Research Portfolio Publications, Papers & Academic Contributions
Advancing AI & Technology Through Research
Bridging the gap between theoretical research and practical applications. My research focuses on cutting-edge AI/ML techniques, with particular emphasis on real-world implementations that drive business value and societal impact.
Research Domains
Artificial Intelligence & Machine Learning
Deep learning architectures, neural networks, and intelligent systems for real-world applications.
Computer Vision & Image Processing
Advanced image recognition, object detection, and visual intelligence systems.
Natural Language Processing
Language models, text analysis, and conversational AI systems for enterprise applications.
Process Automation & Optimization
Intelligent automation systems, workflow optimization, and business process enhancement.
Publications & Research
AI-Powered ERP Assistant: Bridging Natural Language and Enterprise Systems
This paper presents a novel approach to enterprise resource planning through natural language interfaces, achieving 85% efficiency improvements in business process automation. Our system combines transformer-based models with domain-specific knowledge graphs to enable intuitive ERP interactions.
Real-Time Multi-Object Detection for Enhanced Security Surveillance
We propose an optimized YOLO-based architecture for real-time multi-object detection in surveillance systems, achieving 98% accuracy while maintaining 30fps processing speed on standard hardware configurations.
Multilingual Conversational AI: Context-Aware Chatbots for Global Enterprise
This study presents a novel framework for developing context-aware multilingual chatbots that maintain conversation quality across 15+ languages while adapting to cultural nuances and business contexts.
AI-Driven Business Process Optimization: From Theory to Implementation
Keynote presentation covering practical implementation strategies for AI-driven business process optimization, featuring real-world case studies and ROI analysis from 15+ enterprise deployments.
Federated Learning for Privacy-Preserving ERP Analytics
We introduce a federated learning framework for ERP systems that enables collaborative machine learning while preserving data privacy across multiple organizations, achieving comparable performance to centralized models.
Efficient Edge AI Deployment for Real-Time Image Processing
This paper explores optimization techniques for deploying computer vision models on edge devices, achieving 70% reduction in model size while maintaining 95% accuracy.
Research Impact & Analytics
Publication Timeline
Citation Trends
Research Domains Distribution
Collaboration Network
Interested in Collaboration?
I'm always open to research collaborations, academic partnerships, and innovative projects that push the boundaries of AI and technology. Let's explore how we can work together to create impactful research.