Laurel Riek

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Dr. Laurel Riek is an Associate Professor in Computer Science and Engineering at the University of California, San Diego, with joint appointments in the Department of Emergency Medicine and Contextual Robotics Institute. Dr. Riek directs the Healthcare Robotics Lab, and leads research in human-robot teaming, computer vision, and healthcare engineering, and builds autonomous systems which work proximately with people. Riek’s current research projects have applications in critical care, neurorehabilitation, and home health. Dr. Riek received a Ph.D. in Computer Science from the University of Cambridge, and B.S. in Logic and Computation from Carnegie Mellon. Riek served as a Senior Artificial Intelligence Engineer and Roboticist at The MITRE Corporation from 2000-2008, working on learning and vision systems for robots, and held the Clare Boothe Luce chair in Computer Science and Engineering at the University of Notre Dame from 2011-2016. Dr. Riek has received the NSF CAREER Award, AFOSR Young Investigator Award, Qualcomm Research Award, and multiple best paper awards.

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Taking an (Embodied) Cue From Community Health: Designing Dementia Caregiver Support Technology to Advance Health Equity

Situating Robots in the Emergency Department

JESSIE: Synthesizing social robot behaviors for personalized neurorehabilitation and beyond

Robot-Centric Perception of Human Groups

Unseen Salient Object Discovery for Monocular Robot Vision

Robots for Joy, Robots for Sorrow: Community Based Robot Design for Dementia Caregivers

Modeling and Synthesizing Idiopathic Facial Paralysis

Coordinating Clinical Teams: Using Robots to Empower Nurses to Stop the Line

Preference Learning in Assistive Robotics: Observational Repeated Inverse Reinforcement Learning

Reframing Assistive Robots to Promote Successful Aging

Expressive Robotic Patient Simulators for Clinical Education

Healthcare Robotics

Faster Robot Perception Using Salient Depth Partitioning

Using Facially Expressive Robots to Calibrate Clinical Pain Perception

Movement Coordination in Human-Robot Teams: A Dynamical Systems Approach

Exploring Implicit Human Responses to Robot Mistakes in a Learning from Demonstration Task

Visual TASK: A Collaborative Cognitive Aid for Acute Care Resuscitation

A Method for Automatic Detection of Psychomotor Entrainment