Department of Computer Science
Tom Williams is an Assistant Professor of Computer Science at the Colorado School of Mines, where he directs the Mines Interactive Robotics Research Lab. Prior to joining Mines, Tom earned a joint PhD in Computer Science and Cognitive Science from Tufts University in 2017. Tom’s research focuses on enabling and understanding natural language based human-robot interaction that is sensitive to environmental, cognitive, social, and moral context. His work is funded by grants from NSF, ARL, and USAFA, as well as by Early Career awards from both NASA and the US Air Force.
- BA in Computer Science, Hamilton College, 2011
- MS in Computer Science, Tufts University, 2013
- PhD in Computer Science: Cognitive Science, Tufts University, 2017
- Human-Robot Interaction (F19)
- Robot Ethics (S19, S20)
- Linguistic Human-Robot Interaction (S18)
- Computer Vision (F17, F18, F19)
- Human-Robot Interaction
- Natural Language Understanding and Generation
- Artificial Intelligence
- Cognitive Science
- Robot Ethics
- Augmented Reality
- Williams, T., Zhu, Q., Wen, R., & de Visser, E. (2020). The Confucian Matador: Three Defenses Against the Mechanical Bull. In Proceedings of the 15th ACM/IEEE International Conference on Human-Robot Interaction (HRI). ACM. [alt.HRI track]
- Jackson, R.B., Williams, T., & Smith, N. (2020). Exploring the Role of Gender in Perceptions of Robotic Noncompliance. In Proceedings of the 15th ACM/IEEE International Conference on Human-Robot Interaction (HRI). ACM.
- Jackson, R. B., & Williams, T. (2019). Language-capable robots may inadvertently weaken human moral norms. In Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 401-410). IEEE. [alt.HRI track]
- Williams, T., & Scheutz, M. (2019). Reference in robotics: A givenness hierarchy theoretic approach. The Oxford handbook of reference.
- Scheutz, M., Williams, T., Krause, E., Oosterveld, B., Sarathy, V., & Frasca, T. (2019). An overview of the distributed integrated cognition affect and reflection DIARC architecture. In Cognitive Architectures (pp. 165-193). Springer, Cham.
- Williams, T., Tran, N., Rands, J., & Dantam, N. T. (2018). Augmented, mixed, and virtual reality enabling of robot deixis. In International Conference on Virtual, Augmented and Mixed Reality (pp. 257-275). Springer, Cham.
- Williams, T., Thames, D., Novakoff, J., & Scheutz, M. (2018). ” Thank You for Sharing that Interesting Fact!” Effects of Capability and Context on Indirect Speech Act Use in Task-Based Human-Robot Dialogue. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (pp. 298-306). Best Paper Nominee
- Williams, T., & Scheutz, M. (2017). The state-of-the-art in autonomous wheelchairs controlled through natural language: A survey. Robotics and Autonomous Systems, 96, 171-183.
- Williams, T., Briggs, G., Oosterveld, B., & Scheutz, M. (2015). Going beyond literal command-based instructions: Extending robotic natural language interaction capabilities. In Twenty-Ninth AAAI Conference on Artificial Intelligence.