Research Fellow, Digital Futures
- Research Directorate
Salman Ahmed is a Research Fellow at the Digitech Centre, Digital Futures Institute, where he actively contributes to industrial consultancies, training initiatives, and knowledge dissemination. He is committed to mentoring students and fostering a research-focused environment.
Salman is currently pursuing a Ph.D. in Data Analytics, specializing in Natural Language Processing. He holds a Master's degree in Software Engineering and a Bachelor's degree in Information Technology. Salman's experience is diverse, with a focus on managing and analyzing complex industrial and transdisciplinary projects.
During his Ph.D. research, Salman led an industrially focused NLP project at the Intelligent Systems Research Centre (ISRC) within the School of Computing, Engineering, and Intelligent Systems at Ulster University. This project was supported by the UK Research and Innovation Turing AI Fellowship, funded by the Engineering and Physical Sciences Research Council(EPSRC). The project aimed to develop an advanced multi-modal analytics approach to predict major Allstate infrastructure incidents. His work has provided insights to implement preventative measures promptly, showcasing his commitment to practical solutions.
Salman's proficiency extends to employing state-of-the-art transformer models, including BERT, ERNIE, and Roberta. He has worked on various projects in collaboration with industry and academia, ranging from industrial projects to the UKRI research framework. Salman has published in prestigious venues, including high-impact conferences and journals in NLP/ML for AIOps, Text/Dialogue Summarization, Sentiment Analysis, Social Media Analytics, Scientific Document Processing, and Financial/Forensic Sciences.
Collaborative by nature, Salman actively engages with colleagues, fostering a collaborative environment. His dedication to academic excellence is evident through his diligent approach to meeting tasks within designated timelines. His multidisciplinary background and commitment to advancing the field make him a valuable asset to any research team.
Salman has previous teaching experience at several universities in Pakistan before pursuing his PhD journey. This experience includes designing module materials, grading examinations and papers, and gathering student feedback. Furthermore, during his PhD program at Ulster University, Salman worked as a Lab demonstrator for over three years, in both online and in-person settings. In this role, he assisted in various modules, including Professional Software Development I & II, Object-Oriented Programming, Software Engineering, Web Application Development, and Expert Systems.
1) S. Ahmed, M. Singh, B. Doherty, et al., “An empirical analysis of state-of-art classiﬁcation models in an it incident severity prediction framework,” Applied Sciences, vol. 13, no. 6, 2023, Issn: 2076-3417. DOI: 10.3390/app13063843.
2) S. A. K. Gahyyur, A. Razzaq, S. Z. Hasan, Ahmed, Salman, and R. Ullah, “Evaluation for feature driven development paradigm in context of architecture design augmentation and perspective implications,” International Journal of Advanced Computer Science and Applications, vol. 9, no. 3, pp. 236–247, 2018.
3) S. A. K. Ghayyur, Ahmed, Salman, M. Ali, A. Razzaq, N. Ahmed, and A. Naseem, “A systematic literature review of success factors and barriers of agile software development,” International Journal of Advanced Computer Science and Applications, vol. 9, no. 3, pp. 278–291, 2018.
4) S. A. K. Ghayyur, Ahmed, Salman, A. Naseem, and A. Razzaq, “Motivators and demotivators of agile software development: Elicitation and analysis,” International Journal of Advanced Computer Science and Applications, vol. 8, no. 12, pp. 304–314, 2018.
5) S. A. K. Ghayyur, Ahmed, Salman, S. Ullah, and W. Ahmed, “The impact of motivator and demotivator factors on agile software development the case of pakistan,” International Journal of Advanced Computer Science and Applications, vol. 9, no. 7, pp. 80–93, 2018.
6) S. A. K. Ghayyur, A. Razzaq, S. Ullah, and Ahmed, Salman, “Matrix clustering based migration of system application to microservices architecture,” International Journal of Advanced Computer Science and Applications, vol. 9, no. 1, pp. 284–296, 2018.
7) A. Khan, F. Bibi, M. Dilshad, Ahmed, Salman, Z. Ullah, and H. Ali, “Accident detection and smart rescue system using android smartphone with real-time location tracking,” International Journal of Advanced Computer Science and Applications, vol. 9, no. 6, pp. 341–355, 2018.
8) M. Khan, N. Javaid, A. Naseem, et al., “Game theoretical demand response management and short-term load forecasting by knowledge based systems on the basis of priority index,” Electronics, vol. 7, no. 12, p. 431, 2018.
9) A. Naseem, M. Anwar, Ahmed, Salman, Q. A. Satti, F. R. Hashmi, and T. Malik, “Tagging urdu sentences from english pos taggers,” International Journal Of Advanced Computer Science And Applications, vol. 8, no. 10, pp. 231–238, 2017.
1) S. Ahmed, M. Singh, S. Bhattacharyya, and D. Coyle, “Decoding Neural Activity for POS Tagging"in IEEE International Conference on Systems, Man, and Cybernetics (SMC)
1) Ahmed, Salman, M. Singh, and D. Coyle, “Knowledge-based intelligent system for it incident devops,” in International Conference on Software Engineering, IEEE, 2023.
2) S. Ahmed, M. Singh, B. Doherty, E. Ramlan, K. Harkin, and D. Coyle, “Ai for information technology operation (aiops): A review of it incident risk prediction,” in 2022 9th International Conference on Soft Computing Machine Intelligence (ISCMI), 2022, pp. 253–257.DOI: 10.1109/ISCMI56532.2022.10068482.
3) S. Ahmed, M. Singh, B. Doherty, E. Ramlan, K. Harkin, and D. Coyle, “Multiple severity-level classiﬁcations for it incident risk prediction,” in 2022 9th International Conference on Soft Computing Machine Intelligence (ISCMI), 2022, pp. 270–274. DOI: 10.1109/ISCMI56532.2022.10068477.
4) A. A. Butt, N. Javaid, S. Mujeeb, Ahmed, Salman, M. M. S. Ali, and W. Ali, “Foged energy optimization in smart homes,” in Innovative Mobile and Internet Services in Ubiquitous Computing: Proceedings of the 12th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing
(IMIS-2018), Springer, 2019, pp. 265–275.
5) A. Naseem, M. Anwar, Ahmed, Salman, A. Jan, and A. K. Malik, “Reusing stanford pos tagger for tagging urdu sentences,” in 2017 13th International Conference on Emerging Technologies (ICET), IEEE, 2017, pp. 1–6.
Books and Chapters
1) M. Singh and Salman Ahmed, Eds., Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers. 2023.
Salman has extensive experience in managing multinational companies. In his recent collaboration, Salman was involved in a data analytics project with UU and AllState Inc. for an IT Incident Severity Prediction Framework, supported by the UK Research and Innovation Turing AI Fellowship, funded by the Engineering and Physical Sciences Research Council.