Hello, I'm Daniel Sliwowski

I am a PhD at TU Wien advised by Prof Dongheui Lee , where I work on understanding human and robot task execution, for better autonomous robot performance and human-robot collaboration.

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News

  • Jun 2026: M2R2 has been accepted to ICRA 2026!
  • Jun 2026: ATLAS has been accepted to ARSO 2026!
  • Nov 2025: Our “Constraint-Informed Temporal Action Segmentation” paper was presented at ICCAS 2025.
  • Feb 2025: We are releasing the REASSEMBLE dataset.
  • Oct 2025: Our “Multimodal Anomaly Detection with a Mixture-of-Experts” paper was accepted at IROS 2025.
  • Feb 2025: Our ConditionNET paper got accepted at Robotics and Automation Letters!
  • Dec 2024: Our “Multimodal Transformer Models for Human Action Classification” paper at RiTA has won the reward of the Best Intelligence Paper.
  • Sep 2024: Our “Multimodal Transformer Models for Human Action Classification” paper was accepted at RiTA.
  • Sep 2023: HOI4ABOT has been accepted to CoRL 2023.
  • Sep 2022: I started my Ph.D. studies under Dongheui Lee at the Autonomous Systems Lab in TU Wien!

Publications

M2R2: MultiModal Robotic Representation for Temporal Action Segmentation

M2R2: MultiModal Robotic Representation for Temporal Action Segmentation

Daniel Sliwowski, Dongheui Lee
IEEE International Conference on Robotics & Automation (ICRA 2026)

We propose a multimodal robotic representation for temporal action segmentation in long-horizon manipulation tasks.

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ATLAS: An Annotation Tool for Long-horizon Robotic Action Segmentation

ATLAS: An Annotation Tool for Long-horizon Robotic Action Segmentation

Sergej Stanovcic, Daniel Sliwowski, Dongheui Lee
IEEE International Conference on Advanced Robotics and Its Social Impact (ARSO 2026)

We present an annotation tool designed for efficient labeling of long-horizon robotic action segmentation datasets.

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Constraint-Informed Temporal Action Segmentation

Constraint-Informed Temporal Action Segmentation

Daniel Sliwowski, SeongSu Park, KwanHyun Lee, Donghyeon Kim, JeeHwan Ryu, Dongheui Lee
25th International Conference on Control, Automation and Systems (ICCAS 2025)

We propose constraint-informed temporal action segmentation leveraging robot kinematic and task constraints.

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Multimodal Anomaly Detection with a Mixture-of-Experts

Multimodal Anomaly Detection with a Mixture-of-Experts

Christoph Willibald, Daniel Sliwowski, Dongheui Lee
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025)

We propose a mixture-of-experts approach for multimodal anomaly detection in robotic manipulation tasks.

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REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly

REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly

Daniel Sliwowski, Shail Jadav, Sergej Stanovcic, Johannes Heidersberger, Jedrzej Orbik, Dongheui Lee
Robotics: Science and Systems 2025 (RSS 2025)

We release a multimodal dataset for long-horizon contact-rich assembly and disassembly tasks

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Multimodal Transformer Models for Human Action Classification

Multimodal Transformer Models for Human Action Classification

Zoltan Varga, Esteve Valls Mascaro, Daniel Sliwowski, Dongheui Lee
RiTA 2024 Winner of Best Intelligence Paper at the International Conference on Robot Intelligence Technology and Applications (RiTA 2024)

We investigate how best to fuse multimodal information for the task of human action recognition.

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ConditionNET: Learning Preconditions and Effects for Anomaly Detection and Recovery

ConditionNET: Learning Preconditions and Effects for Anomaly Detection and Recovery

Daniel Sliwowski, Dongheui Lee
IEEE Robotics and Automation Letters

Learn Preconditions and Effects of actions in a data-driven manner, and leverage the learned conditions for anomaly detection.

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HOI4ABOT: Human-Object Interaction Anticipation for Assistive roBOTs

HOI4ABOT: Human-Object Interaction Anticipation for Assistive roBOTs

Esteve Valls Mascaro, Daniel Sliwowski, Dongheui Lee
CoRL 2023

Detect and anticipate human-object interactions for intention reading, which facilitate robots to assist humans.

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