Short Bio

Dr. Erdal Kayacan received a Ph.D. degree in electrical and electronic engineering at Bogazici University, Istanbul, Turkey. After finishing his post-doctoral research at KU Leuven at the division of mechatronics, biostatistics and sensors (MeBioS) in 2014, he worked in Nanyang Technological University at the School of Mechanical and Aerospace Engineering as an assistant professor for four years. Currently, he is pursuing his research in Aarhus University at the Department of Engineering as an associate professor. He is the Director of Artificial Intelligence in Robotics (Air Lab) laboratory.

Dr. Kayacan is co-writer of a course book “Fuzzy Neural Networks for Real Time Control Applications, 1st Edition Concepts, Modeling and Algorithms for Fast Learning“, Butterworth-Heinemann, Print Book ISBN:9780128026878. (17 Sept 2015).

He is a Senior Member of Institute of Electrical and Electronics Engineers (IEEE). From 1st Jan 2017, he is an Associate Editor of IEEE Transactions on Fuzzy Systems and Technical Editor of the IEEE/ASME Transactions Mechatronics.

Positions

  • Now2018

    Associate Professor

    Aarhus University, Department of Engineering

  • 20182014

    Assistant Professor

    Nanyang Technological University, Mechanical and Aerospace Engineering

  • 20142011

    Post-doctoral Researcher

    University of Leuven (KU Leuven), Division of Mechatronics, Biostatistics and Sensors

Projects Directed (Ongoing)

  • EU
    Vision-based inspection navigation algorithm for ship inspection
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    by European Regional Development Fund
  • EU
    Smart Parking System for Vessels and Ports
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    by European Regional Development Fund
  • EU
    OpenDR: Open Deep Learning Toolkit for Robotics
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    by HORIZON 2020 - LEIT ICT WORK PROGRAMME 2018-2020

Projects Directed (Finished)

  • DHRTC
    Danish Hydrocarbon Research and Technology Centre: Visualisation of Virtual Outcrops Using Aerial Robots
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    by Technical University of Denmark, Danish Hydrocarbon Research and Technology Centre
  • ST Eng-NTU Corp Lab
    ST Eng-NTU Corp Lab: Precise landing for unmanned aerial vehicles
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    by ST Eng-NTU Corp Lab
  • ST Eng-NTU Corp Lab
    ST Eng-NTU Corp Lab: Fuzzy neural network-based learning control of unmanned aerial vehicles
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    by ST Eng-NTU Corp Lab
  • JTC Corporation - NRF
    JTC Corporation - NRF: Automated Construction Quality Assessment Robot System (A-CONQUARS)
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    by JTC Corporation - NRF
  • NTU Start up Grant
    NTU Start up Grant (Learning control algorithms for unmanned aerial vehicles)
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    by Nanyang Technological University
  • MOE Tier 1
    MOE Academic Research Funding (AcRF) Tier 1: Learning-based path planning of unmanned aerial vehicles with vision-based sensing
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    by Nanyang Technological University
  • MOE Tier 1
    MOE Academic Research Funding (AcRF) Tier 1: Model predictive control-moving horizon estimation framework as applied to tilt rotor UAVs and its experimental evaluation
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    by Nanyang Technological University
  • NRF
    NRF - Design of lightweight UAV for 3D Printing
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    by NRF Medium-Sized Centre (MSC)

Publication Database

Research impact

Total citations (by 13.07.2020)

Google scholar [Total citations: 3542 and H-index:31]
Scopus [Total citations: 2601 and H-index:27]
Web of science [Total citations: 1824 and H-index:23]