Mina Atef Yousef Wahba

Mina Atef Yousef Wahba

LLM | Deep Learning | Machine Learning

Posts by Collection

industry

Software Engineer for Security Programs

From: To:

  • Designed and developed security projects in C#.
  • Built scalable websites using Django REST framework, HTML, and JavaScript.

Vulnerability Management Specialist

From: To:

  • Conducted vulnerability assessments and implemented patch management solutions.
  • Ensured server integrity by monitoring system health and resolving security issues.

Vulnerability Management and Patching Specialist

From: To:

  • Conducted vulnerability assessments and implemented patch management solutions.
  • Managing and addressing vulnerabilities across various servers, including conducting thorough vulnerability assessments using nessus.
  • Managing Servers, Printer, Laptops and Handling IT problems.

SQL & Power BI Developer

From: To:

  • Built real-time data analysis pipelines using SSIS, SQL, and Power BI.
  • Automated dashboards and conducted advanced statistical analysis with DAX.

Software Engineering Backend

From: To:

  • Developed web applications using Django and FastAPI frameworks.
  • Managed deployment on Linux servers.
  • Refactored legacy databases and integrated modern API solutions.

publications

Natural Language Processing: Text Categorization and Classifications

Published in International Journal of Advanced Networking and Applications, Vol. 12, Iss. 2, 2020

This paper covers advanced techniques for text categorization and classification using NLP methods.

Recommended citation: Mona Nasr, Andrew Karam, Mina Atef, Kirollos Boles, Kirollos Samir, & Mario Raouf. (2020). "Natural Language Processing: Text Categorization and Classifications." International Journal of Advanced Networking and Applications. Vol. 12, Iss. 2.

Deep Learning Approaches for Analyzing Visual Stimuli from Human fMRI

Published in Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), International, IEEE, 2022

This paper discusses the use of deep learning techniques for analyzing visual stimuli from human fMRI.

Recommended citation: Andrew Karam, Kirollos Boles, Mario Raouf, Mina Atef Yousef, & Ghada Khoriba. (2022). "Deep Learning Approaches for Analyzing Visual Stimuli from Human fMRI." MIUCC, IEEE.

Generating Application Traffic Data from Tax Data: A Synthetic Data Approach

Published in NetMob 2023 Data Challenge, Madrid, Spain, 2023

This project introduces a synthetic data approach for generating application traffic data from tax data.

Recommended citation: Tamer Arafa, Noha Gamal, Ghada Khoriba, Mina Atef Yousef, & Ahmed El-Mahdy. (2023). "Generating Application Traffic Data from Tax Data: A Synthetic Data Approach." NetMob 2023 Data Challenge, Madrid, Spain.

Désordre: A Framework for Real-Time Detection and Prediction of Social Unrest and Catastrophes Using Mobile Data Traffic

Published in NetMob 2023 Data Challenge, Madrid, Spain, 2023

This framework focuses on real-time detection and prediction of social unrest using mobile data traffic.

Recommended citation: Noha Gamal, Mina Atef Yousef, & Ahmed El-Mahdy. (2023). "Désordre: A Framework for Real-Time Detection and Prediction of Social Unrest and Catastrophes Using Mobile Data Traffic." NetMob 2023 Data Challenge, Madrid, Spain.

Predicting the Productivity Indicators of a Society Using Workforce Behavior Dynamics

Published in NetMob 2023 Data Challenge, Madrid, Spain, 2023

This project predicts productivity indicators based on workforce behavior dynamics.

Recommended citation: Noha Gamal, Tamer Arafa, Mina Yousef, & Ahmed El-Mahdy. (2023). "Predicting the Productivity Indicators of a Society Using Workforce Behavior Dynamics." NetMob 2023 Data Challenge, Madrid, Spain.

BeGrading: Large Language Models for Enhanced Feedback in Programming Education

Published in Neural Computing and Applications, 2024

This paper explores the application of LLMs to provide enhanced feedback in programming education.

Recommended citation: Mina Yousef, Kareem Mohamed, Walaa Medhat, Ensaf Hussein Mohamed, Ghada Khoriba, & Tamer Arafa. (2024). "BeGrading: Large Language Models for Enhanced Feedback in Programming Education." Neural Computing and Applications. 1-14. IF 4.8.
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Hands-on Analysis of Using Large Language Models for the Auto Evaluation of Programming Assignments

Published in Information Systems, 2024

This paper investigates the use of LLMs for automatic evaluation of programming assignments.

Recommended citation: Kareem Mohamed, Mina Yousef, Walaa Medhat, Ensaf Hussein Mohamed, Ghada Khoriba, & Tamer Arafa. (2024). "Hands-on Analysis of Using Large Language Models for the Auto Evaluation of Programming Assignments." Information Systems. 102473. IF 3.0.
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Optimizing Real-Time Data Processing in Resource-Constrained Environments: A Spark and GPU-Driven Workflow for Large Language Models

Published in 2024 IEEE International Conference on Future Machine Learning and Data Science (FMLDS), 2024

This paper explores a Spark and GPU-driven workflow for efficient real-time data processing of LLMs.

Recommended citation: Mina Yousef, Ghada Khoriba, & Tamer Arafa. (2024). "Optimizing Real-Time Data Processing in Resource-Constrained Environments: A Spark and GPU-Driven Workflow for Large Language Models." IEEE FMLDS 2024.
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research

talks

Talk 1 on Relevant Topic in Your Field

From: To:

This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!

teaching

Teaching Assistant Experience at Nile University

Undergraduate Course, Nile University, Department of Computer Science

From: To:

  • Delivered courses in Artificial Intelligence, including Machine Intelligence, Computer Vision, and 3D Computer Graphics.
  • Participated in quality accreditation activities to enhance the academic standards of the institution.
  • Automated administrative workflows to improve operational efficiency.
  • Oversaw server rooms and workstations to ensure seamless operation for educational and research purposes.
  • Actively contributed to research initiatives and participated in the NetMob 2023 Data Challenge.