Full Stack Developer | Cloud Architect | IEEE Published Researcher
Senior Full Stack .NET Developer and Cloud Engineer with 10+ years of experience architecting scalable enterprise applications, distributed systems, and cloud-native platforms using ASP.NET Core, AWS, Kubernetes, and Terraform. IEEE-published researcher focused on cloud computing, AI-driven system reliability, and secure digital infrastructure.
Full Stack .NET Developer with nearly a decade of experience designing, modernizing, and securing mission-critical enterprise systems in high-compliance industries, including healthcare and enterprise services.
I specialize in ASP.NET Core, microservices architecture, distributed systems, AWS cloud-native solutions, Kubernetes-based containerization, and DevOps automation, building scalable platforms that support millions of users.
I have extensive experience transforming legacy enterprise applications into resilient, cloud-native environments on AWS, enhancing scalability, reliability, and security. My work also explores AI-driven system reliability and advanced cloud computing strategies.
I hold a Master’s degree in Computer Science and am currently based in the Chicago area.
An IEEE-published researcher in AI/ML, cloud computing and cybersecurity, I actively contribute to advancing secure and scalable digital systems through innovative research and publications.
I mentor aspiring professionals through Women in Tech and IEEE Women in Engineering, advocating for equitable access and representation in STEM.
A journey through my career in software development and AI, showcasing growth and expertise in full-stack technologies and artificial intelligence.
WEX Health Inc.
Experience designing, developing, and deploying fault-tolerant, scalable, and resilient microservices using C#, SQL, .Net Core, and AWS services.
Benefit Express
Developed and maintained .NET applications, enhancing client support and platform efficiency. Implemented security features and optimized performance across multiple benefit platforms.
Antra
Developed .NET applications improving client satisfaction and system reliability. Led production support, implemented SSO authentication, and optimized SQL performance while establishing monitoring solutions to reduce system downtime.
The growing complexity of urban data management in smart cities necessitates innovative solutions that balance predictive accuracy, scalability, and privacy. This paper proposes a novel framework that integrates Federated Learning (FL), Blockchain, and Foundation Models (FMs) to address these challenges. By leveraging FL, data is processed locally on edge devices, ensuring that sensitive information remains private and secure, while the predictive power of FMs enhances real-time decision-making across urban systems. Blockchain technology ensures transparency and trust, providing an immutable ledger for secure governance and operations. The proposed system enables seamless collaboration across diverse data sources while preserving privacy and fostering a decentralized, resilient infrastructure. A practical use case in inventory management and sales forecasting for businesses within a smart city is presented, showcasing how this framework can enhance operational efficiency, reduce costs, and maintain high standards of data protection. This integrated approach sets a new standard for secure, adaptive, and efficient smart city management.
Read PaperThe scarcity of high-quality labeled network data poses a significant challenge for machine learning applications in cybersecurity and traffic analysis. This study presents a novel approach leveraging diffusion models to generate high-fidelity synthetic network traces, preserving critical structural and statistical properties of real-world traffic. By employing an optimized fine-tuning pipeline, controlled generation constraints, and automated post-processing techniques, the framework en-sures compliance with network protocols while enhancing model performance in classification tasks. Experimental evaluations demonstrate that the generated data achieves strong statistical alignment with real traces and serves as an effective augmentation tool for AI-driven network analysis. This research highlights the potential of generative AI in improving data availability for secure communications research.
Read PaperConventional security systems find it hard to safeguard a company from the growing, complex cyber threats. The study assesses several algorithms on their effectiveness in identifying cyber intrusions and the performance of the machine learning techniques used in the process. It can compare different contexts with true external events and measure its capability of distinguishing normal network activities from identifying networks with abnormal behavior. The report highlights the advantages and limitations of Artificial Intelligence (AI) in internet protection solutions. It points to how a monitoring framework can be organized in a better way.
Read PaperThe rapid growth of modern software ecosystems has resulted in massive, globally distributed code repositories, creating significant challenges in efficient indexing, retrieval, and structural analysis. Existing repository mining tools often struggle to scale, lack deep code structure correlation, or provide limited support for multi-language analysis. This paper introduces SearchSECO, a distributed, language-agnostic search and analysis engine designed for large-scale software repository mining. The system integrates a modular architecture comprising a high-throughput crawler for metadata harvesting, a parallel retriever for repository acquisition, and hybrid parsers leveraging both srcML and custom ANTLR grammars for precise method-level extraction. A distributed Apache Cassandra backend ensures scalable, fault tolerant storage, while a high-performance networking layer enables low-latency client-server communication. Experimental evaluations on diverse open-source datasets demonstrate the system’s ability to process millions of methods across thousands of repositories with near-linear scalability. By linking methods, authors, and version histories across projects, SearchSECO enables advanced cross-repository analytics for vulnerability detection, clone identification, and software evolution studies. This work contributes to the fields of software engineering and repository mining by delivering an extensible framework that combines scal- ability, accuracy, and adaptability to emerging programming languages and repository platforms.
Read Paper
IEEE Women in Engineering (WIE), Treasurer Role, Chicago Section
Supporting professional development, STEM outreach, and technical mentoring initiatives to empower women and girls in technology.
Professional certifications, awards, and recognition received throughout my career in software development.
Amazon Web Services
Dec 2023 - Dec 2026
CertificationValidates expertise in designing distributed systems on AWS, including compute, networking, storage, and database services. Demonstrates ability to architect secure and robust applications on AWS technologies.
2024
CertificationCompleted comprehensive specialization in .NET full stack development, covering frontend and backend technologies, APIs, databases, and modern development practices.
IEEE Chicago Section
Ongoing
MentoringSupporting professional development, STEM outreach, and technical mentoring initiatives to empower women and girls in technology through IEEE Women in Engineering Chicago Section.
IEEE
Ongoing
RecognitionRecognized as IEEE Senior Member for significant performance and contributions to the profession. Active member of IEEE Chicago Section, contributing to professional development and community initiatives.
2024
CertificationCompleted Google Analytics certification course, demonstrating proficiency in web analytics, data analysis, and digital marketing measurement strategies.
GenAI.Works
2025
CertificationLearned to make decisions tailored to business constraints, understand when & how to apply AI effectively & build a multi-agent application. Covered RAG, evals, agents, MCP, multi-agents, and context engineering.
IEEE
Ongoing
RecognitionActive member of IEEE Young Professionals, engaging in professional development activities, networking opportunities, and contributing to the advancement of technology and engineering.