Full Stack Engineer
Current from June 2019
Backend development on learning management systems (LMSs) involving REST API interactions and LTI integrations.
Backend development on a workflow-based auto-grading service offering portability and interoperability with a variety of LMSs.
Frontend development on UIs for LTI tools that integrate with an LMS, supporting analytics dashboards, grade submissions, and learner feedback.
April 2014 -- June 2019
Designed and wrote the SDN controller and RESTful API for the NSF-funded project, DANCES.
Created NOC-oriented web applications to display monitored network measurements, utilizing Web10G metrics.
Designed a NoSQL schema for storing TCP flow metrics in InfluxDB, a time series database, and integrated it with data visualization web applications.
Aug. 2013 -- April 2014
Coordinated with systems and business administrators to roll out a new degree audit system to 7,000+ users.
Helped transition from a legacy in-house system to a 3rd party Oracle solution by writing conversion tools and replacing Perl scripts with PL/SQL scripts.
Jan. 2013 -- Aug. 2013
Wrote bash and PL/SQL scripts to support application data flows
Student System Administrator
Created education materials and configured two Beowulf clusters for Computer Science curriculum use.
M.S., Computer Science
B.S., Computer Science
I am a research developer with experience writing C and Python back-ends, storing telemetry data in noSQL databases, and writing web front-ends using JS frameworks.
I work at Carnegie Mellon University currently working with the TEEL Lab to develop and deploy the SAIL Platform and Curriculum.
I previously worked at the Pittsburgh Supercomputing Center researching high performance networking, focusing on Software Defined Networking and the evolution of the TCP/IP stack.
During my graduate and undergraduate studies I focused on high performance computing. I built several Beowulf clusters to provide Slippery Rock University with more distributed environments for curriculum use. I utilized those resources to develop reference implementations of common distributed algorithms using MPI and GPGPU programming techniques.
"Developing Applications with Network Capabilities via End-to-End SDN"Article No. 29
"Developing Applications with Network Capabilities via End-to-End SDN"
"Parallel Computing Methodologies with GPGPU and Classroom Integration"
"Parallel Computing with GPGPU Technologies"
Deep Learning Specialization