As a student worker at UVA Research Computing, Matthew Galitz gained hands-on experience in software engineering and machine learning, fields he is passionate about. He led projects that created practical tools to help researchers across UVA find collaborators and manage their work more efficiently. Through this experience, Matthew developed important professional skills like collaboration, communication, and project ownership. In this Q&A, he shares how working alongside experts and tackling real-world challenges helped prepare him for his future career.
Matthew Galitz
Major: Mathematics & Computer Science
Relevant Interests: Software Engineering, Machine Learning/Artificial Intelligence
Previous Experience: Software Development Engineer Intern at AWS
What sparked your interest in working with UVA Research Computing?
I joined UVA Research Computing in the fall of 2024 after discovering the opportunity on the UVA Workday Job Board. I saw it as a chance to apply the skills I’d gained in my coursework in a real-world setting. Beyond the technical experience, I was eager to understand what it meant to contribute professionally: meeting expectations, working within a team, and delivering under real constraints. I wanted to test and refine my competence outside the academic setting and gain exposure to the kind of workflows and professionalism I’d encounter in the industry.
What kinds of responsibilities and opportunities did you have as a student worker?
My responsibilities as a student worker were wide-ranging. I often switched between leading and supporting roles depending on the project, and I regularly handled technical odd jobs like writing custom scripts for faculty to automate tasks. I contributed to two major efforts: the Rivanna Utilization Statistics Project and a Research Faculty Search Engine for the Data Analytics Center. I also had the opportunity to work closely with Research Computing’s team members like Karsten Siller, User Services, Director, and Andrew Strumpf, Business Systems Analyst, which gave me insight into professional collaboration and helped me understand the kinds of tools and workflows used in research computing.
What are some of the most important skills you developed or lessons you learned during your work at Research Computing?
One of the most valuable aspects of working with UVA Research Computing was the chance to develop soft skills and professional habits that aren’t taught in class. I learned how to communicate effectively with colleagues, ask the right questions, and adapt my work based on feedback and shifting priorities. I also became more comfortable taking initiative and managing ambiguity; skills that are essential in any workplace but rarely emphasized in academic settings. Collaborating with professionals taught me how to write maintainable code, document my work clearly, and stay accountable for my contributions. It was a shift from just trying to “solve the problem” to delivering work that others could rely on, understand, and build upon.
Can you share a project or accomplishment from your time as a student worker that you’re especially proud of?
One project I’m especially proud of is the Research Faculty Search Engine I built for the Data Analytics Center. I led development from start to finish, designing both the backend and frontend, integrating faculty data, and deploying a fully functional web application. The tool helps streamline outreach by letting users search and filter faculty based on their research area and funding history. Building something genuinely useful — something with real stakeholders and long-term impact — is a rare opportunity for an undergraduate. It pushed me to think not just like a coder, but like a software engineer: balancing usability, performance, and maintainability while meeting project goals. Leading this effort taught me how to take ownership of a project and follow through with clarity and professionalism.
I hope my work contributes to a culture where technical infrastructure is not just functional but thoughtfully designed to serve researchers’ needs. Tools like the Research Faculty Search Engine aim to reduce friction in processes that are often overlooked, like outreach or identifying collaborators, yet can have a disproportionate impact on research productivity. By improving these behind-the-scenes systems, I hope I’ve helped create space for researchers to focus more on their actual work and less on logistics. More broadly, I see Research Computing as a quiet enabler of progress. If the tools I’ve built or supported can save someone time, make their work more visible, or reduce a barrier, then that’s a meaningful contribution.
How did the UVA Research Computing team support your growth and learning throughout your time there?
What stood out most about the UVA Research Computing team was their eagerness to explain the structure, processes, and culture that underlie their work. Whether it was the reasoning behind a design choice, the context of a tool’s use, or just how research support operates at UVA, they never hesitated to walk me through it. That kind of transparency is valuable, and it made the experience feel collaborative rather than hierarchical. I wasn’t just given tasks, I was given context, and that helped me grow. It deepened my understanding of not only the technical landscape, but also how professional teams think, prioritize, and communicate. That perspective was just as valuable as any line of code I wrote.
How has this experience helped prepare you for your future academic or professional goals?
This internship helped me bridge the gap between being a student and becoming a professional. It trained me to approach work with intention, thinking in terms of maintainability, usability, and stakeholder needs rather than just completing assignments. That shift in mindset is crucial for both industry and academia. I now feel more prepared to contribute meaningfully to a team, whether that’s in a research lab, a company, or graduate school. I also developed confidence in my ability to take ownership of complex projects and deliver under real expectations, something coursework rarely demands. It was my first experience operating in a professional engineering context, and it validated that I’m ready for what comes next.
What advice would you give to other students who are interested in research computing?
Don’t wait until you feel “qualified.” Research computing is an environment where curiosity and initiative matter just as much as technical expertise. If you’re willing to ask questions, take ownership, and learn as you go, you’ll gain far more than you would in a purely academic setting. Also, don’t underestimate the value of small tasks — sometimes writing a simple script for someone or debugging a cron job teaches you more about real-world problem-solving than a semester-long class. Finally, treat every interaction as a chance to understand how professionals think and work. There’s a lot of institutional knowledge that doesn’t live in documentation; it lives in people who are generous enough to share it if you ask.
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