Stefan K. Ehrlich

About

Stefan K. Ehrlich is a pioneering researcher at the intersection of neuroscience, robotics, and brain-computer interfaces, with a primary focus on making human-robot interaction (HRI) more intuitive, adaptive, and neurologically informed. His most influential work centers on harnessing error-related potentials (ErrPs) — brain signals decoded from electroencephalography (EEG) — as a real-time feedback mechanism that enables robots to learn from and adapt to human cognitive responses. His 2018 paper on human-agent co-adaptation using ErrPs (83 citations) and a companion feasibility study (61 citations) established foundational frameworks for this approach, demonstrating that robots can be trained to self-correct based purely on neural signals from observing humans. Ehrlich's broader vision is articulated in his 2020 piece on the neuroengineering challenges of fusing robotics and neuroscience (52 citations), which maps the conceptual and technical frontiers of the field. Beyond error detection, his work spans social signal interpretation in humanoid robots, anticipatory brain responses for collaborative task planning, and assistive brain-robot interfaces for patients with limited mobility. Collectively, his research charts a compelling course toward robots that are not merely programmed, but genuinely responsive to the human mind.

Research Focus

Key Achievements

Top Papers

1. 1
   Human-agent co-adaptation using error-related potentials

   83 citations · 2018
2. 2
   A Feasibility Study for Validating Robot Actions Using EEG-Based Error-Related Potentials

   61 citations · 2018
3. 3
   Neuroengineering challenges of fusing robotics and neuroscience

   52 citations · 2020
4. 4
   A neuro-based method for detecting context-dependent erroneous robot action

   22 citations · 2016
5. 5
   When to engage in interaction — And how? EEG-based enhancement of robot's ability to sense social signals in HRI

   18 citations · 2014
6. 6
   Human-robot collaborative task planning using anticipatory brain responses

   9 citations · 2023
7. 7
   A computational model of human decision making and learning for assessment of co-adaptation in neuro-adaptive human-robot interaction

   7 citations · 2019
8. 8
   A prototype of a P300 based brain-robot interface to enable multi-modal interaction for patients with limited mobility

   6 citations · 2019
9. 9
   A comparative study on adaptive subject-independent classification models for zero-calibration error-potential decoding

   5 citations · 2019

Key Collaborators

Contact & Links