Tsunami Prediction System
Built an AI-based tsunami early warning system using Arduino UNO R3 and Deep Neural Networks. Implemented real-time disaster prediction and alert mechanisms.
Yuvaraj J
AI Automation Engineer
Rajapalayam, Tamil NaduArtificial Intelligence and Machine Learning
2roles
21skills
3education
About
Enthusiastic and dedicated individual with strong communication and problem-solving skills, passionate about guiding and supporting students in their learning journey. Possesses a solid academic background in Computer Science along with patience, adaptability, and a keen interest in creating an engaging learning environment.
Experience
AI Automation Engineer
CodingRim Technology and Private Limited
Feb. 2026 – Jun. 2026
Worked on real-time AI automation projects involving frontend and backend development. Gained hands-on experience in AI automation workflows, integration, and deployment concepts. Learned AI-based video editing techniques and contributed to long-term live projects.
Intern
V-CODEZ
Apr. 2025 – Jun. 2025 · On Site
Worked across the complete machine learning workflow including data cleaning, model development, and performance evaluation. Applied deep learning techniques on NLP and image datasets to strengthen practical AI skills.
Education
Kalasalingam University
Bachelor of Technology, CSE
2021 – 2025
CGPA: 7.2/10.0
Sri Ramana Vidyalaya Montessori Matric Higher Secondary School
Intermediate, State Board
2020 – 2021
84.15%
Sri Ramana Vidyalaya Montessori Matric Higher Secondary School
High School, State Board
2018 – 2019
83.6%
Skills
JavaCPythonCommunicationProblem SolvingHTMLCSSSQLMachine LearningDeep LearningNatural Language ProcessingImage Data AnalysisAI AutomationFrontend DevelopmentBackend DevelopmentData CleaningModel DevelopmentPerformance EvaluationFlaskArduino UNO R3Predictive Modeling
Projects
Prediction and Diagnosis of Alzheimer’s
Utilized deep learning techniques to predict protein structures for early Alzheimer’s diagnosis. Evaluated model accuracy and optimized prediction performance.
AI-Driven Phytoremediation
Developed a Flask-based application for predicting soil contaminant reduction efficiency. Implemented predictive AI models for phytoremediation analysis and performance evaluation.