Research & Publications
Overview
Cloud architecture researcher with published peer-reviewed papers in algorithmic trading, distributed systems, and cloud-native messaging architectures. Active research focus on AI/ML integration, high-throughput systems, and next-generation cloud platforms.
Research Philosophy: Bridging the gap between theoretical models and practical implementation by conducting research in production environments and sharing actionable insights for enterprise architects and engineers.
Published Scholarly Articles
Integrating AI Agent Frameworks with Existing Microservices: An Adapter-Based Architecture for Enterprises (WIP)
Status: Work in Progress - Internal Review
Expected Publication: 2025
Research Contribution:
Novel architectural framework for integrating AI agent systems with existing microservices ecosystems, enabling enterprises to adopt intelligent automation through evolutionary rather than revolutionary modernization. Addresses critical challenges in authentication propagation, distributed tracing, security compliance, and performance optimization while supporting multiple AI agent frameworks (LangChain, Semantic Kernel, Agent Framework).
Key Innovations: - Hybrid architecture for AI-microservices integration with standardized adapter patterns - Validated design patterns for service wrapping and agent tool development - Production implementation in financial services sector with 40% reduction in API orchestration complexity - Comprehensive security evaluation confirming SOC 2 and PCI DSS compliance
Keywords: AI agents, microservices architecture, enterprise integration, large language models, API gateway, distributed systems, RESTful services, authentication propagation, tool calling, Model Context Protocol, LangChain, Semantic Kernel, financial services, software architecture patterns
AI-Driven Algorithmic Trading: Integrating Machine Learning, Hybrid Technical Indicators, and Risk Management for Momentum Strategies
Journal: International Journal of Engineering and Computer Science (IJECS)
Volume: Vol. 14 No. 11 (2025) | Published: November 24, 2025
DOI: https://doi.org/10.18535/ijecs.v14i11.5335
Research Contribution:
Novel integration of supervised machine learning with hybrid technical indicators (VWAP, MACD, RSI, Bollinger Bands) and dynamic risk management for momentum trading. Demonstrates 14% higher returns and 7% lower drawdown compared to conventional rule-based approaches, with Sharpe ratio improvement from 0.8 to 1.7.
Key Innovations: - Sub-second latency trading system with 67% accuracy (vs. 54% baseline) - Momentum-specific signal fusion with adaptive weighting - Integrated real-time risk management with momentum-aware controls - Comprehensive data validation across multiple market data providers
Keywords: Algorithmic trading, machine learning, momentum trading, technical indicators, risk management, hybrid signals, real-time systems, VWAP, artificial intelligence, quantitative finance
📖 Read Full Paper | 📥 Download PDF | 🔗 View DOI
High-Throughput Cloud-Native Messaging Architectures: Design and Performance Analysis of Pub/Sub Microservices with Kubernetes and Azure Event Hub
Journal: International Journal of Advance Research in Computer Science and Management Studies (IJARCSMS)
Volume: Vol. 13 Issue 11 | Published: 2025
DOI: https://doi.org/10.61161/ijarcsms.v13i11.1
Research Contribution:
Comprehensive empirical performance analysis of high-throughput cloud-native messaging architectures using Azure Kubernetes Service (AKS) and Azure Event Hub within a publish-subscribe model. Demonstrates how cloud-native designs effectively handle large-scale data ingestion and real-time event streaming with minimal latency while maintaining 99.9%+ reliability.
Key Findings: - Systematic evaluation of scalability, throughput, and latency under varying load conditions - Operational efficiency through Kubernetes auto-scaling and partition-based distribution - Best practices for integrating observability, security, and automation - Reference architecture for mission-critical enterprise applications
Keywords: Cloud-Native Architecture, Microservices, Kubernetes, Azure Event Hub, Messaging Architecture, Pub/Sub, Event-Driven Systems, Distributed Systems, High-Throughput Processing
📖 Read Full Paper | 📥 Download PDF | 🔗 View DOI
Research Interests
Primary Research Areas
- Cloud-native architecture patterns and distributed systems design
- Algorithmic trading systems with AI/ML integration
- Microservices design and event-driven architectures
- High-throughput messaging and streaming platforms
- Real-time data processing at enterprise scale
Emerging Research Focus
- AI agents for cloud operations and automation
- Performance optimization of Kubernetes-based systems
- Integration patterns for Azure OpenAI Service
- Next-generation platform capabilities (WebAssembly, serverless architectures)
Active Research Projects
Current Investigations
- AI-Powered Cloud Infrastructure Automation: Exploring intelligent agents for infrastructure management and optimization
- High-Performance Event Streaming: Advanced patterns for real-time data processing in financial services
- Cloud-Native Security: Zero-trust architecture implementations in Kubernetes environments
Research Impact
Academic Contributions
- Published in peer-reviewed international journals
- DOI-indexed publications for citation and verification
- Bridging gap between theoretical models and practical implementation
- Providing actionable insights for cloud architects and engineers
Industry Applications
- Real-world performance analysis from production environments
- Best practices for enterprise-scale deployments
- Reference architectures for mission-critical systems
- Compliance-aware designs for regulated industries (financial services)
Future Research Directions
- Advanced AI/ML Integration: Next-generation machine learning models for cloud optimization
- Edge Computing Patterns: Hybrid cloud-edge architectures for real-time processing
- Sustainable Cloud Computing: Energy-efficient architecture patterns for large-scale systems
- Financial Technology Innovation: Advanced trading system architectures with regulatory compliance
Collaboration Opportunities
Interested in collaborating on research in cloud architecture, distributed systems, or algorithmic trading?