I'm such a fan on interdisciplinary science and it's been a joy working with the wonderful Kevin Mitchell @WiringTheBrain to share a geneticists perspective on the strengths and weaknesses of analogies between our computational models and natural systems. arxiv.org/abs/2407.15908

I'm grateful that my colleagues have trusted me to take on such an ambitious endeavor and I hope that our lab can make the most of this opportunity.  It's the way science should be done!

Tenure provides the security to take on risky and uncertain approaches that may not pay off for many years or without the contributions of many others.

I also want to quickly reflect on the institution of tenure.  I find it incredible and so important that there exists a system that lets us tackle grand and open challenges in science and society, knowing that these are complex and long-term problems.

I want to thank my students for doing the hard work in the trenches that's built such an interesting and impactful body of work in our lab, my colleagues for their mentorship and collaboration, and my family for their support and sacrifice as I take on such a demanding career.

I'm thrilled to announce that I've been awarded tenure and promotion to Associate Professor at the University of Vermont!  Starting in research as an undergrad at UVM nearly 15 years ago, I'd never have imagined being in this position, but am so glad that it's come full circle!

This award looks at the 10-year impact a paper has had on our field, so your engagement with the research (or our fun videos tinyurl.com/evolvingsoftrobo…) have made this happen! I’m so very flattered every time someone reaches out or interacts with our work. You are all awesome!

Honored to win my society's Impact Award this year. Thanks to all who read, shared, and built upon the work; and to the SIGEVO Board for calling it seminal to our field. Shout out to my collaborators for making this impactful and a ton of fun to work on! uvm.edu/news/cems/nick-chene…

The full experiments (github.com/uvm-neurobotics-l…) can be run on CoLab without any problem! However to further speed up training time, you could also try reducing the: network size, meta-training classes/iterations/batch size, or inner-loop trajectory length