About Us
Cameron McGuinness, PhD.
Cameron is an expert in computational intelligence methods for production scheduling optimization and automatic content generation. He has pioneered the application of the powerful Monte Carlo Tree Search decision making method to many diverse problems, where before it had been almost exclusively applied to decision making in games such as Chess or Go. Cameron is an experienced computer programmer and has degrees in theoretical physics and mathematics. In his spare time, he enjoys games of all sorts, video games, board games, fantasy role playing games.
Daniel Ashlock, PhD -- Chief of Innovation
Daniel has made fundamental contributions to computational intelligence for over 25 years, both in research and in industry. His interests are diverse, including among others: evolutionary computation, bioinformatics, ecoinformatics, image generation and processing, and evolved art. He is skilled in applying techniques developed for one field to other fields. Daniel has participated in many industrial and scientific projects. For example, together with Proctor and Gamble , he developed bioinformatics tools for gene regulatory networks. With grants from NSERC , he has worked on modelling biological data and designing bioinformatic tools. In a Cooperative R&D Agreement with Polycon Industries , Daniel developed methods to optimize industrial processes to minimize waste. Daniel is an award winning teacher, skilled at explaining difficult concepts so that they are easily understood. In his spare time, Daniel enjoys creating rules systems for fantasy role playing games and developing fractal images. Check out his blog, OccuΠ Math .
Wendy Ashlock, PhD -- Chief Data Scientist
Wendy is an expert in applying computational intelligence and machine learning to bioinformatics. She held an NSERC Fellowship in Computer Science in the biology lab of Dr. Ronald E. Pearlman, one of the foremost experts on the model organism, Tetrahymena thermophila . She spearheaded the development of the motif-finding technique, Side Effect Machines. Side Effect Machnines enable the identification of complex motifs, such as those created by groups of transcription factor binding sites in promoter regions of genes. In addition, Wendy has produced award winning software and is an experienced teacher.