Ph.D. in Computer Science with expertise in machine learning, data engineering, and biomedical analytics. Passionate about bioinformatics, cancer genomics, and precision medicine through data-driven discovery.
Data scientist and researcher with deep expertise in machine learning, data engineering, and biomedical data analysis. My work spans from designing deep learning models for IoT security to building healthcare analytics platforms and implementing scalable data pipelines using Microsoft Fabric and PySpark for financial institutions. I am driven to advance bioinformatics and genomic research — focusing on computational genomics, cancer biomarker discovery, and precision medicine.
Building end-to-end data solutions on Microsoft Fabric; designing Power BI dashboards with complex DAX, developing SQL/PySpark pipelines, and optimising data processing workflows at scale.
Data cleaning, statistical modelling, forecasting, and cross-functional reporting to support operational decision-making.
Teaching Database Systems, Cloud Computing, Networking, OS, IT Project Management, Algorithm Design, and Research Methods. Supervised master theses on IoT optimisation and leukemia ML detection.
Implemented ML models, risk assessment frameworks, and end-to-end analytics solutions for business intelligence reporting.
End-to-end unified analytics platform — from data ingestion and lakehouse architecture to real-time intelligence and Power BI reporting. Proficient in designing Fabric workspaces, Dataflows Gen2, Notebooks, and Lakehouse pipelines for enterprise-scale financial data.
Reviewer for Journal of Supercomputing and IEEE journals. Top Student Award, Islamic Azad University 2023.