Image Description

Rory A. Lewis JD PhD

Associate Professor, Dept. of Computer Science

Engineering Building, Room 188
University of Colorado at Colorado Springs
1420 Austin Bluffs Parkway
Colorado Springs, CO 80918, 719.255.3149
Email rlewis5@uccs.edu :: Website https://www.rorylewis.com
GitHub https://github.com/innertron :: Google Scholar https://scholar.google.com


Prof. Lewis is the Program Director: Masters of Computer Science. He is the recipient of Outstanding Achievement: Teacher of the Year. College Of Engr, Computer Science. He is the recipient of Outstanding Achievement: Inventor of the Year CU. University of Colorado, for his work in computational neurosciences. He is also the recipient of the “Innovations in Scholarship for Inclusiveness and the recipient of Outstanding Achievement: Teacher of the Year. College of Engr (Student Vote), 2018.

Prof. Lewis conducts his computational neuroscience research at the neuroICU ward at University of Colorado Hospital at Anschutz Medical School. Prof. Lewis has Secret Clearance and is the Senior Scientist at the United States Airforce NM2 laboratories developing artificial intelligence for Intelligence Surveillance & Recconnaissance (ISR) at the Pentagon in Washington DC and 10th Division Special Forces. Prof. Lewis is also a Senior Research Scientist at the RAND Corporation where he researches and prepare white papers regarding classified DOD ISR Machine Learning, Artificial Intelligence and Machine Consciousness theory and state-of-the-art advances.

His research lies broadly in creating machine learning that predict events in time-variant signal analysis in neurosciences and other complex systems. Prof. Lewis currently focuses on bringing machine reasoning and machine consciousness into computationlal neuroscience and military humanoids. [see Curriculum Vitae heref]

 

P rof. Lewis received a B.S. in Computer & Electrical Engineering in 1993 from Syracuse University. In 1996, he received his J.D in Law from the Syracuse University College of Law. After working in law, litigating microprocessor electrical engineering intellectual property inherrent in microprocessors, such as Intel. v. AMD, Prof. Lewis transitioned back into academia over 2002 - 2004. In 2008 he received his PhD in Computer Science at the University North Carolina at Charlotte. Following is some of Prof. Lewis' research interests and personal interests that students sometimes seem interested in.

ZBIGNIEW W. RAS

Dr. Lewis was fortunate to study under one of the giants of computational mathematics, Zbigniew W. Ras who, though often quite stringent, played a major role in developing Dr. Lewis' abilities with mathematics and electrical engieering into machine learning. First, Dr. Ras had Lewis study the mathematical theory of ontologies, then signal analysis and finally Rough Set Theory in its application to the mathematical constructs of artificial intelligence and machine learning, This picture is with Profs Ras, Skowron and Lewis at the University of Warsaw.

Zbigniew Ras, Andrzej Skowron and Rory Lewis artificial intelligence

Inventor of The Year

Dr. Lewis received Inventor of the Year for his work in machine learning and artificial intelligence

Rory Lewis Inventor of the year artificial intelligence

minedICE (click here)

While studying the mathematical theory of Knowledge Discovery in Databases under Professor Zibignieus Ras at the University of North Carolina Charlotte, the focus was on creating machines that could discern between very similar instruments and learn from its mistakes. The issue was not music in the sense it was the sinusoidal wave forms and the inherrent Fourier Transforms that made this a non triveal endeavor. For his Doctoral Dissertation, PhD Candidate Rory Lewis went further and introduced emotions in music making the machine not only recognize instruments and the notes they were playing but also eliminate the vocals and understand the emotions of the music.

minedICE artificial intelligence and machine learning

NSF STTR Syberenity (click here)

Artificial Intelligence to predict when addicts when relaps

minedICE artificial intelligence and machine learning