
We develop and evaluate AI systems that operate meaningfully within context, across language, embodiment, and society, to support safer, fairer, and more collaborative human and machine interaction.
We study:
-
Contextual language understanding
Discourse coherence, semantics, pragmatics, and conversational modeling -
Contextual interaction
Gesture, gaze, sign language, multimodal communication, and embodied AI -
Contextual evaluation
Human-in-the-loop methods, fairness-informed metrics, and socially grounded assessments -
Contextual deployment
Equity, access, and real world applications in healthcare, education, and policy
Our recent projects include AI systems that moderate social media discussions, mitigate misinformation, and foster common ground through healthy friction. We also develop multimodal systems that personalize STEM education for students with varied communication skills, and AI-driven tools supporting embodied decision-making and patient communication in healthcare.

Kate Atwell, PhD Student
(She/Her)

Asteria Kaeberlein, PhD Student
(She/Her)

Mert Inan, PhD Student
(He/Him)

Saki Imai, PhD Student
(She/Her)

Past students and visitors

Anthony Sicilia, PhD Student
Assistant Professor, West Virginia University

Sabit Hassan
Scientist at UNESCO
MS Students
-
Sanchayan Sarkar, MS project: Multimodal Turn-Taking in Human-Machine Dialogue, 2021.
-
Christian Pensabene, MS project: The Representation and Processing of Singed Coreference in Discourse
-
Kevin Hostler, MS Project: Discourse Coherence and Misinformation: A Multimodal Case Study
Undergraduate Students
-
Joffin Manjaly, Ph.D. student at Georgia Tech, Project Title: Political Ideology and Polarization of Policy Positions, 2022.
-
Sadhana Sridhar, Graduate student of neuroscience at UCSF, Project Title: Dynamic evaluation of trust in NLP systems 2022..
-
Urjeet Deshmukh, Amazon Alexa, Project Title: Lexical innovation in visual dialogue games, 2022.
-
Katelyn Morrison, Ph.D. student at CMU, Project Title: Spatially Sensitive Learning Algorithm to Mitigate Discrimination in Resource Allocation, 2021.
-
Nur Iren, Google, Project Title: Examining Covert Gender Bias in Machine Translation, 2021.
-
Chloe Ciora, Google, Project Title: Examining Covert Gender Bias in Machine Translation, 2021.
-
Daya Sharon, IBM, Project Title: Pronominal Reference Type Identification and Event Anaphora Resolution in American Sign Language, 2021.
-
Christian Pensabene, MS student at Pitt, SCITalk: A Data2Text Converstinal System for Communicating about COVID Data, 2021.
-
Michael Voit, Project Title: Multimodal Clarification Strategies in Conversational AI Systems, 2021.