34 citations · 64 across the 8 of their papers we have counts for
9 papers
Language-Grounded Control for Coordinated Robot Motion and Speech
Ravi Tejwani, Chengyuan Ma, Paco Gomez-Paz +2
Recent advancements have enabled human-robot collaboration through physical assistance and verbal guidance. However, limitations persist in coordinating robots' physical motions an…
An Avatar Robot Overlaid with the 3D Human Model of a Remote Operator
Ravi Tejwani, Chengyuan Ma, Paolo Bonato +1
Although telepresence assistive robots have made significant progress, they still lack the sense of realism and physical presence of the remote operator. This results in a lack of…
Neural Topic Modeling of Psychotherapy Sessions
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi +1
In this work, we compare different neural topic modeling methods in learning the topical propensities of different psychiatric conditions from the psychotherapy session transcripts…
Incorporating Rich Social Interactions Into MDPs
Ravi Tejwani, Yen-Ling Kuo, Tianmin Shu +5
Much of what we do as humans is engage socially with other agents, a skill that robots must also eventually possess. We demonstrate that a rich theory of social interactions origin…
Migratable AI: Personalizing Dialog Conversations with migration context
Ravi Tejwani, Boris Katz, Cynthia Breazeal
The migration of conversational AI agents across different embodiments in order to maintain the continuity of the task has been recently explored to further improve user experience…
Migratable AI : Investigating users' affect on identity and information migration of a conversational AI agent
Ravi Tejwani, Boris Katz, Cynthia Breazeal
Conversational AI agents are becoming ubiquitous and provide assistance to us in our everyday activities. In recent years, researchers have explored the migration of these agents a…
Migratable AI: Effect of identity and information migration on users perception of conversational AI agents
Ravi Tejwani, Felipe Moreno, Sooyeon Jeong +2
Conversational AI agents are proliferating, embodying a range of devices such as smart speakers, smart displays, robots, cars, and more. We can envision a future where a personal c…
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel +8
Despite significant recent advances in deep neural networks, training them remains a challenge due to the highly non-convex nature of the objective function. State-of-the-art metho…
Autism Classification Using Brain Functional Connectivity Dynamics and Machine Learning
Ravi Tejwani, Adam Liska, Hongyuan You +2
The goal of the present study is to identify autism using machine learning techniques and resting-state brain imaging data, leveraging the temporal variability of the functional co…