activity
20192026
most citedUnremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes

243 citations · 325 across the 13 of their papers we have counts for

collaborators

13 papers

cs.HC2026

Beyond Overt Reactions: Analyzing Subtle User Emotional Response to Unexpected In-Vehicle System Behavior

Huy Quyen Ngo, Suresh Kumaar Jayaraman, Brian Mok +4

Modern vehicles, with advanced AI voice and autonomous navigation features, extend beyond traditional driving but, like any autonomous system, can potentially make mistakes or beha…

cs.AI2023★ 4 cited

Synergistic Integration of Large Language Models and Cognitive Architectures for Robust AI: An Exploratory Analysis

Oscar J. Romero, John Zimmerman, Aaron Steinfeld +1

This paper explores the integration of two AI subdisciplines employed in the development of artificial agents that exhibit intelligent behavior: Large Language Models (LLMs) and Co…

cs.RO2023

Optimizing Algorithms From Pairwise User Preferences

Leonid Keselman, Katherine Shih, Martial Hebert +1

Typical black-box optimization approaches in robotics focus on learning from metric scores. However, that is not always possible, as not all developers have ground truth available.…

cs.AI2022

AAAI SSS-22 Symposium on Closing the Assessment Loop: Communicating Proficiency and Intent in Human-Robot Teaming

Michael Goodrich, Jacob Crandall, Aaron Steinfeld +1

The proposed symposium focuses understanding, modeling, and improving the efficacy of (a) communicating proficiency from human to robot and (b) communicating intent from a human to…

cs.CV2022★ 3 cited

Towards Rich, Portable, and Large-Scale Pedestrian Data Collection

Allan Wang, Abhijat Biswas, Henny Admoni +1

Recently, pedestrian behavior research has shifted towards machine learning based methods and converged on the topic of modeling pedestrian interactions. For this, a large-scale da…

cs.RO2021★ 1 cited

Group-based Motion Prediction for Navigation in Crowded Environments

Allan Wang, Christoforos Mavrogiannis, Aaron Steinfeld

We focus on the problem of planning the motion of a robot in a dynamic multiagent environment such as a pedestrian scene. Enabling the robot to navigate safely and in a socially co…