Research
Exploring the intersection of AI, formal methods, and enterprise systems to solve real-world challenges.
My research centers on bridging the gap between formal methods and practical software engineering. I investigate how graph-based representations, AI agents, and automated verification can improve how we design, analyze, and optimize complex business processes and enterprise systems.
Business Process Mining & Analysis
Formal verification of BPMN models using graph theory and Linear Temporal Logic for deadlock and livelock detection.
Agentic AI & Multi-Agent Systems
Orchestrating specialized AI agents through coordinated pipelines for complex reasoning and automation tasks.
Graph Databases & Knowledge Graphs
Leveraging graph-based representations for enterprise data modeling, semantic analysis, and process mining workflows.
Enterprise Systems & ERP
Designing scalable enterprise architectures using microservices, three-tier patterns, and cross-module integration.
Information Security & Steganography
Exploring Vision Transformer approaches for high-fidelity data hiding with enhanced residual learning.
Computer Vision & Image Processing
Applying object detection, recognition, and satellite imagery analysis for agricultural and environmental monitoring.
Software Architecture & Design
Investigating architectural patterns including microservices, clean architecture, event-driven systems, and scalable distributed application design.
DevSecOps & Infrastructure
Integrating security practices into CI/CD pipelines, container orchestration, infrastructure automation, and continuous monitoring for production systems.
LLM-Based Blockchain Verification
Applying Large Language Models with Chain-of-Thought reasoning and RAG for automated verification of digital financial applications on Ethereum protocol.