Publications
Peer-reviewed papers, thesis, and technical blog posts.
Papers & Thesis
WildfireVLM: AI-powered Analysis for Early Wildfire Detection and Risk Assessment Using Satellite Imagery
Presents WildfireVLM, an AI-driven framework for early wildfire detection and risk assessment using satellite imagery. Demonstrated at the 3rd Wildfire Digital Twin Semi-Annual Review at UMBC in front of scientists from NASA.
SOTA Results in Agentic Memory on LongMemEval
Achieved state-of-the-art performance on the LongMemEval benchmark with 86% accuracy, surpassing the previous best by 15%, using a long-term memory system for conversational agents.
SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval Augmented Generation
Proposes SBI-RAG, a framework combining schema-based instruction with retrieval augmented generation to improve mathematical word problem solving capabilities in students using LLMs.
Dynamic Edge Weighting in Relational Graph Convolutional Networks: Enhancing Sample Efficiency via Graph Attention in Reinforcement Learning
MS thesis presenting a novel approach to enhancing model-free RL algorithms by integrating graph attention networks into an R-GCN framework, achieving a 20% improvement in sample efficiency on Boxworld and Minigrid LavaGap benchmarks.
ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents
Presents ReProHRL, a hierarchical reinforcement learning framework for multi-goal navigation, transferring from simulation to real-world robotic environments with an 85% transfer success rate.
Toward Real-World Implementation of Deep Reinforcement Learning for Vision-Based Autonomous Drone Navigation with Mission
Explores the practical deployment of deep RL for autonomous drone navigation in real-world environments using vision-based inputs and YOLO object detection, bridging the Sim2Real gap.
Peer-Reviewing Experience