Assessing the Causal Impact of Online Instruction due to COVID-19 on Students' Grades and its aftermath on Grade Prediction Models. - Oscar Blessed Deho; Lin Liu 003; Srecko Joksimovic; Jiuyong Li; Chen Zhan; Jixue Liu (GoodIT, 2022)

How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics? - Oscar Blessed Deho; Chen Zhan; Jiuyong Li; Jixue Liu; Lin Liu 003; Thuc Duy Le (Br. J. Educ. Technol., 2022)

Assessing the Fairness of Course Success Prediction Models in the Face of (Un)equal Demographic Group Distribution. - Oscar Blessed Deho; Srecko Joksimovic; Lin Liu 003; Jiuyong Li; Chen Zhan; Jixue Liu (L@S, 2023)

Should Learning Analytics Models Include Sensitive Attributes? Explaining the Why. - Oscar Blessed Deho; Srecko Joksimovic; Jiuyong Li; Chen Zhan; Jixue Liu; Lin Liu 003 (IEEE Trans. Learn. Technol., 2023)

Decision Trees in Federated Learning: Current State and Future Opportunities. - Sudath Rohitha Heiyanthuduwage; Irfan Altas; Michael Bewong; Md Zahidul Islam 001; Oscar Blessed Deho (IEEE Access, 2024)

When the Past != The Future: Assessing the Impact of Dataset Drift on the Fairness of Learning Analytics Models. - Oscar Blessed Deho; Lin Liu 003; Jiuyong Li; Jixue Liu; Chen Zhan; Srecko Joksimovic (IEEE Trans. Learn. Technol., 2024)

Beyond Predictive Accuracy: Fairness and Bias in Predicting Test Anxiety. - Oscar Blessed Deho; Srecko Joksimovic; Maria Vieira; Ryan Baker 001 (AIED (2), 2025)

Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms. - Qinyi Liu; Oscar Blessed Deho; Farhad Vadiee; Mohammad Khalil; Srecko Joksimovic; George Siemens (LAK, 2025)

Is it still fair? A comparative evaluation of fairness algorithms through the lens of covariate drift. - Oscar Blessed Deho; Michael Bewong; Selasi Kwashie; Jiuyong Li; Jixue Liu; Lin Liu 003; Srecko Joksimovic (Mach. Learn., 2025)