New: “AI-guided vectorization for efficient storage and semantic retrieval of visual data” (Discover Artificial Intelligence, 2025) See highlight
New: “Data lakehouse: a survey and experimental study” (Information Systems, 2025) See highlight
Photo of Ahmed Harby

Database Systems & Intelligent Lakehouse Architectures

Ph.D. in Computing with expertise in data warehousing, data lakes, and lakehouse systems. Focused on intelligent ingestion, storage optimization, and metadata-driven analytics across structured, semi-structured, and unstructured data.

Data Lakehouse Intelligent Ingestion Metadata Optimization Cloud & Big Data
Google Scholar Publications

Work Experience

Database Administrator (DBA)

Providence Care — Kingston, ON, Canada • 2023–Present

Database administration, data migration/reformatting, and health information management & decision support.

Software Consultant

Queen’s University — Kingston, ON, Canada • 2022

Customized open-source applications, integrated research code, and taught efficient coding techniques.

Research Assistant

Queen’s University — Kingston, ON, Canada • 2020–2024

Data collection/analysis, literature reviews, prototyping, and implementation support across research projects.

Teaching Assistant

Queen’s University — Kingston, ON, Canada • 2020–2024

Supported courses in compilers, machine learning, and neural networks; mentored students on complex projects.

Assistant Lecturer & Teaching Assistant

Arab Academy — Cairo, Egypt • 2016–2020

Taught programming, operating systems, and AI topics; supervised innovative student projects.

Research Focus

Advancing database systems and large-scale analytics with lakehouse architectures that unify data lake flexibility and warehouse governance. Emphasis on adaptive ingestion pipelines, semantic/metadata-driven retrieval, and performance-aware storage management.

Interests:
  • Cloud Computing
  • Virtualization
  • Distributed Algorithms
  • Advanced Machine Learning
  • Databases
  • Blockchain
  • Data Warehouse
  • Data Lake
  • Data Lakehouse
  • Health Information Management
  • Big Data & Analytics
  • Information Management

Technical Skills

Programming

C, C++, C#, Python, Java, ASP.NET

Tools & Platforms

Visual Studio, PyCharm, Eclipse, Oracle Database, MATLAB, SSMS, Power BI, Databricks, Azure

Operating Systems

Windows, Ubuntu, Red Hat, Linux Mint

Key Strengths

Budget management, staff training & coaching, communication, composure under pressure, service orientation

Education

Ph.D., School of Computing, Queen’s University, Canada (2020–2025). M.Sc., Computer Engineering, Arab Academy, Egypt (2016–2019). B.Sc., Computer Engineering, Arab Academy, Egypt (2010–2015; ranked 1st).

Publications

Sorted newest to oldest. Full list on Google Scholar.

2025
Woo, M., Harby, A. A., Zulkernine, F., et al. A two-phase hybrid clustering framework exploring transitional activities in HAR Recent
Discover Artificial Intelligence, 5, 233, 2025. doi:10.1007/s44163-025-00503-6
2024
Harby, A. A., et al. Revolutionizing Healthcare Management: Architecture of a Web-based Medical Triage Service
2024 IEEE 48th Annual COMPSAC, Osaka, Japan, pp. 1887–1894. doi:10.1109/COMPSAC61105.2024.00299
2023
Harby, A. A., & Zulkernine, F. A Comparative Analysis of Graph Neural Networks for Fake News Detection
2023 IEEE 47th Annual COMPSAC, Torino, Italy, pp. 1215–1222. doi:10.1109/COMPSAC57700.2023.00184
2022
A. Harby & F. Zulkernine. From Data Warehouse to Lakehouse: A Comparative Review
2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, pp. 389–395. doi:10.1109/BigData55660.2022.10020719
Ibrahim, R., Harby, A. A., Nashwan, M. S., & Elhakeem, A. Financial Contract Administration in Construction via Cryptocurrency Blockchain and Smart Contract: A Proof of Concept
Buildings, 12(8), 1072, 2022. doi:10.3390/buildings12081072
2021
T. Abughofa, A. A. Harby, H. Isah, & F. Zulkernine. Incremental Community Detection in Distributed Dynamic Graph
2021 IEEE BigDataService, Oxford, UK, pp. 50–59. doi:10.1109/BigDataService52369.2021.00012
2019
A. A. Harby, S. F. Fahmy, & A. F. Amin. More Accurate Estimation of Working Set Size in Virtual Machines
IEEE Access, 7, 94039–94047, 2019. doi:10.1109/ACCESS.2019.2928221
View on Google Scholar

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