A highly skilled software and ML engineer and with over one year of experience in full-stack and iOS app development, and system design and deployment. Proficient in designing and optimizing deep learning models, particularly in medical imaging and NLP. Experienced in leading teams, mentoring interns, designing systems, and developing web and mobile applications for professional medical environments. Explore my resume below and contact me if my experience aligns with your needs.
Last updated March 2025.
Developed the system design and led the development of a full-stack web platform for oral cancer detection. Managed a team of five interns, delegating tasks and driving project milestones to completion. Architected and implemented a new version of the platform, applying software development best practices. Built the platform with FastAPI, React, MySQL, and Docker, ensuring scalability and robust performance. Developed secure authentication and authorization using the OAuth2 protocol, and custom row-level access control. Created an iOS app in Swift, enabling lesion identification through on-device models and patient report generation. Developed a complete user study and associated web application with survey design, data collection, and statistics. Collaborated with doctors, professionals, and researchers from universities and hospitals from over six countries. Designed, optimized, and tested various deep learning models for the diagnosis of oral cancer lesions. Contributed to papers, including in system design and usability testing, for submission in conferences worldwide.
Contributed to the development of a Flask-based social media analytics platform, deployed with Kubernetes. Integrated Angular frontend, utilizing RxJS and NgRx for reactive state management. Enhanced frontend query validation with Angular validators and resolved bugs to improve efficiency. Developed and executed unit tests for backend functions using Python’s unittest framework.
Graduated with Distinction. Key Courses: Information Retrieval, Deep Learning, Text-as-Data (NLP), Big Data, HCI, Human-Centered Security. Thesis: Implementation and Evaluation of a Language Server for the Fun Programming Language
GPA 3.83 out of 4.00. Graduated with High Distinction. Dean’s List for six semesters. Key Courses: Algorithms, Data Structures, Databases, Web Development, Operating Systems, Machine Learning. Thesis: Bayan: Towards an Effective Arabic Fatwa Search Engine
In Hammoudeh, M., Alessa, A. T., Sherbeeni, A. M., Firth, C. M., Alessa, A. S. (Eds.),
Quantum Computing: A Journey into the Next Frontier of Information and Communication Security.
CRC Press. ISBN: 978-1-032-75705-6
Developed an Arabic search engine for Islamic jurisprudence queries using Flask, PyTorch, JavaScript, and SQLite. Trained a transformer-based re-ranking model, outperforming all prior submissions with a macro F1 of 81.5%. Surpassed Google Search’s results by obtaining an NDCG@10 score of 0.93 on the test set. Engineered a system to extract, score, and annotate answers from webpages using a corpus in real-time. Led the web development efforts and built features including user management, search history, and preferences. Deployed the application using NGINX and Gunicorn, employing SQLite for data storing, caching, and logging.
Developed a language server for a custom programming language using Java, Maven, LSP4J, and TypeScript. Engineered language parsers and visitors using ANTLR, enhancing functionality. Implemented error and warning highlighting features, along with intelligent auto-completion suggestions. Conducted user studies resulting in a 42% improvement in coding efficiency and 100% in coding effectiveness.
Developed a full daily routine application, a flag listing and filtering application, and various other applications. Used Swift and SwiftUI to create native user interfaces adhering to Apple’s Human Interface Guidelines. Integrated Core Data and SwiftData into applications for efficient data management across applications.
Fine-tuned a RoBERTa model, achieving 86.2% accuracy and a macro F1 of 82.0% in classifier comparisons. Developed a CNN and fine-tuned a ResNet50 model to classify cancer cell images with 98% accuracy.
Developed and actively maintain a full stack blogging engine with a custom content delivery network and RSS feed. Created the blog frontend for viewing and backend for posting using Flask, Jinja, and SQLite.
Utilized Unity and C# to develop 2D platformer games and a 3D obstacle course game for Windows and Android. Currently learning Godot and utilizing GDScript to develop a 2D platformer game for Windows and macOS.