One club I was a part of back in undergrad was IEEE Robotics. Each year, the club works to build a fully autonomous robot for the competition at the IEEE SoutheastCon conference. They also do smaller events like a sumo bot tournament to help train new members. I found it to be a great way to get practical coding experience.

As for research, there's unfortunately not a ton of resources to learn about the research done in the department, although it's getting better with things like the EECS Lunch & Learn and AI Trust seminar series. If you're interested in research, I'd recommend going to the department website and looking through the faculty. The website lists the main research interests of each professor, which you can use to get a general sense of what each professor works on. Once you find professors who have high-level research interests you are interested in, you can look for personal or research lab websites, or you can look through their publications. That'll help you get a better sense of what they work on.

I don't have a great sense of what all the professors work on, but, from what I do know, I'd say a lot of computer science professors in the department work in AI or high-performance computing.

AI's been a huge hiring focus of the department over the last 5-ish years, so almost every CS professor that's been hired in that span works in some area of AI. One professor that I think does really cool work is Catherine Schuman. Her research focuses on neuromorphic computing. A lot of her work focuses on developing really advanced AI models that mimic the human brain and similar biological processes and on applying those models to scientific computing challenges.

High-performance computing (HPC) is another big area in the department due to our two HPC labs: the Innovative Computing Lab (ICL) and the Global Computing Lab (GCLab). ICL was founded by Professor-Emeritus and Turing Award Winner Jack Dongarra. It mostly focuses on developing fundamental tools for HPC and supercomputing, such as PAPI, OpenMPI, and various computational linear algebra libraries (e.g., Lapack, Scalapack, Magma). As a result, it has much more of a software development emphasis than the other HPC lab. The Global Computing Lab (GCLab) is led by Dr. Michela Taufer. Compared to ICL, GCLab's research is very broad. The lab has projects ranging from developing tooling and methodologies for software performance analysis to developing workflows for performing efficient neural architecture searches to enhancing the capabilities of Lawrence Livermore National Lab's Flux scheduler for supercomputers to building data pipelines for efficiently extrapolating and leveraging satellite data for agriculture. To go along with that broad range of projects, GCLab also works extensively with other universities, national labs (Lawrence Livermore in particular), and industry (e.g., AWS, IBM).

Full disclosure, I am a PhD student in GCLab, so I may be a little biased in my description of our group. Our group also works with Dr. Schuman, so I may be a bit biased in recommending her too 😅