Jason Yoder
Dr. Yoder earned a dual Ph.D. in computer science and cognitive science from Indiana University. His teaching interests include bio-inspired artificial intelligence, artificial life, evolutionary computation, object-oriented programming, and web programming. He has played competitive Ultimate Frisbee for over twenty years, including four years of semi-professional ultimate, and has over a decade of experience coaching college ultimate teams including Rose-Hulman. He also plays pickleball, ice/roller hockey, and enjoys snow/long/mountain/paddle boarding, rock climbing, hiking, and camping.

Academic Degrees

  • Dual Ph.D. in Computer Science and Cognitive Science, Indiana University 2018.
  • M.S. in Computer Science, Indiana University 2011.
  • B.A. Computer Science and Mathematics Goshen College 2008, 2009.

Awards & Honors

  • National Science Foundation Research Opportunity Award 2021
  • Indiana University Male Big of the Year Award, Big Brothers Big Sisters 2019
  • Sarah D. Barder Fellowship 2017
  • School of Informatics and Computing Associate Instructor of the Year Award 2016

Publications & Presentations

  • A. Renner, É. Marois, J. Fiorito, J. Ashworth, and J. A. Yoder, “A computational model of developmental exaptations,” Proceedings of the 2024 Artificial Life Conference, 2-10, 2024.
  • J. Ashworth, J. Fiorito, and J. Yoder, “Modeling evolutionary development with indirect encodings on dynamic nk fitness landscapes,” Proceedings of the 2023 Artificial Life Conference, 113-121, 2023.
  • J. Ashworth, Y. Lee, J. Shen, E. Kim, Z. Decker, and J. Yoder, “Evolution of developmental strategies in nk fitness landscapes,” The 2022 Conference on Artificial Life, 59-67, 2022.
  • C. A. LaKemper, C. Wang, and J. A. Yoder, “Biology inspired growth in meta-learning,” Proceedings of the Genetic and Evolutionary Computation Conference Companion, 63-64, 2022.
  • D. Whitley, J. Yoder, and N. Carpenter, “Intrinsic evolution of analog circuits using field programmable gate arrays,” Artificial Life, vol. 28, no. 4, 499–516, 2022.
  • J. A. Yoder, C. B. Anderson, C. Wang, and E. J. Izquierdo, “Reinforcement learning for central pattern generation in dynamical recurrent neural networks,” Frontiers in Computational Neuroscience, vol. 16, 818-985, 2022.
  • D. Whitley, J. Yoder, and N. Carpenter, “Resurrecting FPGA intrinsic analog evolvable hardware,” in Artificial Life Conference Proceedings 33, 106-113, 2021.
  • J. A. Yoder and S. Chenoweth, “Reflection for recovery: Exam wrappers in an object-oriented software development course help struggling students improve future exam scores,” IEEE 32nd Conference on Software Engineering Education and Training (CSEE&T), 1–9, 2020.
  • Yoder, J. "Neuromodulation for Artificial Intelligence: Understanding by Building, Building with Understanding," dissertation, Indiana University, 2018.
  • J. A. Yoder and E. J. Izquierdo, “Behavioral stability in the face of neuromodulation in brain-body-environment systems,” The 2018 Conference on Artificial Life, 268–275, 2018.
  • J. Yoder, “Evolving neuromodulatory architectures on non-associative learning tasks,” IEEE Symposium Series on Computational Intelligence (SSCI), 1–9, 2017.
  • J. Yoder and L. Yaeger, “Evaluating topological models of neuromodulation in polyworld,” Artificial Life Conference Proceedings 14, 916-923, 2014.

Research Interests

Evolutionary and Adaptive Systems:

  • Modeling Evolution of Development
  • Developmental Neural Networks
  • Neuromodulation
  • Evolvable Hardware
  • Artificial Life
  • Bio-Inspired Artificial Intelligence

Cognitive Science: 

  • Metacognition
  • Motivation Theory
  • Theories of Emotion
  • Theories of Consciousness

Teaching Interests

  • Bio-Inspired Artificial Intelligence
  • Artificial Life
  • Evolutionary Computation
  • Object-Oriented Programming and Software Development
  • Web Programming
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