| 2026 | EACL | Compact Multimodal Language Models as Robust OCR Alternatives for Noisy Textual Clinical Reports. | Nikita Neveditsin, Pawan Lingras, Salil Patil, Swarup Patil, Vijay Kumar Mago |
| 2025 | ACL | Evaluating Structured Output Robustness of Small Language Models for Open Attribute-Value Extraction from Clinical Notes. | Nikita Neveditsin, Pawan Lingras, Vijay Kumar Mago |
| 2025 | NAACL | From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models. | Nikita Neveditsin, Pawan Lingras, Vijay Kumar Mago |
| 2025 | SMC | Extracting 3D Features From 2D Images Using Artificial Intelligence: A Survey. | Andrew Fisher, Arjun Pillai, Pawan Lingras, Vijay Mago |
| 2019 | IFSA | Effect of Maximizing Recall and Agglomeration of Feedback on Accuracy. | Ross MacDonald, Nikita Neveditsin, Pawan Lingras, Trent Hillard |
| 2017 | ISMIS | Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns. | Matthew Triff, Ilya Pavlovski, Zhixing Liu, Lori-Anne Morgan, Pawan Lingras |
| 2016 | CEC | Evolutionary semi-supervised rough categorization of brain signals from a wearable headband. | Glavin Wiechert, Matthew Triff, Zhixing Liu, Zhicheng Yin, Shuai Zhao, Ziyun Zhong, Pawan Lingras |
| 2015 | AI | Visual Predictions of Traffic Conditions. | Jason P. Rhinelander, Mathew Kallada, Pawan Lingras |
| 2014 | DSAA | Rough possibilistic meta-clustering of retail datasets. | Asma Ammar, Zied Elouedi, Pawan Lingras |
| 2013 | ACIIDS | Comparison of Gene Co-expression Networks and Bayesian Networks. | Saurabh Nagrecha, Pawan Lingras, Nitesh V. Chawla |
| 2013 | AI | The K-Modes Method under Possibilistic Framework. | Asma Ammar, Zied Elouedi, Pawan Lingras |
| 2013 | AI | Exhaustive Search with Belief Discernibility Matrix and Function. | Salsabil Trabelsi, Zied Elouedi, Pawan Lingras |
| 2013 | IFSA | The k-modes method using possibility and rough set theories. | Asma Ammar, Zied Elouedi, Pawan Lingras |
| 2013 | IFSA | A granular recursive fuzzy meta-clustering algorithm for social networks. | Kishore Rathinavel, Pawan Lingras |
| 2012 | HIS | Propagation of knowledge from crisp and soft clustering through a granular hierarchy. | Pawan Lingras, Parag Bhalchandra, Santosh Khamitkar, Satish Mekewad, Ravindra Rathod |
| 2012 | IPMU | K-Modes Clustering Using Possibilistic Membership. | Asma Ammar, Zied Elouedi, Pawan Lingras |
| 2012 | ISDA | Recursive meta-clustering in a granular network. | Pawan Lingras, Kishore Rathinavel |
| 2012 | ISMIS | RPKM: The Rough Possibilistic K-Modes. | Asma Ammar, Zied Elouedi, Pawan Lingras |
| 2011 | GRC | Soft clustering from crisp clustering using granulation for mobile call mining. | Pawan Lingras, Sarjerao Nimse, N. Darkunde, A. Muley |
| 2010 | IPMU | Rule Discovery Process Based on Rough Sets under the Belief Function Framework. | Salsabil Trabelsi, Zied Elouedi, Pawan Lingras |
| 2010 | ISDA | Rough, fuzzy, interval clustering for web usage mining. | Manish R. Joshi, Pawan Lingras, Yiyu Yao, Virendrakumar C. Bhavsar |
| 2010 | ISDA | Belief Rough Set Classification for web mining based on dynamic core. | Salsabil Trabelsi, Zied Elouedi, Pawan Lingras |
| 2009 | AI | Belief Rough Set Classifier. | Salsabil Trabelsi, Zied Elouedi, Pawan Lingras |
| 2009 | FlAIRS | A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network Inference. | Cory J. Butz, Junying Chen, Ken Konkel, Pawan Lingras |
| 2009 | FlAIRS | Join Tree Propagation Utilizing Both Arc Reversal and Variable Elimination. | Cory J. Butz, Ken Konkel, Pawan Lingras |
| 2008 | ISMIS | A Web-Based Interface for Hiding Bayesian Network Inference. | Cory J. Butz, Pawan Lingras, Ken Konkel |
| 2007 | GRC | Precision and Recall in Rough Support Vector Machines. | Pawan Lingras, Cory J. Butz |
| 2007 | HCI | Using Speech Recognition and Intelligent Search Tools to Enhance Information Accessibility. | Keith Bain, Jason Hines, Pawan Lingras, Yumei Qin |
| 2006 | SMC | A New Paradigm for Intelligent Collision Avoidance via Interactive and Interdependent Generic Maneuvers. | Ravipriya Ranatunga, Sisil Kumarawadu, Pawan Lingras, Tsu-Tian Lee |
| 2005 | GRC | Interval set representations of 1-v-r support vector machine multi-classifiers. | Pawan Lingras, Cory J. Butz |
| 2003 | AI | Fuzzy C-Means Clustering of Web Users for Educational Sites. | Pawan Lingras, Rui Yan, Chad West |
| 2003 | ISMIS | Clustering Supermarket Customers Using Rough Set Based Kohonen Networks. | Pawan Lingras, Mofreh Hogo, Miroslav Snorek, Bill Leonard |
| 1993 | ICCI | Combination of Evidence in Rough Set Theory. | Pawan Lingras |
| 1993 | ISMIS | Upper and Lower Entropies of Belief Functions Using Compatible Probability Functions. | C. W. R. Chau, Pawan Lingras, S. K. Michael Wong |
| 1991 | IJCAI | Propagation of Preference Relations in Qualitative Inference Networks. | S. K. Michael Wong, Pawan Lingras, Yiyu Yao |
| 1991 | ISMIS | Towards Implementing Valuation Based Systems with Relational Databases. | S. K. Michael Wong, Pawan Lingras, Yiyu Yao |
| 1991 | UAI | Compatibility of Quantitative and Qualitative Representations of Belief. | S. K. Michael Wong, Yiyu Yao, Pawan Lingras |
| 1988 | ISMIS | An Optimistic Rule for Accumulation of Evidence. | Pawan Lingras, S. K. Michael Wong |