CV

EDUCATION            

Graduate Student in Cognitive Science                                                                 2016-Present

University of California, San Diego
Advisor: Benjamin Bergen

B.A. in Cognitive Science, High Honors                                                                 2010-2014

University of California, Berkeley
Thesis advisor: Terry Regier

 

PROFESSIONAL HISTORY          

Teaching Assistant                                                                                                   2016-Present

Introduction to Computing (Instructor: Mary Boyle, Winter 2017)
Language (Instructor: Esther Walker, Spring 2017)
Cyborgs Now and in the Future (Instructor: David Kirsh, Fall 2017)
Introduction to Research Methods (Instructor: Federico Rossano, Winter 2018)
Lecture delivered: Entitlement modulates request formatting (February 1, 2018)

 Research Assistant                                                                                                        2014-2016

International Computer Science Institute (Berkeley, CA)

 

HONORS AND AWARDS       

Chancellor’s Research Excellence Scholarship (CRES)                                        2018-2019

Why are some people better at inferring what others mean?
Mentors: Benjamin Bergen (Cognitive Science); James Hollan (Cognitive Science, CSE)

 

PUBLICATIONS        

Conference Proceedings

Trott, S., Rossano, F. (2017). Theoretical Concerns for the Integration of Repair. AAAI Fall Symposia Series: AI for Human-Robot Interaction.

Trott, S., Bergen, B. (2017). A Theoretical Model of Indirect Request Comprehension. AAAI Fall Symposia Series: AI for Human-Robot Interaction.

Raghuram, V., Shen, K., Goldberg, E., Oderberg, S., & Trott, S. (2017). Semantically-Driven Coreference Resolution with Embodied Construction Grammar. AAAI Workshop: Computational construction grammar and language understanding.

Dodge, E., Trott, S., Gilardi, L., & Stickles, E. (2017). Grammar Scaling: Leveraging FrameNet   Data to Increase Embodied Construction Grammar Coverage. Technical report, AAAI SS-17-02.

Doubleday, S. Trott, S. Feldman, J. (2016). Processing Natural Language About Ongoing     Actions. Published on arxiv.org (http://arxiv.org/abs/1607.06875).

Eppe, M., Trott, S., Raghuram, V., Feldman, J., & Janin, A. (2016). Application-Independent and Integration-Friendly Natural Language Understanding. EPiC Series in Computing, 41(GCAI 2016. 2nd Global Conference on Artificial Intelligence), 340–352.

Trott, S., Eppe, M., & Feldman, J. (2016). Recognizing Intention from Natural Language : Clarification Dialog and Construction Grammar. Workshop on Communicating Intentions in Human-Robot Interaction.

Eppe, M., Trott, S., & Feldman, J. (2016). Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction. Arxiv.Org.

Trott, S., Appriou, A., Feldman, J., & Janin, A. (2015). Natural Language Understanding and Communication for Multi-Agent Systems. AAAI Fall Symposium, 137–141.

Feldman, J., Trott, S., Khayrallah, H. (2015). Natural Language for Human Robot Interaction. Proceedings of the Workshop on Human-Robot Teaming at the 10th ACM/IEEE International Conference on Human-Robot Interaction, Portland, Oregon.

Presentations

Trott, S., Rossano, F. (2017). Theoretical Concerns for the Integration of Repair. AAAI Fall Symposia Series: AI for Human-Robot Interaction.

Trott, S., Bergen, B. (2017). A Theoretical Model of Indirect Request Comprehension. AAAI Fall Symposia Series: AI for Human-Robot Interaction.

Trott, S., Bergen, B. (2017). The Role of Mentalizing in Pragmatic Inference. Ad Astra, UC San Diego.

Trott, S., Eppe, M., & Feldman, J. (2016). Recognizing Intention from Natural Language : Clarification Dialog and Construction Grammar. Workshop on Communicating Intentions in Human-Robot Interaction.

Trott, S., Appriou, A., Feldman, J., & Janin, A. (2015). Natural Language Understanding and Communication for Multi-Agent Systems. AAAI Fall Symposium, 137–141.

SKILLS        

Experimental design: JsPsych, PsychoPy
Data analysis: Python (SciPy, NumPy, scikit-learn, NLTK) and R