ABIR HENTATI

– Topic: Emotion detection with wearable devices – Exploration and integration of various physiological signal categories across multiple databases such as K-EmoCon. – Detection was extended beyond stress to include a wider range of emotions enhancing emotional state analysis. – New data preprocessing techniques such as temporal segmentation, FFT, and robust normalization were applied to improve machine learning model input quality. – Several classification models, including Transformer-based architectures, were evaluated and compared to identify the most accurate and robust emotion detection methods. – Using machine learning libraries such as scikit-learn and pandas – Data analysis and visualization

– Topic: Stress detection with portable devices. – Exploration and integration of various signal categories across multiple databases was experi-mented with. – Detection has been expanded beyond stress to include other emotions, deepening the analysis of emotional signals. – New data preprocessing techniques have been explored to improve the quality of machine learn-ing model inputs. – Several classification models were tested and their performances compared, making it possible to identify the most robust and precise methods for emotion detection.

– Topic:solve classification problems in different domains, using well-known datasets. – Develope and implemente several machine learning models – Data preprocessing and normalization – Managing class imbalance – Training and evaluation of classification models – Hyperparameter optimization – Using machine learning libraries such as scikit-learn and pandas – Data analysis and visualization

– Topic: Shoplifting – Led technical demonstrations for various projects, specializing in data slicing, segmentation, and annotation for a shoplifting initiative. – Managed daily operations for processing and annotating 800 high-quality items, ensuring precision and consistency. – Collaborated with team members to streamline workflows and enhance data quality for improved analytical outcomes.

– A desktop application designed for managing stores and restaurants... – Developed a user-friendly desktop application aimed at streamlining operations for stores and restaurants, enhancing efficiency and customer satisfaction. – Designed intuitive user interfaces (UI) and user experiences (UX) to facilitate ease of use and reduce training time for employees.

– Topic: Development of school daycare management software. – Designed and implemented a comprehensive system to manage daily operations of a school daycare. – Features include student enrollment, attendance tracking, billing, and activity scheduling. – Integrated user-friendly dashboards for staff and parents to monitor child progress, attendance, and billing history.

– Topic: Design of a database of shoplifting videos. – Coordinated the daily tasks of slicing, segmenting, and annotating 800 high-quality items for the shoplifting challenge. – Developed and structured a database to store and manage a large collection of shoplifting videos for analytical purposes. – Implemented a metadata tagging system to categorize videos based on various factors such as location, time, and type of incident. – Ensured efficient video retrieval by optimizing database queries and indexing techniques.

– Topic: Design and development of a food delivery website. – Optimized performance for high traffic with asynchronous database operations. – Overcame challenges in making the website fully responsive across various devices and browsers by utilizing modern CSS frameworks and extensive testing for compatibility.

– Analysis of a database from an IT services company called SBA-Software. – Cleaned, organized, and validated data to ensure accuracy and consistency for meaningful insights. – Applied SQL queries to extract and analyze data, identifying patterns in customer behavior and service usage.