About
Highly motivated Computer Science Engineering student with a strong foundation in Full-Stack Development, AI, and Data Science. Proven ability to develop impactful applications and systems, as demonstrated by projects achieving 95%+ accuracy in AI models and 40% latency reduction. Seeking to leverage technical expertise and problem-solving skills to contribute to innovative teams in the technology sector.
Work
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Summary
Led the full-stack development of an IoT-based agriculture management mobile application with integrated AI-powered disease detection capabilities.
Highlights
Developed a comprehensive IoT-based agriculture management mobile application using React Native and Expo, enhancing farm efficiency.
Built an integrated plant disease detection system utilizing a CNN deep learning model with 95%+ accuracy, identifying 38 disease classes.
Developed a Flask REST API for plant disease detection, supporting 38 disease classes with dual input methods for robust data handling.
Implemented real-time weather monitoring with hourly/daily forecasts, humidity, wind speed, and precipitation tracking, providing critical agricultural insights.
Designed and developed a modular component architecture with reusable UI components and a consistent styling system, improving maintainability and scalability.
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Summary
Currently engaged in a 6-month Data Science internship at Sabudh Foundation, focusing on developing core skills in SQL, machine learning, deep learning, and NLP through structured training and hands-on practice.
Highlights
Developing core competencies in SQL, machine learning, deep learning, and Natural Language Processing (NLP) through structured training.
Gaining practical experience through expert sessions and hands-on project implementation in data science methodologies.
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Summary
Led the front-end development of a React Native solar panel management application, integrating IoT hardware APIs.
Highlights
Led the development of a React Native solar panel application, enhancing user interface and experience.
Integrated IoT hardware APIs with caching strategies, successfully reducing data latency by 40% for improved performance.
Collaborated effectively with hardware engineers to resolve complex API integration challenges, ensuring seamless system functionality.
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Summary
Developed a Python-based multi-modal intelligent chatbot system, focusing on RAG-based document processing and AI integration.
Highlights
Built a RAG-based document processing system, enabling efficient and context-aware information retrieval.
Integrated 4 AI providers (Groq, OpenAI, Anthropic, Ollama) with robust API management for diverse natural language processing capabilities.
Created a document retrieval system for PDF, DOCX, and TXT files, supporting context-aware Q&A functionalities.
Implemented secure API key management with named references and provider selection, ensuring system security and flexibility.
Optimized UI/UX with responsive design and improved interface elements, enhancing user engagement and accessibility.
Education
Skills
Programming Languages & Databases
Python, Java, JavaScript, SQL, HTML/CSS.
Frameworks & Libraries
React Native, Flutter, BeautifulSoup, Flask, Numpy, Pandas, Scikit-learn, TensorFlow, Keras, PyTorch, NLTK, SpaCy.
Developer Tools
Git, Postman, Figma, VS Code, Jupyter Notebooks.
Other Tools
Microsoft Office, Excel, Word, Canva.
AI & Machine Learning
Deep Learning, Natural Language Processing (NLP), Computer Vision (CNN), Generative AI, RAG (Retrieval-Augmented Generation), AI Model Integration, API Management.
Web Development
Full-Stack Development, Front-End Development, REST API Development, UI/UX Optimization, Responsive Design, Component Architecture.
IoT
IoT Hardware Integration, Real-time Monitoring, Data Latency Reduction.
Problem Solving
API Integration Challenges, System Optimization, Context-aware Q&A.