| 2026 | ICTIR | Equity by Design? On the Trade-Offs in Fairness-Driven Recommendation in Heterogeneous Two-Sided Markets. | Dominykas Seputis, Alexander Timans, Rajeev Verma |
| 2026 | WACV | Detecting Object Tracking Failure via Sequential Hypothesis Testing. | Alejandro Monroy Muoz, Rajeev Verma, Alexander Timans |
| 2025 | IJCCI | A Structured Survey of Anomaly Types and Classification-Based Detection Models in IoT. | Atefeh Gilvari, Ziad Kobti, Narayan C. Kar, Nasrin Tavakoli, Rajeev Verma |
| 2025 | UAI | On Continuous Monitoring of Risk Violations under Unknown Shift. | Alexander Timans, Rajeev Verma, Eric T. Nalisnick, Christian A. Naesseth |
| 2024 | AISTATS | Learning to Defer to a Population: A Meta-Learning Approach. | Dharmesh Tailor, Aditya Patra, Rajeev Verma, Putra Manggala, Eric T. Nalisnick |
| 2023 | AISTATS | Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles. | Rajeev Verma, Daniel Barrejn, Eric T. Nalisnick |
| 2022 | ICML | Calibrated Learning to Defer with One-vs-All Classifiers. | Rajeev Verma, Eric T. Nalisnick |
| 2022 | IJCNLP | The lack of theory is painful: Modeling Harshness in Peer Review Comments. | Rajeev Verma, Rajarshi Roychoudhury, Tirthankar Ghosal |
| 2021 | ICONIP | Attend to Your Review: A Deep Neural Network to Extract Aspects from Peer Reviews. | Rajeev Verma, Kartik Shinde, Hardik Arora, Tirthankar Ghosal |
| 2019 | ACL | DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions. | Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Pushpak Bhattacharyya |