ARPAN PRAMANIK
Arpan Pramanik — AI/ML Engineer & Full-Stack Developer
ENGINEERED WITH RIGOR.
Read Background & DossierAutonomous AI Agents
Multi-step agentic orchestrators with tool integration, streaming citation tracking, and low-latency API consolidation.
Grounded Retrieval (RAG)
Dual-pipeline hybrid architectures pairing memory-speed BM25 + FAISS with persistent remote pgvector storage.
Production Web Systems
Full-stack enterprise platforms with distributed tracing, RBAC JWT auth, and microsecond edge rendering.
FLAGSHIP ARCHITECTURES.
PaperLens AI
2026Autonomous full-stack AI research platform for literature analysis, experiment planning, problem ideation, gap detection, citation intelligence, and benchmark discovery.
JalDrishti (जलदृष्टि)
2026Climate-smart precision agronomy and irrigation advisory platform engineered for Indian smallholders combining FAO-56 Penman-Monteith physics, root-zone depletion tracking, and Groq-native multilingual AI.
ACADEMIC RESEARCH.
FruitQ-GradeX: Determining Fruit Quality and Grading with Explainable Deep Learning
This paper presents a novel multi-task deep learning framework for simultaneous fruit classification and quality assessment using a multi-headed Convolutional Neural Network (CNN). The proposed model achieves state-of-the-art performance on a curated dataset of four Indian fruits (apple, banana, guava, and orange) with two quality classes (good and bad), achieving 98% accuracy in fruit classification and 99% accuracy in quality detection with Grad-CAM visual heatmaps.
Hyperspectral Fruit and Vegetable Classification Using Convolutional Neural Networks with EfficientNetB3
Deep learning has revolutionized the fruits and vegetables classification in the food and farming sectors. This study presents an EfficientNetB3 model trained on a comprehensive Kaggle dataset of 36 distinct agricultural classes, achieving 99.29% training accuracy and 97.21% test accuracy. Using transfer learning and real-time predictions with Streamlit and OpenCV, the model enables automated sorting and quality inspection in supply chain logistics.
LET'S ENGINEER SOMETHING EXCEPTIONAL.
Available for AI/ML engineering roles, autonomous agent architectures, full-stack systems, or applied research consultations.