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MSc Computer Science (Data Analytics) graduate with a strong foundation in Python, data analysis, and machine learning, along with hands-on experience in NLP and LLM-based systems. Developed end-to-end applications involving data processing, intelligent automation, and user-facing interfaces. Interested in building scalable, data-driven and AI-powered solutions for real-world problems.
Digital University of Kerala
M.Sc. · Computer Science – Specialization in Data Analytics
August 1, 2024 – Present
Christ College (Autonomous)
B.Sc. · Physics
August 1, 2021 – June 30, 2024
UVJ Technologies
AI Intern
February 18, 2026 – June 9, 2026
Thrissur, Kerala, India
Invoice & Expense Summarizer
June 18, 2026 – Present
Built an AI-powered invoice processing system using OCR and RAG for structured data extraction and natural language querying. Implemented semantic search and validation pipelines, with an interactive dashboard for financial insights.
Speech Emotion Recognition
June 18, 2026 – Present
Developed a deep learning system to recognize emotions from speech using a hybrid CNN-BiLSTM model. Achieved 86% accuracy on the CREMA-D dataset using mel spectrogram features and data augmentation.
Near Real-Time News Sentiment Analysis System
June 18, 2026 – Present
Built a near real-time system to analyze sentiment of news headlines from multiple sources. Enabled continuous updates and visualization to monitor sentiment trends.
Hospital AI Assistant - Multi-Agent Conversational System
February 18, 2026 – May 9, 2026
Developed a multi-agent AI system enabling natural language interaction with appointment booking, symptom triage, and LLM-based intent routing. Integrated RAG-based medical responses, session memory with flow continuation, real-time scheduling with automated notifications, and voice interaction support.
Introduction to Git and GitHub
Unknown
June 1, 2026 – Present
Google Cloud Career Launchpad - Data Analytics Track
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in applying AI to practical problems, aligning well with an innovative and solution-oriented culture. The diversity of projects (conversational AI, emotion recognition, invoice processing, sentiment analysis) suggests adaptability and a broad interest in AI applications. The ongoing Master's degree indicates a commitment to continuous learning. However, the lack of team-based projects or explicit collaboration details makes it difficult to fully assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-component systems, suggesting good problem-solving and integration skills. The focus on end-to-end applications implies an understanding of operational deployment, though specific soft skills like teamwork or leadership are not explicitly detailed in the provided data.