Harsh Tailor

Led a team to study and implement insights from a novel EEG cognition assessment model. Executed data preprocessing and analysis using MNE and SVM, improving model accuracy and applying advanced EEG signal processing techniques to enhance data quality.

Developed a game that tracks body landmarks in real-time, allowing players to control the game by swiping at virtual fruits, implementing dynamic difficulty levels based on performance.

Completed a course covering front-end, back-end, and database integration, focusing on essential skills for developing applications. Engaged in milestone assessments and projects to enhance coding and project management skills.

Developed an ensemble learning model for EEG-based cognition assessment, employing various methods to improve accuracy and robustness. Included preprocessing steps and visualized data to show collaboration.

Created a centralized database management system for student and staff data, automating attendance and grades for efficient performance monitoring.

Annotated and categorized large datasets, including images, text, or audio, to train machine learning models. Ensured that annotations met Samsung’s high standards and contributed to iterative improvements by providing feedback on model performance.

Pursuing a Bachelor of Engineering in AIML (Artificial Intelligence and Machine Learning), focusing on advanced concepts in AI and machine learning applications.

Completed Pre-University Course (PCMC), which included subjects such as Physics, Chemistry, Mathematics, and Computer Science, laying a strong foundation for engineering studies.