Matthias Scheutz
Scholar

Matthias Scheutz

Google Scholar ID: 5yT3GScAAAAJ
Karol Family Applied Technology Professor of Computer Science, Tufts University
Artificial intelligenceroboticshuman-robot interactionnatural language understanding
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Citations & Impact
All-time
Citations
7,915
 
H-index
45
 
i10-index
169
 
Publications
20
 
Co-authors
0
 
Contact
No contact links provided.
Publications
14 items
Build on Priors: Vision--Language--Guided Neuro-Symbolic Imitation Learning for Data-Efficient Real-World Robot Manipulation
2026
Cited
0
Novelty Adaptation Through Hybrid Large Language Model (LLM)-Symbolic Planning and LLM-guided Reinforcement Learning
2026
Cited
0
The Price Is Not Right: Neuro-Symbolic Methods Outperform VLAs on Structured Long-Horizon Manipulation Tasks with Significantly Lower Energy Consumption
2026
Cited
0
Where Norms and References Collide: Evaluating LLMs on Normative Reasoning
2026
Cited
0
Achieving Safe Control Online through Integration of Harmonic Control Lyapunov-Barrier Functions with Unsafe Object-Centric Action Policies
2025
Cited
0
IntelliProof: An Argumentation Network-based Conversational Helper for Organized Reflection
2025
Cited
0
LLMs and their Limited Theory of Mind: Evaluating Mental State Annotations in Situated Dialogue
2025
Cited
0
Few-Shot Neuro-Symbolic Imitation Learning for Long-Horizon Planning and Acting
2025
Cited
0
Resume (English only)
Academic Achievements
  • He has over 400 peer-reviewed publications in areas such as artificial intelligence, artificial life, agent-based computing, natural language understanding, cognitive modeling, robotics, human-robot interaction, and foundations of cognitive science.
Research Experience
  • He is the Karol Family Applied Technology Professor of Computer and Cognitive Science at Tufts University, Director of the Human-Robot Interaction Laboratory, and the HRI Masters and PhD programs.
Education
  • Ph.D. in Philosophy from the University of Vienna; Joint Ph.D. in Cognitive Science and Computer Science from Indiana University.
Background
  • His research focuses on complex ethical cognitive robots with natural language interaction, problem-solving, and instruction-based learning capabilities in open worlds.
Co-authors
0 total
Co-authors: 0 (list not available)