• Options Without Agency: Diversity as a Requirement for Fair Actionable Recourse
  Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Elke A. Rundensteiner
  Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency (FAccT 2026)
• KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction
  Lei Ma, Jinyang Liu, Tieying Zhang, Peter M. VanNostrand, Dennis M. Hofmann, Lei Cao, Elke A. Rundensteiner, Jianjun Chen
  Proceedings of the IEEE International Conference on Data Engineering (ICDE 2026)

• Agree to Disagree: Robust Anomaly Detection with Noisy Labels
  Dennis M. Hofmann, Peter M. VanNostrand, Lei Ma, Huayi Zhang, Joshua C. DeOliveira, Lei Cao, Elke Rundensteiner
  Proceedings of the ACM on Management of Data (SIGMOD 2025)
• Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data
  Lei Ma, Lei Cao, Peter M. VanNostrand, Dennis M. Hofmann, Su Yao, Elke Rundensteiner
  Proceedings of the ACM on Management of Data (SIGMOD 2025)

• Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions
  Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Belisha Genin, Randy Huang, Elke Rundensteiner
  Proceedings of the VLDB Endowment (VLDB 2024)
• Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding
  Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Elke Rundensteiner
  The ACM Conference on Fairness, Accountability, and Transparency (FAccT 2024)

• FACET: Robust Counterfactual Explanation Analytics
  Peter M. VanNostrand, Huayi Zhang, Dennis M. Hofmann, Elke Rundensteiner
  Proceedings of the ACM on Management of Data (SIGMOD 2023)

• A Demonstration of AutoOD: A Self-Tuning Anomaly Detection System
  Dennis M. Hofmann, Peter M. VanNostrand, Huayi Zhang, Yizhou Yan, Lei Cao, Samuel Madden, Elke Rundensteiner
  Proceedings of the VLDB Endowment 2022 (VLDB 2022)