🎓 B.Tech CSE (AIML) @ The Neotia University | 📍 West Bengal, India
- 🤖 Building intelligent systems with TensorFlow, PyTorch & LangChain
- 🌐 Creating full-stack applications with the MERN stack
- 👁️ Developing CNN models for computer vision applications
- ☁️ Deploying scalable solutions on AWS, Render & Railway
- 🔌 Designing RESTful services with Node.js & FastAPI
- 🧠 Exploring LLMs, RAG pipelines & AI agents with Ollama & LangChain
Programming Languages
Frontend
Backend
Databases & Data Stores
AI/ML & Data Science
Cloud & Deployment
Data Formats & Datasets
Tools & IDEs
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Paper 1: FruitQ-GradeX: Determining Fruit Quality and Grading with Explainable Deep Learning
Shibdas Dutta, Subhrendu Guha Neogi, Diya Chanda, Arpan Pramanik, Özgün Girgin, Enes Ladin Öncül
DOI: 10.1109/ICRITO66076.2025.11241706
Multi-task deep learning framework for fruit classification and quality assessment using multi-headed CNN. 98% classification & 99% quality detection accuracy with Grad-CAM interpretability.
Paper 2: CropSense: Explainable Deep Learning Framework for Accurate Quality Detection in Solanaceous Crops
Shibdas Dutta, Subhrendu Guha Neogi, Shiladitya Chowdhury, Vikrant Chole, Arpan Pramanik, Diya Chanda
DOI: 10.1109/ICRITO66076.2025.11241535
Lightweight multi-headed CNN for potato and tomato quality classification. 99.9% crop classification & 98.5% quality detection accuracy with Grad-CAM, deployed via Streamlit.
Paper 3: An Explainable Deep Learning Approach for Quality Assessment in Solanaceous Crops
Shibdas Dutta, Barshan Adhikari, Arpan Pramanik, Diya Chanda
DOI: 10.1109/COMPUTINGCON64838.2025.11376762
Hybrid CNN-ViT model for simultaneous crop classification and quality assessment. Reduces parameters by 30%+. 98.45% potato & 97.49% tomato classification accuracy with 98.5% quality assessment.
| Domain | Skills |
|---|---|
| Machine Learning | Supervised/Unsupervised Learning, Feature Engineering, Model Optimization |
| Deep Learning | CNNs, Transfer Learning, Grad-CAM, Image Classification, Computer Vision |
| LLMs & AI Agents | LangChain, Ollama, RAG Pipelines, Prompt Engineering, Vector Search |
| Web Development | MERN Stack, RESTful APIs, Authentication, Admin Dashboards |
| Database Management | MongoDB, PostgreSQL, MySQL, Redis, Firebase, Vector DBs |
| Cloud & DevOps | AWS, Railway, Render, Vercel, Docker, Git/GitHub, CI/CD |
| Data Science | EDA, Data Visualization, Statistical Analysis, Pandas, NumPy |
| ✨ 15+ Machine Learning Projects | 🚀 10+ Production Deployments |
| 🎯 99.9% Model Accuracy Achieved | 💻 Full-Stack Development |
| 📊 Advanced Data Analysis | ☁️ Cloud Deployment Experience |
| 🔬 3 Published Research Papers | 🌐 RESTful API Development |
💼 Open to: Internships, Collaborations, Freelance Projects
⚡ "Code is like humor. When you have to explain it, it's bad." – Cory House