PROFILE SUMMARY

Dr. Raja Habib is an accomplished data scientist, researcher, and educator holding a PhD in Data Mining from the Capital University of Science and Technology (CUST), Islamabad. With more than 7 years of professional industry experience across national and international software houses and telecom organizations, and over 6 years of university-level teaching experience, he brings a strong blend of practical expertise and academic depth to his role as Assistant Professor at Shifa Tameer-e-Millat University, Islamabad. Dr. Habib has authored multiple research publications in high-impact, peer-reviewed journals, contributing to the advancement of knowledge in data science and machine learning. His research interests include machine learning, data mining, recommender systems, and intelligent data-driven solutions, with a focus on developing innovative methods to extract meaningful insights from complex datasets.

EDUCATIONAL QUALIFICATIONS

TEACHING EXPERIENCE

PROFESSIONAL EXPERIENCE

MANAGEMENT EXPERIENCE

MEMBERSHIP OF PROFESSIONAL BODIES

• Convener: NCEAC Committee, CS & IT, University of Lahore, Islamabad Campus
• Member: Board of Faculty, Faculty of Information Technology, University of Lahore
• Member: Board of Studies, CS & IT, University of Lahore, Islamabad Campus
• Member: Departmental Board of Studies, CS & IT, University of Lahore, Islamabad Campus

HONORS & AWARDS

• Successful Accreditation for the BS (Computer Science) and BS (Software Engineering) Degree Programs of University of Lahore, Islamabad Campus (2020, 2021, and 2022).
• Fully funded scholarship for PhD studies from the Higher Education Commission (HEC), Pakistan.
• IGNITE funding for various Final Year Projects (FYPs) as a supervisor.

RESEARCH AREAS & INTERESTS

• Machine Learning
• Data Science
• Scientometrics
• Internet of Things (IoT)

JOURNAL PUBLICATIONS

1. Naseem, A., Habib, R., Naz, T., Atif, M., Arif, M., & Allaoua Chelloug, S. (2022). Novel Internet of Things Based Approach Towards Diabetes Prediction Using Deep Learning Models. Frontiers in Public Health, 2848.
2. Habib, R., & Afzal, M. T. (2017). Paper recommendation using citation proximity in bibliographic coupling. Turkish Journal of Electrical Engineering & Computer Sciences, 25(4), 2708-2718.
3. Habib, R., & Afzal, M. T. (2019). Sections-based bibliographic coupling for research paper recommendation. Scientometrics, 1-14.
4. Zaffar, M., Hashmani, M. A., Habib, R., Quraishi, K. S., Irfan, M., Alqhtani, S., & Hamdi, M. (2021). A hybrid feature selection framework for predicting students performance. Computers, Materials and Continua, 70(1), 1893-1920.
5. Saeed, A., Habib, R., Zaffar, M., Quraishi, K. S., Altaf, O., Irfan, M., … & Almushayti, Z. (2021). Analyzing the Features Affecting the Performance of Teachers during Covid-19: A Multilevel Feature Selection. Electronics, 10(14), 1673.