Mark Heimann

Mark Heimann

I am a second-year PhD student in computer science at the University of Michigan working in the GEMS Lab under the supervision of Danai Koutra. Specifically, my current research interests include algorithmic methods for speeding up large matrix-based data mining and machine learning problems, as well as representation learning in networks.

Other significant pursuits of mine include chess, where I am an active competitive player with the master title in both the United States Chess Federation and FIDE, and music. I am interested in creating artificial intelligence technology for music analysis and performance, as well as the design and use of electronic effects especially for augmenting acoustic instruments.