Special Edition: Community Corner Spotlight – Honoring Jim Ferguson!

As we step into 2025, we’re celebrating a remarkable career and the profound impact of Jim Ferguson, Director of Outreach and Training at the Minnesota Supercomputing Institute (MSI), who is retiring this year after decades of dedicated work supporting researchers and advancing the field of data science. Jim’s contributions have not only shaped technology but have also fostered innovation and collaboration across the research community. Join us in recognizing his legacy in this special edition of our Community Corner.

Reflecting on a Career of Innovation

Q: As you reflect on your career, what research areas have been most meaningful to you?

I've spent much of my career *supporting* researchers directly, but have contributed to some things in networks that were really engineering advances. One of these was IETF RFC4898, a published standard that was eventually folded into the main Linux kernel and other operating systems.

 

Q: How has your perspective on Data Science evolved over the years?

It's been a long career and as I've watched computational science evolve, it has tracked in a fairly predictable way. Faster compute engines and denser & cheaper data storage have made discoveries focused on data more viable, and accurate enough to be accepted. Discoveries based on simulations of first principals have also advanced due to these technological advances, but aren't as new and shiny.

 

Q: Looking back, what is one of the most interesting or surprising findings from your research?

Not from research, but a surprise from a tool we built to support researchers. Back in the late 1990's I was working on a grant that supported training University researchers and their students how to more effectively use the new high-speed networks being deployed. Our researchers, in their offices and labs around the country, had no way of testing to see if their network was working well, so we built an easy tool (that required no root privileges to run) to show them what their network performance was between two endpoints -- so they would have data to show their local IT network engineers. Within about 12 months, due to Internet2 and NLANR tech workshops, our biggest downloaders and requests for more features came from -- network engineers! We had no idea they would want to use our tool as well. It's still around and being used today (Iperf).

 

Q: Are there any tools or methods that you’ve enjoyed working with or that you see as game-changers for the next generation of researchers? 

I was skeptical of the claims of supporters of quantum computing made when I first encountered stories of the first lab-bench prototypes of Qbits. The progress has been slow but steady, and I am not very skeptical anymore.

 

Q: As you step into this next chapter, what developments in Data Science are you most excited to watch unfold? 

I am more interested/concerned about areas where data science methods will be used next. In my semi-informed opinion, I don't think some fields have enough data available (yet) to extract answers we can have confidence in. I think data scientists need to be careful when making that case regarding the strength of their training and testing data sets, every time.

 

As Jim Ferguson embarks on his well-earned retirement, we celebrate the profound impact he has had on the research community. His contributions to networking standards, computational tools, and data science have paved the way for future innovations. Jim’s reflections remind us of the power of technological progress and the responsibility that comes with it. We thank him for his dedication, insight, and unwavering support of researchers over the years.

Wishing Jim all the best in this next chapter!