Research
Research Interests
Primary
Social and Information Network Analysis
Deep Learning, Data Mining, Anomaly Detection
Scientometrics
Secondary
Prediction
Recommender Systems
Machine Learning
Research Experience
My primary research interest is in mining social and information networks. I have sound experience of studying evolution structure, semantics, and diffusion analysis among multi-typed objects in these networks. My research concentrates on exploring heterogeneous information networks for modeling novel problems and proposing scalable and efficient algorithms for real-world applications that include but not limited to anomaly detection, recommender systems, academic ranking, information diffusion analysis, influence analysis, scientometrics, and informetrics.
My masters research work emphasis on detecting novel type of anomalies in bibliographic networks. Their dynamic nature necessitates and poses a challenge to detect evolution-based anomalies. Likewise, it is investigated that how the objects influence each other in the heterogeneous network. It has applications in social media analytics, education, business, and bioinformatics. Currently, the focus of my research work is on modeling and using deep learning techniques to extract meaningful insights from social networks.
Research Grants
2020
Funding Agency: Deanship of Scientific Research, University of Jeddah, Jeddah, Saudi Arabia
Funding: 30, 000 SAR (10, 000 SAR/project)
Title: Measuring the Impact of COVID-19 Surveillance Variables over International Oil Market Grant Number: UJ-20-DR-044
Title: Indexing Important Drugs from Medical Literature, Grant Number: UJ-20-DR-047
Title: Measuring Impact of Co-author Count on Citation Count of Research Publications, Grant Number: UJ-20-DR-048