Midwest Research Computing and Data Consortium
In this series, we dive into the world of the Midwest Research Computing and Data Consortium. We explore its members, their challenges, and prospects. Recently, we had the opportunity to connect with Thomas White, a Critical Environment Engineer in Data Center Strategy and Operations at the University of Washington. Thomas was a speaker at the recent Next Generation Data Center Workshop, and he shares his insights on the field in the excerpts below:
I have a background in radio communication technology and computer networked systems, along with a Bachelor of Science in Network Operations and Security from Western Governors University. My career started in Network Operations Centers (NOCs), where I specialized in troubleshooting communications infrastructure and high bandwidth circuits. Working closely with senior engineers, I was introduced to the data center field and became drawn to its specialized nature compared to traditional network technician roles. This realization helped shape my career path. Today, I oversee daily operations and manage projects across multiple data centers and router rooms that are critical to the University of Washington and its partner institutions.
I began my IT career in computer networking, working night shifts in a large U.S. based telecom Network Operations Center. I then transitioned to the University of Washington, where I installed campus networks and contributed to a major technology refresh by deploying hardware in the university’s data centers. This experience introduced me to critical data center environments focusing on space, power, and cooling, which ultimately led to my role in the data center strategy and operations team. Over time, I took on daily operations while gaining expertise in power efficiency, vendor management, and product upgrade evaluations. I then progressed to leading larger projects, including the deployment of environments for emerging technologies such as HPC and AI clusters.
As a Critical Environment Engineer, my core mission is to provide operations and maintenance support for large scale data centers and multiple smaller network and telecommunications facilities, with a strong emphasis on research customer platforms. A key focus of my role is ensuring the operational integrity of Research IT platforms by monitoring and servicing these environments to maintain optimal performance and reliability.
I oversee the continuous operation and availability of critical environmental systems, including space, power, and cooling, to maximize efficiency and resource utilization. In daily operations, I schedule, coordinate, and monitor contracted vendor maintenance, particularly for Research, ensuring adherence to service agreements and quality standards. I also evaluate vendor performance, contracts, and operational procedures, providing feedback for improvements to maintain the integrity of customer-facing systems. Additionally, I contribute to resource allocation planning for Research and other stakeholders by identifying trends, making strategic recommendations, and developing plans for future platform growth. My team and I are committed to ensuring sustainable operations with no unscheduled, customer impacting outages. We also drive innovation by developing new methods to optimize resource utilization, supporting the expansion of Research Services Platforms, including those for artificial intelligence (AI) and other emerging technologies
Through conversations with engineers across the education sector, I’ve realized that while every institution faces unique challenges, we’re all working toward the same goal—building reliable, efficient, and scalable infrastructure to support research and innovation. Attending conferences and collaborating with peers from other universities has broadened my perspective on the evolving data center landscape and the challenges institutions like ours are facing.
Today, there is an unprecedented demand for computing power, storage, and performance, driving businesses and institutions to modernize their facilities. As a public university, we don’t always move as quickly as private sector companies due to resource constraints, budget limitations, and reliance on federal funding. However, the University of Washington takes pride in being a leader in research and technology innovation, and the pace of advancement across campus is remarkable. Our IT staff and researchers are eager to leverage high performance computing (HPC) and AI technologies, but we must work within the constraints of our existing infrastructure. Currently, we are deploying an AI cluster in a data center built in 2009, designed with a raised floor and air cooling. This project has required careful planning, trade-offs, and lessons learned along the way. To accommodate the growing power and cooling demands of AI workloads, we conducted a full assessment of our infrastructure with a third-party engineering firm. This evaluation focused on power usage, load balancing, distribution, and overall system capacity. We quickly recognized that air cooling alone would not be sufficient for high density AI racks, making liquid cooling a necessary consideration for future deployments.
Beyond infrastructure upgrades, we also explored advanced automation and predictive management tools to improve monitoring, temperature control, and power optimization. This involved evaluating various solutions to determine the key metrics we needed while automating routine tasks for greater efficiency. To ensure a smooth transition, we developed a phased retrofit plan that balances the needs of new AI workloads with those of our existing enterprise co-location customers. Supporting AI infrastructure requires more than just technical upgrades—it also demands strategic business planning to secure funding and ensure the facility remains adaptable to future demands.
My advice to aspiring engineers in this field is to deeply explore the technologies that interest you—whether through certifications, courses, or hands-on experience—but also to understand the broader systems that support them. In the world of high-performance computing (HPC) and AI, success is closely tied to the data center environment. If you’re working with these technologies, take the time to learn how data centers operate and how they support advanced computing workloads.
Build strong communication skills to collaborate effectively with data center teams, ensuring that everyone is aligned for success. Develop an understanding of space allocation, power distribution from the utility source down to the rack PDU and the various cooling technologies that keep these systems running efficiently.
Beyond the technical aspects, learn the business side of IT within your organization. Understand what drives leadership decisions and how technology investments align with business goals. The more you understand where you fit into the bigger picture, the more value you can bring to the team and the more opportunities you’ll create for yourself to grow in the field.