Julie Shah
Massachusetts Institute of Technology
Associate Professor
Department of Aeronautics and Astronautics
Research Area
#Computer science#Artificial intelligence#Robot#Human-computer interaction#Human-robot interaction#Machine learning#Robotics#Engineering#Knowledge management#Task analysis
SCIE paper information
Papers relevant to ‘Computer science’: 13
Research performance of SCIE papers matching with ‘Computer science’
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Decision-making authority, team efficiency and human worker satisfaction in mixed human---robot teams
2015/10 AUTONOMOUS ROBOTS 1.548 Impact Factor 160 citations
Implicit Coordination Strategies for Effective Team Communication
2016/04 HUMAN FACTORS 1.99 Impact Factor 71 citations
Papers for author ‘Julie Shah’: 20
Number of published SCIE papers by year
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Decision-making authority, team efficiency and human worker satisfaction in mixed human---robot teams
2015/10 AUTONOMOUS ROBOTS 1.548 Impact Factor 160 citations
An Architecture for Online Affordance-based Perception and Whole-body Planning
2015/03 JOURNAL OF FIELD ROBOTICS 2.059 Impact Factor 148 citations
conference information
Papers relevant to ‘Computer science’: 24
Research performance of Top-tier Conference matching with ‘Computer science’
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
2014/12 NEURIPS Top-tier Conference 203 citations
Mind the Gap: a generative approach to interpretable feature selection and extraction
2015/12 NEURIPS Top-tier Conference 91 citations
Papers for author ‘Julie Shah’: 25
Number of published Top-tier Conference by year
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
2014/12 NEURIPS Top-tier Conference 203 citations
Mind the Gap: a generative approach to interpretable feature selection and extraction
2015/12 NEURIPS Top-tier Conference 91 citations
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