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Contextual AI Lab

Studying language, interaction, and the societal contexts that shape and are shaped by AI.

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 

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Kate Atwell, PhD Student
(She/Her)

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Asteria Kaeberlein, PhD Student
(She/Her)

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Mert Inan, PhD Student
(He/Him)

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Saki Imai, PhD Student
(She/Her)

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Inclusive Alexa team: Qi Chang, Mert Inan, Malihe Alikhani, Jennifer Nwogu, Sabit Hassan, Paras Sharma, Kate Atwell, Anthony Sicilia, Yuya Asano

Past students and visitors
 

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Anthony Sicilia, PhD Student
Assistant Professor, West Virginia University 

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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.

Photo credit:  3D Visualization of Basal Ganglia: Subcortical Nuclei in Human Brain Controlling Motor and Cognitive Functions

By Bartek, Education License, Adobe Stock 

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