About Me
Researcher in artificial intelligence with publications in leading peer-reviewed journals and conferences, including the IEEE, Nature Portfolio, MDPI, and JMIR Publications. Current research focuses on LLMs, NLP, computer vision, and XAI for critical applications in healthcare, agriculture, and multilingual intelligence. International research exposure across Canada, New Zealand, and Mexico, combined with strong software development expertise gained through 8 years of industry practice.
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Research Publication
1. Ahmad, Muhammad and Waqas, Muhammad and Hamza, Ameer and Usman, Sardar and Batyrshin, Ildar and Sidorov, Grigori. 2025. “UA-HSD-2025: Multi-Lingual Hate Speech Detection from Tweets Using Pre-Trained Transformers.” MDPI AG 14. https://doi.org/10.3390/computers14060239
2. Ahmad, Muhammad and Waqas, Muhammad and Hamza, Ameer and Usman, Sardar and Batyrshin, Ildar and Sidorov, Grigori. 2025. “UA-HSD-2025: Multi-Lingual Hate Speech Detection from Tweets Using Pre-Trained Transformers.” MDPI AG 14. https://doi.org/10.3390/computers14060239
3. Usman, Muhammad and Ahmad, Muhammad and Ullah, Fida and Muzamil, Muhammad and Hamza, Ameer and Jalal, Muhammad and Gelbukh, Alexander. 2025. “Fine-Tuned RoBERTa Model for Bug Detection in Mobile Games: A Comprehensive Approach.” MDPI AG 14. https://doi.org/10.3390/computers14040113
4. Ahmad, Muhammad and Batyrshin, Ildar and Sidorov, Grigori. 2025. “Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation.” JMIR Publications Inc. 5. 10.2196/70525
5. Ahmad, Muhammad and Sidorov, Grigori and Amjad, Maaz and Ameer, Iqra and Batyrshin, Ildar. 2025. “Opioid Crisis Detection in Social Media Discourse Using Deep Learning Approach.” MDPI AG 16. https://doi.org/10.3390/info16070545
6. Ahmad, Muhammad and Farid, Humaira and Ameer, Iqra and Ullah, Fida and Muzamil, Muhammad and Jalal, Muhammad and Hamza, Ameer and Batyrshin, Ildar and Sidorov, Grigori. 2025. “UE-NER-2025: A GPT-Based Approach to Multi-Lingual Named Entity Recognition on Urdu and English.” Institute of Electrical and Electronics Engineers (IEEE) 13. 10.1109/ACCESS.2025.3579289
7. Ahmad, Muhammad and Basile, Pierpaolo and Ullah, Fida and Batyrshin, Ildar and Sidorov, Grigori. 2025. “RUDA-2025: Depression Severity Detection Using Pre-Trained Transformers on Social Media Data.” MDPI AG 6. https://doi.org/10.3390/ai6080191
8. Ahmad, Muhammad and Sardar, Usman and Batyrshin, Ildar and Hasnain, Muhammad and Sajid, Khan and Sidorov, Grigori. 2024. “Elegante: A Machine Learning-Based Threads Configuration Tool for SpMV Computations on Shared Memory Architecture.” MDPI AG 15. https://doi.org/10.3390/info15110685
9. Ahmad, Muhammad and Usman, Sardar and Farid, Humaira and Ameer, Iqra and Muzzamil, Muhammad and Ameer, Hmaza and Sidorov, Grigori and Batyrshin, Ildar. 2024. “Hope Speech Detection Using Social Media Discourse (Posi-Vox-2024): A Transfer Learning Approach.” National Research University 10. https://doi.org/10.17323/jle.2024.22443
10. Ahmed, Muhammad and Usman, Sardar and Shah, Nehad Ali and Ashraf, M. Usman and Alghamdi, Ahmed Mohammed and Bahadded, Adel A. and Almarhabi, Khalid Ali. 2022. “AAQAL: A Machine Learning-Based Tool for Performance Optimization of Parallel SPMV Computations Using Block CSR.” MDPI AG 12. https://doi.org/10.3390/app12147073
11. Muhammad Ahmad, Iqra Ameer, Wareesa Sharif, Sardar Usman, Muhammad Muzamil, Ameer Hamza, Muhammad Jalal, Ildar Batyrshin & Grigori Sidorov. 2021. “Multilingual hope speech detection from tweets using transfer learning models.” Springer Nature 15. 10.1038/s41598?025?88687?w
Research and Development Projects
1. Bilingual Sentiment Analysis of Mobile Game Reviews: A Human?Centered Explainable AI Approach
With: Dalhousie University (2026-02 - 2026-07)
This research project investigates bilingual sentiment analysis of mobile game user reviews by integrating human?centered design principles with explainable AI (XAI) methodologies. The work involves collecting and preprocessing multilingual mobile game review data, implementing transfer learning and explainability techniques to understand model decisions, and evaluating model performance on sentiment classification tasks. The goal is to improve sentiment analysis accuracy while providing interpretable insights into user feedback that can support developers and stakeholders in game analytics.