Harshit Mehan
B.Tech Data Science student with hands-on experience in Python, SQL, data analysis, and machine learning. Built practical projects involving data preprocessing, ETL pipelines, predictive modeling, and AI-powered applications through internships and academic work. Strong problem-solving skills with a focus on developing practical data-driven solutions.
- Developed Cyber Defense Copilot, an AI-powered cybersecurity assistant using Python and Streamlit.
- Implemented AI-driven modules for SOC analysis, phishing detection, vulnerability assessment, incident response, and security assistance.
- Integrated Google Gemini API and developed AI-agent workflows, report generation, visualization, testing, and debugging.
- Developed an ETL pipeline using Python and Pandas for extracting, transforming, and preparing data for analysis.
- Performed data preprocessing and analysis on real-world datasets to prepare data for machine learning tasks.
- Built and evaluated machine learning models using Python and Scikit-learn.
- Worked on practical data science tasks involving classification, optimization, and application development.
• Developed an AI-powered cybersecurity assistant using Python and Streamlit. • Built modules for SOC analysis, phishing detection, vulnerability assessment, incident response, and Linux security assistance. • Integrated Google Gemini API for AI-driven cybersecurity analysis and recommendations. • Implemented security report generation and threat visualization features.
• Developed an emotion detection system using deep learning and NLP to classify user emotions from text. • Implemented BiLSTM and BERT-based approaches for emotion classification. • Integrated AI-generated personalized learning guidance based on detected emotional states. • Developed an interactive Streamlit interface for emotion analysis and learning support.
• Developed an AI-powered application to simplify legal information and assist users with legal queries. • Integrated Google Gemini API for natural-language processing and AI-generated responses. • Built the application using Python and Streamlit with a modular backend architecture. • Designed the system to provide accessible, user-friendly legal assistance.