MirAI 2.0 – Personal AI Assistant
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Summary
Developed a lightweight AI desktop assistant using PySide6, integrating multiple Large Language Models (LLMs) and productivity tools for enhanced user experience and task automation.
About
Highly motivated and results-driven AI/ML Developer with a strong academic foundation (CGPA 8.55/10) and practical experience in building and deploying intelligent systems. Adept at leveraging Python, TensorFlow, and scikit-learn to develop innovative solutions, as demonstrated by leading projects like MirAI 2.0 (30% faster UX, 200% productivity boost) and DeceptiNet (80% accuracy in fraud detection). Eager to apply advanced machine learning and deep learning expertise to solve complex challenges in a dynamic technical environment, contributing to cutting-edge AI development.
Education
VIT Bhopal University
Bhopal, Madhya Pradesh, India
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Bachelor of Technology
Computer Science and Engineering (Specialization in AI - ML)
Grade: 8.55/10
Awards
Amazon ML Summer School 2025 Selectee
Awarded By
Amazon
Selected for the Amazon ML Summer School 2025, an exclusive program for only 3,000 students across India, gaining exposure to advanced ML concepts and real-world applications.
National Semi-Finalist, Flipkart GRID 7.0
Awarded By
Flipkart
Achieved National Semi-Finalist status in the Flipkart GRID 7.0 (2025) national-level competition, recognized for outstanding technical achievement and problem-solving capabilities.
2nd Place, University-Level Robotics and Coding Competition
Awarded By
University Competition
Secured 2nd Place in a highly competitive university-level Robotics and Coding Competition, demonstrating strong programming and algorithmic skills.
Certificates
Blockchain Developer Certification
Issued By
IBM Career Education Program
MERN Full Stack Developer Certification
Issued By
Ethnus via Codemithra
Applied Machine Learning in Python
Issued By
University of Michigan via Coursera
Skills
Programming Languages
Python, C++, Java.
Machine Learning Skills
TensorFlow, Keras, PyTorch, Scikit-learn, OpenCV, Pandas, NumPy, Matplotlib, NLTK.
Web Development
HTML5, CSS3, Tailwind CSS, JavaScript, React.js, Node.js, Express.js, Django, MySQL.
Developer Tools
VS Code, Google Collab, Jupyter, Git, GitHub.
Projects
DeceptiNet – Real-Time Digital Deception Detection System
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Summary
Engineered a real-time digital deception detection system leveraging advanced AI techniques to identify fraud across various digital content types including apps, clickbait, and fake news.
Real Time Emotion Detector
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Summary
Developed and optimized a real-time emotion detection system using a custom TensorFlow CNN and OpenCV for accurate facial emotion recognition from webcam input.