Current Role
I currently work as a software engineer at S&C Electric Company, where I’ve spent the past six years contributing across a diverse range of technical domains. The majority of my work spans enterprise applications and embedded systems. During my first five years with S&C, I dove deep into various enterprise applications, primarily using technologies such as Java Spring Boot, React, and various relational database technologies. Over the past year and change, I have shifted from enterprise development to embedded, where I develop and maintain mission-critical systems in C/C++. My career has been shaped by a passion for building reliable systems, solving complex problems, and continuously learning new technologies.
Professional Experience
S&C Electric Company (2019–Present)
Software Engineer specializing in enterprise applications and embedded systems. Focused on building reliable, scalable systems for critical infrastructure.
Travas Inc. (2018–2019)
Co-Founder. Built and deployed a full-stack application enabling cryptocurrency trading strategy design and live deployment of automated trading bots. This startup experience was a pivotal turning point in my technical skillset, forcing me to learn many intricacies of system design that accelerated my growth as an engineer.
IBM (2017–2018)
Cognitive Computing Consultant. Worked with a range of technologies and directly with public sector clients to help launch and deploy software on-site. Contributed to an R&D effort involving training convolutional neural networks for object detection, which resulted in U.S. Patent “Convolutional neural network with augmentation features”1.
Education & Early Background
Georgetown University (Class of 2017)
Bachelor of Science in Computer Science. Competed as a Division I track and field athlete in the 200-, 400-, and 800-meter events. Recognized with the Thomas Francis Graham Award2, which honors a single student-athlete from the college for leadership and scholarship. Worked as a teaching assistant for three years, co-founded the Game Design Club, and co-authored research, A High-Performance Algorithm for Identifying Frequent Items in Data Streams3, under Professor Justin Thaler.
Internships
- Systems and Technology Research (STR), Woburn, MA (Summer 2017): Machine learning project leveraging Recurrent Neural Networks (RNNs) to assist in reverse engineering binaries
- Cerner (now Oracle), Kansas City (Summer 2015): Automated several processes for the data warehousing team
Personal Background
I was born and raised in Ozark, Missouri, where I attended Ozark High School from kindergarten through 12th grade. Creativity has always been at my core. In grade school, I designed board games, trading card games, and wrote fiction stories. In fifth grade, I discovered “drag-and-drop” programming through RPG Maker, sparking a curiosity that evolved into formal programming by high school and eventually a degree in Computer Science. A successful high school track and field career brought me to Washington, DC to compete at Georgetown University.
Outside of work, I’m deeply committed to running and endurance sports. My journey as a runner began in seventh grade and continued through college and post-collegiately. For the past four years, I have trained with the Georgetown Running Club in Washington, DC. Running has taught me lessons that carry into every aspect of my life: time management, setting long-term goals, learning from setbacks, and striving for constant improvement both personally and professionally.
When I’m not training for a big race, I enjoy many other pastimes. You can find me spending time with my partner Brenda. We enjoy hiking, exploring new restaurants around the city, or relaxing at home watching a movie or TV series together. We have a 9-year-old rescue dog, Stella, who tests our patience every day but makes up for it with the joy and energy she brings to our home. When time permits and I’m feeling motivated to learn and build, I thoroughly enjoy diving into creative hobby projects—many of which are captured here on this site.
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U.S. Patent “Convolutional neural network with augmentation features” (2021) - View patent ↩
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Thomas Francis Graham Award (2017) - Georgetown article ↩
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A High Performance Algorithm for Identifying Frequent Items in Data Streams (2017) - arXiv link ↩
Daniel Anderson