(From left to right)
Michael Lacasse - Michael's college education, job experience, and constant pursuit of the latest training and certification programs, has led him to become an expert in the profession. After graduating with a B.S. in Computer Engineering with minor in Computer Science in 2003, Michael worked at the National Radio Astronomy Observatory developing test and measurement software in LabVIEW. Six years later, as a Certified LabVIEW Architect, he went on to developing control system software for the Discovery Channel Telescope. After completing this project, he now develops software for rocket engine and component testing for SpaceX. He is an NI Certified Professional Instructor and Certified Embedded Systems Developer. Michael even codes for fun in his free time with his kids!
Paul Lotz - Paul’s academic background (B.A. in Physics and Greek & Latin, The Catholic University of America; M.S. in Electrical Engineering, concentration in optics, University of Michigan) helped prepare him for success building complex optical systems, first for photolithography, then for telescopes. Paul served as Software Engineering Manager on the Discovery Channel Telescope (DCT) project, and, after completing that project, is helping to make the Large Synoptic Survey Telescope a reality. Paul has been writing control applications in LabVIEW since 1997, and has employed modeling languages to design complex systems since 2008.
Ryan Godwin, Ph.D. - Ryan has spent most of his early career focusing on academics (B.S. in Physics and Astronomy, University of Arizona, 2005; M.S. in Applied Physics (with distinction), Northern Arizona University 2008; Ph.D. in Physics (with Structural Computational Biophysics certificate), Wake Forest University, 2017) with a short break in between to work on the LDT. A passionate curiosity has driven him to study a diverse spectrum of topics, from astronomy to computer science to biophysics, and this diversity brings a unique perspective to the Apeiron team. Ryan has been using LabVIEW since 2004 and modeling languages since 2009. Ryan now works in radiology exploring applications of machine learning and artificial intelligence.