Senior Software Engineer | Lead Enterprise Data Platform Architecture | AI/ML Systems Specialist
Recognition for groundbreaking work in AI systems and neural network architectures.
Distinguished recognition for exceptional achievements in data science and analytics.
Recognition of technical achievement and professional contribution in computing.
Distinguished recognition of scientific research achievements and contributions.
Fellowship recognizing leadership in cloud computing architecture.
Service as technical judge evaluating global innovation and excellence.
I am a Senior Software Engineer specializing in secure AI/ML and scalable cloud solutions for mission-critical applications. My expertise spans automating CI/CD processes with Python, Scala, Ansible, and Terraform, utilizing Docker in AKS and EKS environments. My work delivers significant reductions in operational costs and vulnerabilities while improving product delivery efficiency through team collaboration.
Currently at 7-Eleven's Data Innovation & Monetization Division, I architect and optimize enterprise data platforms, cloud infrastructure, and machine learning systems serving retail locations processing millions of weekly transactions.
Beyond industry work, I maintain an active research profile with peer-reviewed publications, multiple professional fellowships, and service as a judge for international conferences. My research interests encompass AI governance, cloud security, real-time data systems, and sustainable computing architectures.
Peer-reviewed research contributions spanning AI systems, cloud computing, emergency response, network virtualization, optimization methods, and emerging technologies. Over 17 publications with significant citations.
Advances in stream data processing through tensor decomposition techniques for efficient data compression and real-time analytics.
View on DOI →Novel approach to automated data lakehouse architecture with self-healing capabilities for improved data reliability and availability.
View Paper →Proposes cryptographic solutions for secure data sharing and coordination in emergency response systems across multiple agencies.
View Publication →Develops real-time optimization algorithms for EV charging infrastructure, balancing grid stability with economic efficiency.
View Article →Presents algorithms and techniques for dynamic resource optimization in multi-cloud environments with cost-benefit analysis.
View Article →Develops ML-based predictive models for identifying and mitigating supply chain disruptions in complex logistics networks.
View on IEEE →Explores gamification strategies and metaheuristic approaches for optimizing logistics routing in smart cities.
View on IEEE →Comparative analysis of emerging technology-enhanced learning methodologies using advanced evaluation frameworks.
Investigates advanced optimization techniques for improving efficiency in metal cutting and manufacturing processes.
Applies advanced optimization methodology to improve properties and performance of sustainable polymer composites.
Develops pedagogical frameworks and evaluation methodologies for computer-mediated learning environments.
Analyzes key factors influencing digital payment adoption and barriers in emerging markets.
Evaluates NFV architectures for flexible network service delivery using advanced multi-criteria decision analysis.
Comprehensive analysis of autonomous drone applications across industrial sectors using comparative decision-making methods.
Develops frameworks for automated monitoring and control systems using advanced optimization techniques.
Comprehensive analysis of e-commerce ecosystems combining data analytics, environmental assessment, and socioeconomic evaluation.
Proposes data-driven investment strategies for improving digital connectivity and communication infrastructure in underserved regions.
Full research profiles and publications:
Google Scholar |
ResearchGate |
ORCID |
Academia.edu
Proposes cryptographic solutions for secure data sharing and coordination in emergency response systems across multiple agencies.
Presents algorithms and techniques for dynamic resource optimization in multi-cloud environments with cost-benefit analysis.
Develops ML-based predictive models for identifying and mitigating supply chain disruptions in complex logistics networks.
Issued and pending patent applications spanning AI systems, quantum computing, financial technology, and enterprise automation.
Advanced optical neural network architecture utilizing silicon photonic technology for ultra-low latency financial decision-making and high-frequency trading applications.
Federated learning framework for secure, distributed sensor data fusion and anomaly detection in critical infrastructure systems with privacy preservation and cryptographic security.
Real-time risk assessment and intelligence system for trade finance operations across complex, multi-modal supply chain networks using advanced analytics and machine learning.
Hybrid quantum-photonic computing architecture for accelerating complex financial derivatives pricing calculations, combining quantum and optical computing advantages.
Intelligent data pipeline orchestration system that optimizes both performance and environmental impact by integrating real-time renewable energy availability and carbon-aware scheduling.
Novel forecasting system utilizing chaos theory and optical reservoir computing to predict financial market dynamics with high-dimensional signal processing for improved accuracy.
Novel approach to controlling and optimizing large language model outputs through semantic graph structures and adaptive policy frameworks for enterprise applications.
Comprehensive automation governance system developed during tenure at Verizon. Provides policy enforcement, compliance management, and governance automation across enterprise infrastructure.
Additional patent applications pending. Details available upon request.
Advanced optical neural network architecture utilizing silicon photonic technology for ultra-low latency financial decision-making.
Hybrid quantum-photonic computing architecture for accelerating complex financial derivatives pricing calculations.
Novel forecasting system utilizing chaos theory and optical reservoir computing to predict financial market dynamics.
Recognition of professional excellence, scholarly contribution, and industry leadership.
Recognition for innovation and leadership in artificial intelligence technologies.
Distinguished recognition for exceptional achievements in data science and analytics.
International recognition of professional contribution and technical excellence.
Recognition for innovation in technology solutions.
Recognition for excellence in enterprise data platform development and deployment.
Recognition for technical excellence and contribution to critical infrastructure.
Serve as technical judge and evaluator for international AI innovation awards.
Serve as technical judge and evaluator for international technology innovation awards.
Recognition for excellence in retail data platform innovation.
Kubernetes & Cloud: Certified Kubernetes Administrator (CKA), Microsoft Certified: Azure Administrator Associate, AWS Certified Solutions Architect - Associate
Data & Analytics: Data Science Associate (EMCDSA), Six Sigma Black Belt Certification
Education: Master of Science, Technology Management, University of Bridgeport (2017)
Lead architect for enterprise data platform modernization. Key achievements: Orchestrated cloud migration strategy with 25% efficiency improvement; Implemented containerization achieving dramatic operational gains; Achieved 80% reduction in vulnerabilities; Led team improving operational efficiency by 30%; Deployed new technologies enhancing real-time traffic responsiveness by 35%.
Optimized server management and Kubernetes containerization. Key achievements: Reduced response time by 50%; Achieved 99.9% uptime; Led Kubernetes initiatives reducing infrastructure costs by 25%; Reduced deployment time by 30%; Automated operations improving system performance by 15%.
Designed and implemented scalable CI/CD systems. Key achievements: Integrated Python with Jenkins and Kubernetes; Addressed deployment errors and optimized delivery timelines; Analyzed performance under various operating conditions.
Administered RHEL and SUSE systems specializing in automation. Key achievements: Managed UNIX servers with automation tools; Implemented VMware and Solaris Zones; Managed storage devices including RAID and SANs; Hardened solutions with security technologies.
Master of Science, Technology Management | University of Bridgeport, Connecticut (2017)
Certifications: Certified Kubernetes Administrator (CKA), AWS Solutions Architect Associate, Microsoft Azure Administrator, Six Sigma Black Belt, EMCDSA Data Science Associate
I'm interested in discussing research collaboration, speaking opportunities, consulting engagements, and emerging challenges in cloud computing, AI systems, and enterprise data platforms. Please share your contact information below, and I'll reach out to you promptly.
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