Rohan Gautam
MCA Student
Turning ideas into impactful digital solutions
About Me
My Journey
I'm a dedicated MCA student at CHRIST (Deemed to be University) with a passion for creating innovative digital solutions. My journey in technology began during my BCA at Amity University Jharkhand, where I developed a strong foundation in computer science.
I specialize in Machine Learning, Deep Learning, and Full-Stack Development. My experience ranges from developing AI-powered applications to creating responsive web solutions that make a real impact.
I believe in continuous learning and staying updated with the latest technologies. Whether it's implementing neural networks for computer vision or building scalable web applications, I'm always excited to tackle new challenges.
Education Timeline
Master of Computer Applications (MCA)
Specializing in Software Development, Machine Learning, and Deep Learning
Bachelor of Computer Applications (BCA)
Graduated with strong foundation in computer science fundamentals
Skills & Expertise
Constantly learning and evolving with the latest technologies to build innovative solutions
Technical Skills
Soft Skills
Problem-solving
Analytical thinking and creative solutions
Leadership
Leading teams and driving projects forward
Teamwork
Collaborative approach to achieve common goals
Adaptability
Quick learning and adapting to new technologies
🎯Currently Learning
Advanced Deep Learning techniques, Computer Vision with OpenCV, and exploring cutting-edge AI/ML frameworks for real-world applications.
Experience
Building real-world solutions and gaining practical experience in software development
Software Developer Intern
MECON Limited
Developed an intelligent chatbot system using cutting-edge AI technologies to enhance user interaction and support.
🏆Key Achievements
- •Developed and deployed Nexora AI, a full-stack intelligent chatbot platform using ReactJS, TailwindCSS, FastAPI, MySQL, and ChromaDB.
- •Integrated LLaMA 3.2 (via Ollama) with Retrieval-Augmented Generation (RAG) to enable context-aware and session-based conversations with persistent chat history.
- •Delivered a production-ready solution adopted by MECON, streamlining internal query handling and improving employee productivity.
🚀Looking for New Opportunities
I'm actively seeking internship and full-time opportunities where I can contribute my skills in software development, machine learning, and AI while continuing to learn and grow in a collaborative environment.
Projects
Showcasing innovative solutions that demonstrate my technical skills and problem-solving abilities
AI Resume Analyzer
An intelligent resume analysis tool that helps optimize resumes for Applicant Tracking Systems (ATS) using advanced AI algorithms.
Key Features:
- •90% accuracy in ATS compatibility scoring
- •Real-time keyword optimization suggestions
Full Stack Chatbot
A sophisticated conversational AI chatbot built with React frontend and Python backend, integrating modern LLMs for intelligent responses.
Key Features:
- •Real-time conversation capabilities
- •Context-aware AI responses
Automatic Table Allotment System
A smart web application for automatic table allocation in restaurants and events, built with React.js and Firebase.
Key Features:
- •Real-time table availability tracking
- •Smart allocation algorithms
Alphabet Prediction using ML
Deep learning model for handwritten alphabet recognition using Convolutional Neural Networks (CNN) with high accuracy prediction.
Key Features:
- •95% accuracy on test dataset
- •Real-time handwriting recognition
Publications
Research contributions in Machine Learning, Deep Learning, and AI applications
Enhancing Handwritten Alphabet Prediction with Real-time IoT Sensor Integration in ML
International Journal of Computer Science and AI
This research presents an innovative approach to handwritten alphabet recognition by integrating IoT sensors with machine learning algorithms. The study demonstrates significant improvements in accuracy and real-time performance through sensor fusion techniques.
Keywords:
Exploration of Hyperparameter Tuning in Handwritten Digit Recognition using CNN
Journal of Deep Learning Applications
A comprehensive analysis of various hyperparameter tuning strategies for Convolutional Neural Networks in handwritten digit recognition, providing insights into optimal configurations for different datasets and computational constraints.
Keywords:
Let's Connect
I'm always open to discussing new opportunities, collaborations, and interesting projects. Feel free to reach out!
Get in Touch
Whether you have a project in mind, want to collaborate, or just want to say hello, I'd love to hear from you. Let's create something amazing together!
Currently Based In
Bengaluru, India (Open to remote opportunities)