MS Data Science @ UC Irvine • Building what matters
My journey in software engineering has been driven by a deep curiosity for how technology transforms industries. From building enterprise-grade distributed data platforms in banking at Barclays, to deploying scalable AWS data pipelines for geospatial analytics, to pushing the boundaries of computer vision research at UC Irvine — each experience has deepened my conviction that great software engineering is about understanding the domain as deeply as the code.
I discovered my passion for engineering during my undergraduate years at SRM, where building my first distributed system showed me the elegance of solving complex problems through thoughtful architecture. This led me to Cognizant and MAQ Software, where I learned the discipline of enterprise-scale development. At Ford, I saw how automation and intelligent systems could transform manufacturing workflows. At Barclays, I experienced the rigor demanded by financial systems processing millions of transactions daily.
Now pursuing my MS in Data Science at UC Irvine, I'm at the intersection of my two greatest interests — scalable systems and artificial intelligence. Whether it's designing event-driven architectures, building ML pipelines, or crafting multi-agent AI systems, I'm energized by problems that require both engineering depth and creative thinking.
View Full ResumeEvent-driven systems, microservices, distributed platforms, cloud-native design
ML pipelines, LLMs, multi-agent AI systems, computer vision research
Medallion architecture, Kafka streaming, ETL pipelines, analytics platforms
AWS infrastructure, Terraform IaC, Docker, Kubernetes, CI/CD pipelines