1. M. Bazina &, O. Habimana (2022). Factors constraining effective application of ICT in teaching and learning Mathematics in Nyanza District Secondary Schools, Rwanda. Journal of Research Innovation and Implications in Education, 6(3), 18 –28.
2. JP. Munyakazi, J. Mukagihana, T. Nsengimana, C. Mukamwambali, and O. Habimana (2022). Impacts of Computer-Assisted Instructions on Students' Academic Performance of Biology within Secondary Schools. International Journal of Learning and Development, 12(2), 81-94.
3. O. Habimana, Y. Li, R. Li, X. Gu, and G. Yu, “Context-Aware Neural Model for Sentiment Analysis Towards Question-Answering”, Expert Systems with Applications, 2022 (Accepted)
4. O. Habimana, Y. Li, R. Li, X. Gu, and G. Yu, “Sentiment analysis using deep learning approaches: An overview,” Science China Information Sciences, vol. 63, no. 1:111102, 2020.
5. O. Habimana, Y. Li, R. Li, X. Gu, and W. Yan, “Attentive Convolutional Gated Recurrent Network: A Contextual Model to Sentiment Analysis,” International Journal of Machine Learning and Cybernetics, vol. 11, no. 12, 22637-2651, 2020.
6. O. Habimana, Y. Li, R. Li, X. Gu, and Y. Peng, “A Multi-Task Learning Approach to Improve Sentiment Analysis with Explicit Recommendation,” in International Joint Conference on Neural Networks, pp. 1–8, IEEE, 2020.
7. T. Liang, Y. Li, R. Li, X. Gu, O. Habimana, and Y. Hu, “Personalizing session-based recommendation with dual attentive neural network,” in International Joint Conference on Neural Networks, pp. 1–8, IEEE, 2019.
8. L. Gao, Y. Li, R. Li, Z. Zhu, X. Gu, and O. Habimana, “ST-RNet: A time-aware point-of-interest recommendation method based on neural network,” in International Joint Conference on Neural Networks, pp. 1–8, IEEE, 2019.
9. X. Zhan, Y. Li, R. Li, X. Gu, O. Habimana, and H. Wang, “Stock price prediction using time convolution long short-term memory network,” in Knowledge Science, Engineering and Management - 11th International Conference, KSEM 2018, 2018, Proceedings, Part I (W. Liu, F. Giunchiglia, and B. Yang, eds.), vol. 11061 of Lecture Notes in Computer Science, pp. 461–468, Springer, 2018.
Habimana Olivier
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Email:
habolivier13@gmail.com
Telephone:
+250788743498
Twitter:
@habolivier20
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Brief profile:
Dr. Olivier HABIMANA is a Lecturer and Master Supervisor at the University of Rwanda, College of Education, Rukara Campus. He is also a Researcher in the African Centre of Excellence for Innovative Teaching and Learning Mathematics and Science (ACEITLMS), based in the College of Education. He received his Ph.D. in Engineering Specialized in Computer Application Technology from the Huazhong University of Science and Technology, Wuhan, China, in 2020. In 2016, he obtained his MSc in Computer science from the Department of Computer Science, University of Mysore, India. After completing his BSc in Computer Science and Education from the former Kigali Institute of Education in 2011, he worked in higher learning institutions. He joined as a Tutorial Assistant at the former Kavumu College of Education and later at the University of Rwanda, College of Education, as an Assistant Lecturer. His research interest is data science, ICT in Education, social network analysis, data mining, sentiment analysis, machine learning, and deep learning.
Research Area:
Data Science and ICT Integration in Education