Lennart Wachowiak

Lennart Wachowiak

PhD Student at the Centre for Doctoral Training in Safe and Trusted Artificial Intelligence

King's College London

Biography

I am a PhD candidate at King’s College and Imperial College London, where I am part of a cohort researching how to make AI safe and trustworthy. In my current project, I am investigating how robots can learn to proactively explain their decisions and assist people in collaborative scenarios. As part of this, I train machine learning models to predict when explanations are needed and what they should be about by interpreting the user’s non-verbal behaviour and contextual task clues.

I love interdisciplinary work, learning about different perspectives, and combining them to get a rich understanding of a phenomenon. Beyond designing human–robot experiments, for which I draw on my background in cognitive science and AI, I am researching conceptual metaphors and image schemas in text corpora using tools from natural language processing and theories from cognitive linguistics.

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Interests
  • Human–Robot Interaction
  • User-centered Explanations
  • Natural Language Processing for Cognitive Linguistics
Education
  • PhD in Safe and Trusted AI, 2021-2025

    King's College London, Imperial College London

  • MSc in Cognitive Science, 2018-2021

    Joint Degree with University of Vienna, University of Ljubljana, Comenius University Bratislava, Eötvös Loránd University Budapest

  • BSc in Computer Science, 2014-2017

    University of Paderborn

Publications

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(2024). Predicting When and What to Explain From Multimodal Eye Tracking and Task Signals. Transactions on Affective Computing.

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(2024). A Taxonomy of Explanation Types and Need Indicators in Human–Agent Collaborations. Journal of Social Robotics.

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(2024). When Do People Want an Explanation from a Robot?. HRI.

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(2023). The Image Schema VERTICALITY: Definitions and Annotation Guidelines. Image Schema Day.

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(2023). A Survey of Evaluation Methods and Metrics for Explanations in Human–Robot Interaction (HRI). ICRA Explainable Robotics Workshop.

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(2022). Analysing Eye Gaze Patterns during Confusion and Errors in Human–Agent Collaborations. RO-MAN.

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(2022). Towards Autonomous Collaborative Robots that Adapt and Explain. ICRA Workshop on Prediction and Anticipation Reasoning in HRI.

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(2022). Extracting Terminological Concept Systems from Natural Language Text. Cognitive Technologies.

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(2021). CogALex 2.0: Impact of Data Quality on Lexical-Semantic Relation Prediction. NeurIPS DCAI Workshop.

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(2021). Multilingual Extraction of Terminological Concept Systems. Workshop on Deep Learning and Neural Approaches for Linguistic Data.

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(2021). Towards Learning Terminological Concept Systems from Multilingual Natural Language Text. Conference on Language, Data and Knowledge (awarded best student paper).

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(2020). CogALex-VI Shared Task: Transrelation - A Robust Multilingual Language Model for Multilingual Relation Identification. Workshop on the Cognitive Aspects of the Lexicon (1st place in CogALex shared task).

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