Curriculum Vitae

Jacob Schrum, Ph.D.

Associate Professor of Computer Science
Chair, Department of Mathematics and Computer Science
Southwestern University
1001 E. University Ave.
Georgetown, TX 78626

Office/Mail: Fondren-Jones Science Hall 308
Off-Campus Phone: (512) 863-1712
On-Campus Extension: x1712

This is my first academic year with tenure and the title of Associate Professor of Computer Science at Southwestern University. I will also be taking over as Chair of the Department of Mathematics and Computer Science. Incidentally, Southwestern University is also where I received my undergraduate B.S. with a triple-major in Computer Science, Math, and German. I received my Ph.D. from the Computer Science Department at the University of Texas at Austin for my dissertation on Evolving Multimodal Behavior Through Modular Multiobjective Neuroevolution.


Upcoming classes at SU (Fall 2020):
  • CSC54-284 - Computer Science II
  • CSC54-394 - Computer Organization
  • CSC54-474 - Programming Languages
Previously taught classes at SU, listed by course number (All content on Moodle):
  • CSC54-184 - Computer Science I (Fall 2014, Spring 2015, Fall 2015, Spring 2016, Fall 2016, Spring 2018, Spring 2019)
  • CSC54-284 - Computer Science II (Spring 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Spring 2020)
  • CSC54-291 - Rapid Application Development (Fall 2016)
    This course is preparation for the ACM South Central USA Regional Programming Contest
  • CSC54-394 - Computer Organization (Fall 2015, Fall 2016, Fall 2018)
  • CSC54-644 - Computer Systems (Spring 2015, Spring 2016, Spring 2017, Spring 2018)
  • CSC54-474 - Programming Languages (Fall 2019)
  • CSC54-534 - Functional Programming (Fall 2014, Spring 2017)
  • CSC54-424 - Artificial Intelligence (Fall 2015, Spring 2019)
Previously taught classes at the University of Texas: Previous Teaching Assistant work at the University of Texas:

Online Instructional Videos

Instructional videos associated with my classes are hosted on this YouTube channel.


My research area is Artificial Intelligence, specifically the automatic discovery of intelligent agent behavior, particularly in the domain of games. I'm interested in all sorts of games: board games, logic puzzles, and video games. Agents in video games and robot agents in the real world often require multiple modes of behavior (multimodal behavior) in order to handle multiple tasks. One powerful technique for discovering intelligent agent behavior is neuroevolution, which is the simulated evolution of artificial neural network brains. The complex domains I am interested in often involve multiple objectives, sometimes because separate tasks have separate objectives, so I am also interested in multiobjective optimization. More recently, I've been scaling up to domains requiring larger, more complex brains, which has sparked an interest in indirect encodings and deep reinforcement learning.

My dissertation advisor was Risto Miikkulainen of the Neural Networks Research Group (NNRG). Information about my research activities at the University of Texas is available on my Personal Page within the larger NNRG website.

My research has led to the development of several software packages:
  • UT^2 is a software agent for Unreal Tournament 2004 that won the 2012 BotPrize competition, a Turing Test for video game bots. The agent depends on the Pogamut platform, which is Java middleware that interfaces with Unreal Tournament 2004 via the included GameBots mod. Information about my past BotPrize research is compiled on this page. Note that this code and other code associated with Unreal Tournament 2004 is now included in MM-NEAT as well.
  • The Infinite Art Gallery is a video game in which players interactively evolve art similar to that of Picbreeder and Endless Forms, but by interacting with the art in an immersive 3D world. The code for this project is available on GitHub. It was developed in C# and Unity by undergraduate student Bryan Hollingsworth.
  • Multi-Brain HyperNEAT is an extension of HyperNEAT, an approach for evolving indirectly encoded neural networks. Multi-Brain HyperNEAT allows individual agents to have multiple separate brains to use in different circumstances. The code is an extension of the Multiagent Simulator for HyperSharpNEAT, which is a C# implementation of HyperNEAT available on this page.
  • BREVE Monsters is a 3D Artificial Life environment with several domains in which I evolved multimodal behavior. This code relies on the Breve simulation environment.
I have also become increasingly involved in undergraduate research during my time at Southwestern University, thanks in part to the SCOPE program, which is a Summer research program for undergraduates at Southwestern University.

Research Movies and Images

Individual videos associated with my research are linked to below, but are all hosted on this YouTube channel. More details about my research are available in my publications, also linked to below:


Peer-Reviewed Journal Articles

Peer-Reviewed Conference Publications

Invited Book Chapters/Articles

Extended Abstracts

Technical Reports

Undergraduate Poster Presentations Supervised


Last Updated: 6/28/2020