Hello! My name is Andrew Massey and I am a recent Computer Science graduate (August 2021) from the College of Engineering at the University of Oklahoma. I have been fortunate enough to be able to focus on a very important topic in my degree program — distributed systems. I know that being able to implement and utilize high performance, accurate systems on a massive scale will be important in every sector for the foreseeable future.
Skills and Technologies
My experience in distributed systems has given me a unique set of skills among other computer science graduates.
Through my courses and the management of my own home network using open source software, I am proficient in the following networking technologies and paradigms:
- IPv6 and IPv4 Dual Stack
- DHCP and IPv6 Prefix Delegation
- Secure DNS
- PFSense and Network Management
- Firewalls and Routing
- OSI Model
- Use of networks for distributed computing
- cURL, dig
My programming experience has been closely tied to high performance and distributed computing using languages and technologies such as:
- Nvidia CUDA GPU acceleration
- Message Passing Interface (MPI) on compute clusters/supercomputers
- Open Multi-Processing (OpenMP) for multi-core programming
- GitHub, git, IntelliJ
You can contact me at: [email protected]
Notable Educational Projects
magic – Cloud hosted Nginx based random number generator
The beginning of my capstone required that my team and I create a highly available random number generator accessible from a web browser. While the project was simple, it taught me a lot about how to spin up secure web servers that serve dynamic content. In this project, we used Nginx on a Google Cloud Platform virtual machine. To secure the site, I set up TLS using Lets Encrypt and was able to obtain an A+ score on the SSL Labs Server Test using HTTP Strict Transport Security (HSTS), Online Certificate Status Protocol (OCSP) Stapling, and only supporting modern TLS versions
1.3. We also deployed the server in the Google App Engine serverless platform. More information on this project can be found in the GitHub repository.