI | ComVas: Contextual Moral Values Alignment System. | Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf |
| 2023 | AAAI | Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. | Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das |
| 2023 | AAAI | Minimax AUC Fairness: Efficient Algorithm with Provable Convergence. | Zhenhuan Yang, Yan Lok Ko, Kush R. Varshney, Yiming Ying |
| 2023 | ICLR | What Is Missing in IRM Training and Evaluation? Challenges and Solutions. | Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu |
| 2023 | IUI | A Banal Account of a Safety-Creativity Tradeoff in Generative AI 163-165. | Kush R. Varshney, Lav R. Varshney |
| 2022 | AAAI | AI Explainability 360: Impact and Design. | 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 | COMAD | Uncertainty Quantification 360: A Hands-on Tutorial. | Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jir Navrtil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang |
| 2022 | SIGMOD | Causal Feature Selection for Algorithmic Fairness. | Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney |
| 2022 | UAI | Differentially private SGDA for minimax problems. | Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying |
| 2021 | AAAI | Exploring the Efficacy of Generic Drugs in Treating Cancer. | Ioana Baldini, Mariana Bernagozzi, Sulbha Aggarwal, Mihaela A. Bornea, Saksham Chawla, Joppe Geluykens, Dmitriy A. Katz-Rogozhnikov, Pratik Mukherjee, Smruthi Ramesh, Sara Rosenthal, Jagrati Sharma, Kush R. Varshney, Laura B. Kleiman, Pradeep Mangalath, Catherine Del Vecchio Fitz |
| 2021 | ACL | Biomedical Interpretable Entity Representations. | Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney |
| 2021 | AIES | Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds. | Michiel A. Bakker, Duy Patrick Tu, Krishna P. Gummadi, Alex 'Sandy' Pentland, Kush R. Varshney, Adrian Weller |
| 2021 | AMIA | Racial Representation Analysis in Dermatology Academic Materials. | Girmaw Abebe Tadesse, Celia Cintas, Roxana Daneshjou, Kush R. Varshney, Peter W. J. Staar, Skyler Speakman, Kenya S. Andrews, Chinyere Agunwa, Justin Jia, Elizabeth E. Bailey, Jules Lipoff, Ginikanwa Onyekaba, Veronica Rotemberg, Ademide Adelekun, James Y. Zou |
| 2021 | COMAD | AI Explainability 360 Toolkit. | 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 | ICASSP | Treatment Effect Estimation Using Invariant Risk Minimization. | Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar |
| 2021 | ICLR | Empirical or Invariant Risk Minimization? A Sample Complexity Perspective. | Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney |
| 2021 | Persuasive | Disparate Impact Diminishes Consumer Trust Even for Advantaged Users. | Tim Draws, Zoltn Szlvik, Benjamin Timmermans, Nava Tintarev, Kush R. Varshney, Michael Hind |
| 2020 | AAAI | Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds. | Michiel A. Bakker, Humberto Rivern Valds, Duy Patrick Tu, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland |
| 2020 | AAAI | Event-Driven Continuous Time Bayesian Networks. | Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian |
| 2020 | AAAI | A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications. | Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman |
| 2020 | AIES | Data Augmentation for Discrimination Prevention and Bias Disambiguation. | Shubham Sharma, Yunfeng Zhang, Jess M. Ros Aliaga, Djallel Bouneffouf, Vinod Muthusamy, Kush R. Varshney |
| 2020 | AIES | Joint Optimization of AI Fairness and Utility: A Human-Centered Approach. | Yunfeng Zhang, Rachel K. E. Bellamy, Kush R. Varshney |
| 2020 | AISTATS | Characterization of Overlap in Observational Studies. | Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel A. Brat, David A. Sontag, Kush R. Varshney |
| 2020 | AMIA | Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning. | William Ogallo, Skyler Speakman, Victor Akinwande, Kush R. Varshney, Aisha Walcott, Charity Wayua, Komminist Weldemariam, Claire-Helene Mershon, Nosa Orobaton |
| 2020 | CHI | Experiences with Improving the Transparency of AI Models and Services. | Michael Hind, Stephanie Houde, Jacquelyn Martino, Aleksandra Mojsilovic, David Piorkowski, John T. Richards, Kush R. Varshney |
| 2020 | CISS | On Mismatched Detection and Safe, Trustworthy Machine Learning. | Kush R. Varshney |
| 2020 | ICASSP | Preservation of Anomalous Subgroups On Variational Autoencoder Transformed Data. | Samuel C. Maina, Reginald E. Bryant, William O. Ogallo, Kush R. Varshney, Skyler Speakman, Celia Cintas, Aisha Walcott-Bryant, Robert-Florian Samoilescu, Komminist Weldemariam |
| 2020 | ICML | Invariant Risk Minimization Games. | Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar |
| 2020 | ICML | Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. | Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney |
| 2020 | IJCAI | Inspection of Blackbox Models for Evaluating Vulnerability in Maternal, Newborn, and Child Health. | William Ogallo, Skyler Speakman, Victor Akinwande, Kush R. Varshney, Aisha Walcott-Bryant, Charity Wayua, Komminist Weldemariam |
| 2020 | KDD | Tutorial on Human-Centered Explainability for Healthcare. | Prithwish Chakraborty, Bum Chul Kwon, Sanjoy Dey, Amit Dhurandhar, Daniel M. Gruen, Kenney Ng, Daby Sow, Kush R. Varshney |
| 2020 | MICCAI | Fairness of Classifiers Across Skin Tones in Dermatology. | Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney |
| 2019 | AIES | Fair Transfer Learning with Missing Protected Attributes. | Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty |
| 2019 | AIES | TED: Teaching AI to Explain its Decisions. | Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney |
| 2019 | ICASSP | Bias Mitigation Post-processing for Individual and Group Fairness. | Pranay Kr. Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R. Varshney, Ruchir Puri |
| 2019 | ICASSP | Constructing and Compressing Frames in Blockchain-based Verifiable Multi-party Computation. | Ravi Kiran Raman, Kush R. Varshney, Roman Vaculn, Nelson Kibichii Bore, Sekou L. Remy, Eleftheria Kyriaki Pissadaki, Michael Hind |
| 2019 | ICML | Topological Data Analysis of Decision Boundaries with Application to Model Selection. | Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Krishnan Mody |
| 2019 | IJCAI | Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration. | Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush R. Varshney, Murray Campbell, Moninder Singh, Francesca Rossi |
| 2018 | AAAI | Assessing National Development Plans for Alignment With Sustainable Development Goals via Semantic Search. | Jonathan Galsurkar, Moninder Singh, Lingfei Wu, Aditya Vempaty, Mikhail Sushkov, Devika Iyer, Serge Kapto, Kush R. Varshney |
| 2018 | IJCAI | Semantic Representation of Data Science Programs. | Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic, Kush R. Varshney |
| 2018 | ICWSM | The Effect of Extremist Violence on Hateful Speech Online. | Alexandra Olteanu, Carlos Castillo, Jeremy Boy, Kush R. Varshney |
| 2016 | CISS | Fidelity loss in distribution-preserving anonymization and histogram equalization. | Lav R. Varshney, Kush R. Varshney |
| 2016 | ITA | Engineering safety in machine learning. | Kush R. Varshney |
| 2015 | BigData | Optigrow: People Analytics for Job Transfers. | Dennis Wei, Kush R. Varshney, Marcy Wagman |
| 2015 | ICASSP | Learning interpretable classification rules using sequential rowsampling. | Sanjeeb Dash, Dmitry M. Malioutov, Kush R. Varshney |
| 2015 | ICASSP | Persistent topology of decision boundaries. | Kush R. Varshney, Karthikeyan Natesan Ramamurthy |
| 2015 | ICASSP | Robust binary hypothesis testing under contaminated likelihoods. | Dennis Wei, Kush R. Varshney |
| 2015 | RecSys | Assessing Expertise in the Enterprise: The Recommender Point of View. | Aleksandra Mojsilovic, Kush R. Varshney |
| 2015 | SDM | Health Insurance Market Risk Assessment: Covariate Shift and k-Anonymity. | Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney |
| 2014 | ICASSP | Screening for learning classification rules via Boolean compressed sensing. | Sanjeeb Dash, Dmitry M. Malioutov, Kush R. Varshney |
| 2014 | KDD | Targeting direct cash transfers to the extremely poor. | Brian Abelson, Kush R. Varshney, Joy Sun |
| 2014 | KDD | Predicting employee expertise for talent management in the enterprise. | Kush R. Varshney, Vijil Chenthamarakshan, Scott W. Fancher, Jun Wang, DongPing Fang, Aleksandra Mojsilovic |
| 2013 | ICASSP | Opinion dynamics with bounded confidence in the Bayes risk error divergence sense. | Kush R. Varshney |
| 2013 | ICDM | Quantifying and Recommending Expertise When New Skills Emerge. | DongPing Fang, Kush R. Varshney, Jun Wang, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic, John H. Bauer |
| 2013 | ICDM | Prescriptive Analytics for Allocating Sales Teams to Opportunities. | Ban Kawas, Mark S. Squillante, Dharmashankar Subramanian, Kush R. Varshney |
| 2013 | ICML | Exact Rule Learning via Boolean Compressed Sensing. | Dmitry M. Malioutov, Kush R. Varshney |
| 2013 | MOBIHOC | Balancing lifetime and classification accuracy of wireless sensor networks. | Kush R. Varshney, Peter M. van de Ven |
| 2012 | ICASSP | Dynamic matrix factorization: A state space approach. | John Z. Sun, Kush R. Varshney, Karthik Subbian |
| 2012 | ICDM | An Analytics Approach for Proactively Combating Voluntary Attrition of Employees. | Moninder Singh, Kush R. Varshney, Jun Wang, Aleksandra Mojsilovic, Alisia R. Gill, Patricia I. Faur, Raphael Ezry |
| 2012 | ICIS | Interactive Visual Salesforce Analytics. | Kush R. Varshney, Jamie C. Rasmussen, Aleksandra Mojsilovic, Moninder Singh, Joan Morris DiMicco |
| 2012 | SDM | Legislative Prediction via Random Walks over a Heterogeneous Graph. | Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic |
| 2011 | ICASSP | MCMC inference of the shape and variability of time-response signals. | Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Aleksandra Mojsilovic, Moninder Singh |
| 2011 | ICASSP | Spatially-correlated sensor discriminant analysis. | Kush R. Varshney |
| 2011 | ICDM | Estimating Post-Event Seller Productivity Profiles in Dynamic Sales Organizations. | Kush R. Varshney, Moninder Singh, Mayank Sharma, Aleksandra Mojsilovic |
| 2011 | ITA | Categorical decision making by people, committees, and crowds. | Lav R. Varshney, Joong Bum Rhim, Kush R. Varshney, Vivek K. Goyal |
| 2010 | KDD | Class-specific error bounds for ensemble classifiers. | Ryan J. Prenger, Tracy D. Lemmond, Kush R. Varshney, Barry Y. Chen, William G. Hanley |
| 2009 | FUSION | Learning dimensionality-reduced classifiers for information fusion. | Kush R. Varshney, Alan S. Willsky |
| 2008 | ICASSP | Minimum mean bayes risk error quantization of prior probabilities. | Kush R. Varshney, Lav R. Varshney |