I’m currently a data scientist at Seagate Technology in Shakopee, MN. There, I work on analyzing and modeling hard drive failures.
Before I made the transition to data science, I was an experimental particle physicist. While working on my PhD, I analyzed data from the CMS experiment at the Large Hadron Collider at CERN. I also did a brief stint as a Postdoctoral Associate at Cornell, where I designed reconstruction algorithms and wrote firmware for the upcoming Muon g−2 experiment at Fermilab.
I earned my Ph.D. in Experimental Particle Phyiscs from Cornell University in 2014, working under Prof. Jim Alexander. My dissertation research was carried out using the CMS experiment on the Large Hadron Collider at CERN. I studied applications of kinematic endpoint variables such as MT2 and MCT for measuerments of particle properties and searches for new physics. You can find my dissertation and the papers that came from this work over at Publications.
I did my undergraduate work at the University of Minnesota – Twin Cities, where I graduated Summa Cum Laude in 2009 with B.S. in Physics. While there, I did a variety of particle-physics-related research under Prof. Roger Rusack, including work on the CMS and NOνA experiments.
I love learning new things, so I dabble in lots of hobbies. I enjoy learning new technologies, including programming languages, framweorks, and machine learning techniques. I occasionally dabble in machine learning competitions over at Kaggle.com. I’ve also been working off and on at rebuilding mechanical watches.
I spend a fair amount of time on strength training, although I’m still a novice. I’ve had a lot of success with the methods outlined in Mark Rippetoe’s book Starting Strength. That said, basically any method that’s based upon linear progression of compound movements ought to work just as well.
If you want to get in touch with me, please email me at nicNOSPAM@eggert.io.