About
Master Student & Computer Engineer.
I am currently pursuing an Erasmus Mundus Joint Master Degree in Medical Imaging and Applications coordinated by the university of Girona, Spain, with a grant from the European Union.
I hold a Bachelor's Degree in Computer Engineering from Eskisehir Technical University, Turkey. I graduated on June 2021 with First Class Honors after 5 years of undergraduate
studies as a "Turkiye Burslari" scholar. During my studies, I had the chance to do an exchange semester at
Liepaja University, Latvia. My graduation project was entitled "EduFERA: A Real-Time Student Facial Emotion Recognition Approach" and supervised by Dr. Burcu YILMAZEL. I worked as part-time candidate researcher at TUBITAK YTE for the period January 2020 - August 2021 after a successful summer internship at the same Institute.
My research interests are Medical Image Analysis and Artificial Intelligence, focusing on Deep Learning and its applications in medecine.
Skills
Programming
Python, Java, C++, MatLab, R, JavaScript, PHP
AI and Computer Vision
PyTorch, Sci-kit Learn, Pillow, OpenCV, Keras, Simple ITK
Web and Mobile development
Spring Boot, Laravel, Flask, ReactJS, Bootstrap, Android, Flutter
Database Management
MySQL, SQLite, PostgreSQL, SQL
Resume
Find my complete CV here...
Summary
Kaouther MOUHEB
B.Sc. in computer engineering, M.Sc. student in medical imaging and applications.
- Girona, Spain
- +39 347 462 5976
- u1976922@campus.udg.edu
Education
Master in Medical Imaging & Applications
2021 - 2023
University of Girona, University of Burgundy, University of Cassino and Southern Lazio
Erasmus Mundus Joint Master Degree
Current grade: 29,52/30, Current rank: 1/25
Bachelor of Computer Engineering
2016 - 2021
Eskisehir Technical University
Graduated as Valedictorian on June 2021
Grade: 3.99/4
Experience
Graduate Research Intern
Jul-Aug 2022
ViCOROB Lab, UdG, Girona
- Supervised by Robert Marti
- Worked with a team on Breast Density Estimation using Federated Learning.
Candidate Researcher
Jan-Aug 2021
TUBITAK Software Technologies Research Institute, Ankara, Turkey
- Project: Expenses Management Systems of the Turkish Ministry of Treasury and Finance.
- Participated as a Full-Stack developer in designing a software system based on the micro-service architecture following the domain driven design paradigm.
Undergraduate Research Intern
Sep 2020 - Jan 2021
ESTU Electrical and Electronics Engineering Department
- Supervised by Cihan Topal.
- Worked on developing an automatic system for face liveness detection during online meetings based on unisotropic diffusion and deep learning.
Software Development Intern
Jun-Aug 2020
TUBITAK Software Technologies Research Institute, Ankara, Turkey
- Developed an event management system for the institute with a Spring Boot based backend, a React-based web front-end and a PostgreSQL database.
Web Development Intern
Jun-Aug 2019
Dypix, Boumerdes, Algeria
- Developed a web-based interactive educational tool for children using Laravel, MySQL and Bootstrap.
Projects
Skin Lesion Segmentation and Classification
We addressed the tasks of skin lesion segmentation and classification using two approaches, a classical pipeline using advanced image processing techniques and traditional machine learning, and a deep learning-based method. [Code]
Alzheimer’s Patient Classification
A comparative study of different statistical learning approaches on 3 different tasks of Alzheimer’s patient classification based on MRI and gene expression data. The best models were submitted for the Statistical Learning Challenge at Cassino University. Challenge Winner for the ADCT task. [Code]
Heart Axes Detection
Worked within a team during the third "Datacare AI Santé Datathon" on detecting the main axes of the heart from MRI images by combining deep learning-based segmentation and image processing techniques. Supervised by Sarah Leclerc and Alain Lalande.
SMS Spam Filter for Turkish
A Machine Learning Method for SMS spam detection for the Turkish Language. Final Project for the Pattern Recognition course @ESTU. [Code]
Movies Recommender System
A simple similarity-based recommender system of movies with a web interface. The problem was addressed in two different ways: user-wise similarity and item-wise similarity. Final project for the Data Aquisition and Processing course @ESTU. [Code]