Michael Gump is a Co-Founder at Aviad. He possess expertise in python, pandas, tensorflow, data analysis. Colleagues describe him as "Michael was selected for a summer internship at The Aerospace Corporation. Even though he was only a first year student, it became quickly apparent that his abilities far exceeded our expectations for his summer. Our plans centered around performing an investigation into the use of microservices to automate the processing chain of a complex, synchronous workflow. We were specifically interested in the application of horizontal scaling of compute infrastructure vs. vertical scaling through faster, more capable processors. With very little guidance, Michael was able to create an experiment using Amazon Web Services' Lambda microservice, combined with the power of the open source TensorFlow machine intelligence library, to prove significant utility of microservices and horizontal scaling. Michael's thorough investigation, coupled with his ability to work with little guidance made this investigation a great success. His efforts were recognized by senior management as well as project management. Michael's efforts didn't stop there, however; because he finished the project much sooner than expected, we developed two other experiments for Michael to investigate. The first was an investigation into the relative differences in network latency within regions in Amazon Web Services. In this experiment, Michael worked from the hypothesis to create his own test harness to extract the necessary data for the study. In his third investigation, Michael researched open source security code analysis tools. Again, given only a hypothesis, Michael was able to compile a list of security analysis tools, then performed direct comparisons of the tools using a code baseline with known security vulnerabilities to assess each systems' efficacy. He also verified compliance of the code analysis tools with the Common Vulnerabilities and Exposure database, the recognized database of security vulnerabilities in software. In all, we were extremely pleased with the self-starter attitude, the functional knowledge of how to apply the engineering method, and his attention to detail. The analyses Michael performed were extremely relevant to the research and customer focus areas of The Aerospace Corporation and were received very well by both Aerospace technical and program management."