| 2026 | ICPR | G-Drift MIA: Membership Inference via Gradient-Induced Feature Drift in LLMs. | Ravi Ranjan, Utkarsh Grover, Xiaomin Lin, Agoritsa Polyzou |
| 2026 | SAC | Aurora: Neuro-Symbolic AI Driven Advising Agent. | Lorena Amanda Quincoso Lugones, Christopher Lukas Kverne, Nityam Sharadkumar Bhimani, Ana Carolina Oliveira, Agoritsa Polyzou, Christine Lisetti, Janki Bhimani |
| 2025 | DSAA | Reasoning with Knowledge Graphs for Trustworthy Course Recommendation. | Md. Akib Zabed Khan, Dongsheng Luo, Agoritsa Polyzou |
| 2024 | EDM | How Can We Use LLMs for EDM Tasks? The Case of Course Recommendation. | Md. Akib Zabed Khan, Agoritsa Polyzou, Neila Bennamane |
| 2024 | FlAIRS | Estimate Undergraduate Student Enrollment in Courses by Re-purposing Recommendation Tools. | Md. Akib Zabed Khan, Agoritsa Polyzou |
| 2023 | EDM | Session-based Course Recommendation Frameworks using Deep Learning. | Md. Akib Zabed Khan, Agoritsa Polyzou |
| 2019 | EDM | Scholars Walk: A Markov Chain Framework for Course Recommendation. | Agoritsa Polyzou, Athanasios N. Nikolakopoulos, George Karypis |
| 2019 | HCI | Learning Behavioral Pattern Analysis Based on Digital Textbook Reading Logs. | Chengjiu Yin, Zhuo Ren, Agoritsa Polyzou, Yong Wang |
| 2018 | EDM | Feature extraction for classifying students based on their academic performance. | Agoritsa Polyzou, George Karypis |
| 2017 | DSAA | Enriching Course-Specific Regression Models with Content Features for Grade Prediction. | Qian Hu, Agoritsa Polyzou, George Karypis, Huzefa Rangwala |
| 2016 | PAKDD | Grade Prediction with Course and Student Specific Models. | Agoritsa Polyzou, George Karypis |