Founding member and Group Product Lead of Appian's Site Reliability Engineering group. We ensure Appian's systems are available, observable, reliable and performant.Lead Performance & Reliability Team, designing and implementing a cloud-native observability systems (distributed tracing, metrics & logging), built on Kubernetes using a Prometheus, Thanos/Cortex, Jaeger & ELK.Received Corporate Impact Award for delivering Appian's next-generation cloud-native Monitoring and Alerting stack. Apply data science to detect and remediate performance issues, architect automated analysis correlating 100k+ unique metrics and monitoring tools.Using FlameGraphs to debug performance issues and applying USE/RED methods to systematically identify capacity bottlenecksDevelop performance testing and analysis frameworks. Evangelize performance-focused design of software and systems architecture by mentoring and advising teams as part of the Engineering Performance Office.Champion SRE and DevOps practices, improving incident management and remediation process.

Lead Performance & Reliability Team, to design and implement cloud native observability systems (distributed metrics & log collection), built on Kubernetes using a Prometheus, Grafana and ElasticSearch.Apply data science to detect and remediate performance issues, architect automated analysis correlating 100k+ unique metrics and monitoring tools.Develop performance testing and analysis frameworks. Evangelize performance-focused design of software and systems architecture by mentoring and advising teams as part of the Engineering Performance Office.Champion SRE and DevOps practices, improving incident management and remediation process.

Technical Lead overseeing all engineering aspects, including architecture, infrastructure and backend design, managing team of developers; driving fast development and delivering on deadlines. Designed and implemented secure HIPAA­ compliant, horizontally scalable architecture and backend API, building a fast, efficient and secure CORRIE Platform.

Research on GPU-accelerated Computational Optics for Atmospherically Distorted Telescope Images, High-Performance GPU-accelerated Astronomy Catalog Cross-Matching, Low-power ARM supercomputing devices and other topics related to analyzing, processing and extracting meaning from large volumes of data.Dissertation title: "Data Fusion at Scale in Astronomy" - Combining computational methods and techniques to gain big data insights. Topics covered include computational optics, machine learning, time series analysis and search.

Developed and deployed a performance regression testing framework to automatically measure, analyze and detect performance changes of the Cloudant Database as well as other related services. Including development of full-stack automation, a "repeatable" load driver and an automated statistical analysis tool which can make statistically-sound performance assertions across different versions, environments and use cases.

Developed a performance testing and analysis framework for IBM's Rational Jazz Platform (JTS/CCM). Automating and Integrating this test framework into the continuous delivery pipeline for performance testing and regression detection. Developed and deployed a set of interactive performance reports featuring dynamic/interactive graphing and various statistical analysis for tracking build over build product performance.

Spearheaded the creation of MakePlayLive's official community surrounding the Mer & Plasma-Active based Vivaldi tablet. (defunkt, Vivaldi failed to come to market)

Completed development on the GPU-accelerated Time Series search engine. Added numerous features, supplementing search results with metadata from AAS publications database. Developed a GPU-accelerated Time Series template matching engine which allows for rapid identification of Trans-Neptunian Objects in the SEDNA region, by matching changes in brightness of background stars. This work was supervised by Dr. Pavlos Protopapas.

Continuing development on a GPU accelerated Time Series search engine for astronomical time series, under the supervision of Dr. Pavlos Protopapas.funded by NSF Grant # CDI‐0835713

Finished development on a Astronomic Time Series Search engine, at http://osiris.seas.harvard.edu/searchtime/searchengine [defunct as of 2011]. Started development on a GPU accelerated implementation of the search engine. The projects was lead by Dr. Pavlos Protopapas and was continued as an NSF funded "Research Experience for Undergraduates" (REU)In parallel I built a web crawler backend for a visualizations application for the Scientist Discovery Room lead by Dr. Chia Shen.

Automotive servicing and repair as well as Gas Attendant and Clerk