Projects

A sensor-aware adaptive extension of LGCP-based barrier coverage that reweights trajectory intensity toward low-detection paths conditioned on sensor deployment, enabling realistic modeling of evasive adversarial targets (drones, UAVs). From β = 0 to β = 5, the adaptive-aware method degrades by only 0.084 vs. 0.297 for the baseline, yielding ~11% fewer expected missed trajectories at β = 5.

DroneSeg is a full-stack semantic segmentation platform for drone/aerial imagery. Upload drone photos, run SegFormer-B2 deep learning inference to generate land-cover classification masks with bounding boxes and visualize results on an interactive map and GeoJSON export. This is an MVP application built for demo.

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.

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.

Implemented the VCFP (Voice Command Fingerprint) attack and BuFLO defense to analyze voice assistant network traffic, showing how encrypted packets can reveal voice commands and how BuFLO mitigates this traffic analysis.

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.

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.

ALTM has Agentic Routing (PageIndex), Dynamic Importance Decay, and Automated Memory Merging to ensure your agents remember what matters and forget what doesn't.

A research project exploring automated generation of chest X-ray diagnostic reports using various Vision-Language Models (VLMs) and CNN backbones with distillation and finetuning.

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.

Early and Late Fusion techniques for multimodal hateful meme classification by integrating visual features from pretrained CNNs with textual features from pretrained BERT models.

Implemented Early Fusion with BiLSTM, CNN, and LSTM+CNN and Late Fusion by concatenating the output of BiLSTM, CNN, and BiLSTM+CNN.

Designed a control sequencer incorporating a 6-bit ring counter to facilitate efficient loading of two data values into registers. Integrated user-friendly buttons for voting and ensured accurate tallying and display of results in real time.

Developed an AI-based-voice controlled over-the-internet Automatic Warehouse Switching and Monitoring system. Real-time Weather Monitoring and Forecasting system.