PROFILE SUMMARY

Dr. Hufsa Mohsin is a highly accomplished academician and researcher focused on Computer Sciences, specializing in the intersection of Artificial Intelligence and Software Engineering. She completed her PhD in Computer Sciences from Beijing Institute of Technology, China, and holds an MS in Software Engineering from NUST. She has received academic distinctions, including a Gold Medal in her MCS and a Distinguished Student award during her PhD, and holds a patent for a method related to software bug classification from her doctoral research. With around two decades of experience in academia across institutions such as Shifa Tameer-e-Millat University (STMU) and COMSATS University Islamabad, she currently serves as Head of the Department of Artificial Intelligence at STMU. Her primary research interests involve Artificial Intelligence, Deep Learning, Reinforcement Learning, Agentic AI, Knowledge Graphs, Quantum Computing, and AI in Healthcare.

EDUCATIONAL QUALIFICATIONS

TEACHING EXPERIENCE

MANAGEMENT EXPERIENCE

HONORS & AWARDS

• Chinese Government Scholarship: Awarded for PhD studies (2017).
• Distinguished Student Award: Awarded during PhD at Beijing Institute of Technology, China (2022).
• Gold Medal: Awarded in Master in Computer Sciences (MCS).

PROFESSIONAL SERVICE & MEMBERSHIPS

• Member: Academic Council, Shifa Tameer-e-Millat University (2025 – Present)
• Member: Graduate Studies & Research Management Council (GSRMC), STMU (2025 – Present)
• Chairperson: Board of Studies, Department of Artificial Intelligence, Faculty of Computing, STMU (2025 – Present)
• Focal Person: Faculty Council, Faculty of Computing, STMU (2024 – Present)
• Member & Program Team Member: Quality Enhancement Cell (QEC) (2023 – 2025)
• Member: Industrial Liaison Committee (2021 – 2023)
• Member: Final Year Committee (2014 – 2017)

RESEARCH AREAS & INTERESTS

• Artificial Intelligence & Agentic AI
• Machine Learning & Deep Learning
• Quantum Computing
• AI in Healthcare
• Software Engineering & Automated Program Repair

PROJECT FUNDINGS & GRANTS

• AI-Assisted Genomic and Phenotypic Characterization of Rare Genetic Disorders in South Asian Population: Submitted in joint collaboration of PSF and NSF.
• AI-Powered Healthcare Platform: Submitted to Google.

RESEARCH SUPERVISION (PhD & MS THESES)

1. [PhD] An agent-based multimodal framework and personalized recommendation for psychological stress detection in university students (In-progress)
2. [MS] Frequency-Temporal Input and Knowledge Distillation for a Compact Deepfake Detector Under Unseen Compression
3. [MS] Structure-Aware Synthesis of Urdu Nastaliq Calligraphy using Generative Diffusion Models
4. [MS] A Lightweight Agentic Workflow for Continual Learning in SMS Spam Detection for the Urdu Script
5. [MS] Integrating Pull Request Comment Analysis and Developer Profiles for Expertise-Based Recommendations in Global Software Development
6. [MS] An Automated Program Repair with Semantic-Aware Prompt Engineering using Open-Source Model
7. [MS] A Hybrid Quantum Framework for Classifying Software Defects Using Grover’s Search Algorithm and Variational Quantum Classifier
8. [MS] QML vs. CML: An empirical analysis and effective feature identification for diabetes predictions
9. [MS] A knowledge graph-based approach for predictive analysis and prevention guidelines of type-1 diabetes at adolescence

FINAL YEAR PROJECT SUPERVISION (BS LEVEL)

1. SMAOSIS: System for Multi-Agent Orchestration with Self Improvement, Intelligence & Supervision
2. Tracing Layer-Wise Weight Change During Fine-Tuning: A Notebook Extension for Efficient LLM Training
3. Irenic: A recruitment system
4. Safedrive: An intelligent driving system
5. Bunyaad: An Intelligent crack detection system and price prediction of houses
6. TechiesArena: Game Development
7. LandBlocks: A blockchain based property solution

JOURNAL PUBLICATIONS & PATENTS

1. Rehman, U. U., Mohsin, H., Mustafa, G., Khan, S. U. R., & Rafiq, H. (2026). A knowledge graph–driven big data framework for explainable clinical decision support using heterogeneous healthcare data. Journal of Big Data, 13, Article 1489. (IF: 10.4)
2. Zamir, S., Rehman, A., Mohsin, H., Zamir, E., Abbas, A., & Al-Yarimi, F. A. M. (2025). Integrating Pull Request Comment Analysis and Developer Profiles for Expertise-Based Recommendations in Global Software Development. IEEE Access, 13, 16637–16648. (IF: 4.2)
3. Mohsin, H., Shi, C., Hao, S., & Jiang, H. (2022). SPAN: A self-paced association augmentation and node embedding-based model for software bug classification and assignment. Knowledge-Based Systems, 236, 107711. (IF: 8.0)
4. Mohsin, H., & Shi, C. (2021). SPBC: A self-paced learning model for bug classification from historical repositories of open-source software. Expert Systems with Applications, 167, 113808. (IF: 9.4)
5. Mohsin, H., & Shi, C. (2021). A Method for software bug classification. Patent No. CN110598787.

CONFERENCE PUBLICATIONS

1. Zhao, S., Shi, C., Ren, S., & Mohsin, H. (2022). Correlation Feature Mining Model Based on Dual Attention for Feature Envy Detection. 34th International Conference on Software Engineering & Knowledge Engineering (SEKE).
2. Mohsin, H. (2017). A Cryptographically Secure Scheme for Preserving Privacy in Association Rule Mining. In: Barolli, L., Zhang, M., & Wang, X. (eds) Advances in Internetworking, Data & Web Technologies (EIDWT 2017). Lecture Notes on Data Engineering and Communications Technologies, vol 6. Springer.
3. Neelofar, Javed, M. Y., & Mohsin, H. (2012). An Automated Approach for Software Bug Classification. 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems, pp. 414–419.