• Intern with the National Security Internship Program (NSIP) which involves a technical paper and an oral presentation detailing the work completed over the internship• Analysis in Motion: Researching the implementation of an image inpainting algorithm on a streaming distributed GPU cluster using OpenCL to reduce latency and still maintain accuracy. Mentored by Dimitri Zarzhitsky.• Cyber Intelligence Center: Creating and optimizing Apache Spark scripts to improve data ingest and provide preliminary statistics about the dataset. Mentored by Bryan Gerber.

• Continuing automation work that was conducted during the internship, as well as working with Quality Assurance Engineers to refactor automation tools. • Utilizing Jenkins Continuous Integration to aid in automating running scripts and provide email capabilities.• Most of automation scripts are written in python.

• Spearheaded automation for testing of the Network Monitor tool.• Delegated tasks between myself and another engineering intern to achieve efficiency and balance team priorities. • Implemented five separate automation tests utilizing both python and bash scripting.

Funded through the National Science Foundation Research Experiences for Undergraduates program (NSF REU).• Goal: design a fault tolerance scheme for stateless message processing and compare performance with Apache Storm message processing guarantee. • Configure and install Apache Storm cluster on department machine• Testing fault tolerance message processing schemes using Apache Storm cluster as a benchmark.

Funded through the National Science Foundation Research Experiences for Undergraduates program (NSF REU).• Goal: provide an alternative way to predicting packet arrival using statistical analysis• Develop a multiple linear regression model to accurately predict when packets arrive from a medical sensor (EEG, ECG, and Thorax). • Utilizes scikit-learn package in python to generate the linear regression model with k-fold cross validation.

• CS 160 – “Foundations of Programming” recitations. Duties include tutoring students on programming concepts, the recitation, the homework or discrete mathematics; as well as leading and teaching the recitations.• Ratings: Conducted through survey monkey, total of eight questions were asked (1 to 4) with an optional comment section. Additional details available. Spring 2014: 3.64/4.00 and Fall 2014: 3.85/4.00

• Developed parsing scripts to synthesize and count the number of errors in an error file. The scripts produced a summary for the specific error file and an overall summary file of the entire design. • Received project team recognition award for merging two tools into one to create efficiency and usability as well as enabling broad adoption of a single tool set for designers. • Developed an automation script to reduce the number of specific errors in a design.

Through Apprenticeships in Science and Engineering program sponsored by the Saturday Academy• Ran upgrade tests on the Connex Vital Sign Monitor 6000 and gathered logs.• Created a C# program that analyzes and merges error and event logs from the CVSM6000 (Connex Vital Sign Monitor 6000). The enhancements made to the program increased understandability the system logs allowing for improved performance and debugging. Other features implemented include the ability to annotate events or errors in the logs as well as save application and session settings to ease the portability of the merged logs.• Developed a presentation and poster board explaining the project and presented at the Apprenticeships in Science and Engineering Symposium.