I am a researcher and educator with extensive experience in teaching, mentoring, and conducting interdisciplinary research in Natural Language Processing (NLP) and Machine Learning. My work focuses on developing human-centred models and applications across four key domains: NLP for Education, Emotion Recognition, Multilingual Representation Learning, and Efficient and Scalable Large Language Models (LLMs).
I am determined to guide the next generation of applied researchers. My goal is to facilitate an environment of collaboration and innovation, supporting students in developing original, high-quality research and practical solutions that advance both theory and real-world applications. Currently, I serve as a lecturer at Breda University of Applied Sciences and an Assistant Professor at the University of Groningen’s Bernoulli Institute, where I specialize in NLP and Machine Learning.
Expertise
- Natural Language Processing (NLP)
- Machine Learning
- Deep Learning
- Large Language Models (LLM)
Teaching
- Natural Language Processing (NLP)
- Machine Learning
Education
- PhD in Computer Science (Specilization in Natural Language Processing), Eötvös Loránd University, 2021
- Masters in Informations Science, Addis Ababa University, 2014
- Bachelors in Informations Science, Addis Ababa University, 2011
Publications
2025
- Angelov, A., Tashu, T. M., & Valdenegro-Toro, M. Difficulty Estimation in Natural Language Tasks with Action Scores In Proceedings of the 5th Workshop on Trustworthy NLP (TrustNLP 2025), pp. 351–364.
- Tashu, T. M., Kontos, E. R., Sabatelli, M., & Valdenegro-Toro, M. Cross-Lingual Document Recommendations with Transformer-Based Representations: Evaluating Multilingual Models and Mapping Techniques In Proceedings of the Second Workshop on Scaling Up Multilingual & Multi-Cultural Evaluation, pp. 39–47.
- Tashu, T. M., & Tudor, A. I. Mapping Cross-Lingual Sentence Representations for Low-Resource Language Pairs Using Pre-trained Language Models In Proceedings of the First Workshop on Language Models for Low-Resource Languages, pp. 249–257.
2024
- Philip, H., & Tashu, T. M. Phrase-Level Adversarial Training for Mitigating Bias in Neural Network-based Automatic Essay Scoring arXiv preprint arXiv:2409.04795.
- Mahajan, V., Birihanu, E., & Tashu, T. M. A Dynamic Session-Based Recommendation System with Graph Neural Networks *Proceedings of ITAT’24: Information Technologies – Applications and Theory, *, 2024.
2023
- Fergan, E., & Tashu, T. M. Course Review Sentiment Analysis: A Comparative Study Of Machine Learning and Deep Learning Methods In Proceedings of the 10th International Conference on Behavioural and Social Computing (BESC 2023), pp. 1–7. IEEE.
- Tashu, T. M., Lenz, M., & Horváth, T. NCC: Neural Concept Compression for Multilingual Document Recommendation Applied Soft Computing, 142, 110348. Elsevier.