Lokesh R

Results-driven B.Tech Information Technology graduate (2026) with practical, hands-on experience in front-end development, full-stack web applications, and machine learning. Proficient in HTML, CSS, JavaScript (ES6+), React.js, Bootstrap 5, Python, and MySQL, with a solid command of responsive design, REST API integration, and component based architecture. Successfully completed an ML internship delivering an NLP-driven real-world application.

Skilled in Figma-based UI/UX wireframing, Agile/Scrum workflows, and Git-based version control. A fast learner with strong analytical and problem-solving abilities, eager to contribute to high-impact software products at leading IT organizations.

Machine Learning Intern - Vcodez Innovating Ideas Pvt Ltd

(2025-07 - 2025-08)

Project: Mental Health Detector — NLP & Sentiment Classification System | Python, Scikit-learn, NLTK, spaCy, Pandas

• Engineered an end-to-end NLP-based Mental Health Detection system using Python, NLTK, spaCy, and Scikit-learn, achieving approximately 85% classification accuracy across multiple sentiment categories.
• Preprocessed and cleaned 5,000+ raw text records through tokenization, stop-word removal, stemming, and TFIDF vectorization, improving model training efficiency by an estimated 30%.
• Designed, trained, and benchmarked three ML classification models — Logistic Regression, Naive Bayes, and Support Vector Machine (SVM) — evaluating each using accuracy, precision, recall, and F1-score to select the optimal model.
• Built robust data pipelines for seamless feature extraction, model inference, and real-time prediction workflows, reducing manual analysis effort by approximately 60%.
• Generated actionable visualizations of emotional trends and model performance metrics using Matplotlib and Seaborn, enabling clear data-driven insights for stakeholders.

B.Tech - Information Technology - Arunai Engineering College (2022 - 2026)