Projects
I did numerous projects which spans across the area of Machine Learning, Natural Language Processing, and Computer Vision covering AI for Healthcare, LLMs, Cybersecurity, Edge AI, Biomedical usecases, and Machine Learning with IoT.
SwiftUI
Object Capture
Photogrammetry
LiDAR
USDZ
ARScaner is a SwiftUI-based iOS application that harnesses Apple's Object Capture and Photogrammetry APIs to perform real-time 3D reconstruction. By integrating LiDAR sensor data with multi-view stereo algorithms, it generates detailed USDZ models from captured image sequences, offering superior accuracy and resolution compared to traditional camera-only scanning methods.
Raspberry Pi 4B x3
Temperature and Humidity sensors
YOLO
Python
Smart Fridge monitors your fridge about temperature and
humidity, alerts you when food is about to expire, or when
someone steals your food. In addition, it can generate a
recipe based on items in the fridge with the help of OpenAI
API.
MedConvFormer : Hybrid CNN-Transformer to Distinguish COVID-19, Normal, and Pneumonia from chest X-ray images
Python
EfficientNet-B0
Vision Transformer (ViT)
Implemented a novel hybrid deep learning architecture that
uniquely combines the strengths of Convolutional Neural
Networks (CNNs) and Vision Transformers (ViT) for medical
image classification.
Python
Langchain
LangGraph
llama.cpp
Optimized a high-performance RAG pipeline (Corrective RAG)
utilizing the Llama-3.2-3B LLM, achieving a 70% reduction in
memory requirements (from 12GB to 3.5GB) using 8-bit
quantization (llama.cpp backed) while maintaining 99.5% of
the original model's performance.
OpenCV
CLIP Embeddings
YOLOv8
QdrantDB
Developed an end-to-end computer vision system combining
YOLOv8 for real-time refrigerator detection, CLIP embeddings
for feature extraction, and Qdrant vector database for
similarity search.