Bilde av Perera, Lokukaluge Prasad Channa
Bilde av Perera, Lokukaluge Prasad Channa
Institutt for teknologi og sikkerhet prasad.perera@uit.no +4777660282 93003615 Tromsø TEK 3.021

Perera, Lokukaluge Prasad Channa


Professor

Stillingsbeskrivelse

LP Perera received BSc (1999) in Mechanical Engineering and MSc (2001) in Systems & Controls from Oklahoma State University, USA and PhD (2012) in Naval Architecture and Marine Engineering from Technical University of Lisbon, Portugal. Currently, he is a Professor at UiT The Arctic University of Norway, Norway. His research experience includes SINTEF Ocean – Norway (2014-2017), Center for Marine Technology and Engineering - Portugal (2008-2012) and Advanced Technology Research Center – USA (1998-2001). His academic experience includes Naval & Maritime Academy - Sri Lanka (2005-2008) and Ocean University of Sri Lanka - Sri Lanka (2003-2005). Furthermore, Prof.Perera was a visiting lecturer (2001-2005) for several academic institutes in Sri Lanka: University of Ruhuna, University of Moratuwa, Open University of Sri Lanka, Colombo International Nautical & Engineering College. His industrial experience includes Wartsila Finland - Finland (2012-2014). Prof. Perera has published more than 100 peer-reviewed papers in reputed international journals and conferences. He has also been categorized into a group of the WORLD'S TOP 2% SCIENTISTS in 2021-2022 by a  Stanford University study .


  • Sivaraman Sivaraj, Suresh Rajendran, Lokukaluge Prasad Channa Perera :
    Data driven control based on Deep Q-Network algorithm for heading control and path following of a ship in calm water and waves
    Ocean Engineering 2022 ARKIV / DOI
  • Tae-Eun Kim, Lokukaluge Prasad Channa Perera, Magne-Petter Sollid, Bjørn-Morten Batalden, Are Kristoffer Sydnes :
    Safety challenges related to autonomous ships in mixed navigational environments
    WMU Journal of Maritime Affairs (JoMA) 2022 DOI
  • Hadi Taghavifar, Lokukaluge Prasad Channa Perera :
    Life Cycle Assessment of Different Marine Fuel Types and Powertrain Configurations for Financial and Environmental Impact Assessment in Shipping
    The American Society of Mechanical Engineers (ASME) 2022 DOI
  • Mahmood Taghavi, Lokukaluge Prasad Channa Perera :
    Data Driven Digital Twin Applications Towards Green Ship Operations
    The American Society of Mechanical Engineers (ASME) 2022 DOI
  • Lokukaluge Prasad Channa Perera, Kostas Belibassakis, Evangelos Filippas, H D Maneesha Nishadini Premasiri :
    Advanced Data Analytics Based Hybrid Engine-Propeller Combinator Diagram for Green Ship Operations
    The American Society of Mechanical Engineers (ASME) 2022 DOI
  • Nikolaos P. Ventikos, Lokukaluge Prasad Channa Perera, Panagiotis Sotiralis, Emmanouil Annetis, Eirini V. Stamatopoulou :
    A Life-Cycle Cost Framework for Onboard Emission Reduction Technologies: The Case of the Flapping-Foil Thruster Propulsion Innovation
    The American Society of Mechanical Engineers (ASME) 2022 DOI
  • Yufei Wang, Lokukaluge Prasad Channa Perera, Bjørn-Morten Batalden :
    The Comparison of Two Kinematic Motion Models for Autonomous Shipping Maneuvers
    The American Society of Mechanical Engineers (ASME) 2022 DOI
  • Khanh Quang Bui, Lokukaluge Prasad Channa Perera, Jan Emblemsvåg, Halvor Schøyen :
    Life-Cycle Cost Analysis on a Marine Engine Innovation for Retrofit: A Comparative Study
    The American Society of Mechanical Engineers (ASME) 2022 DOI
  • Khanh Quang Bui, Lokukaluge Prasad Channa Perera, Jan Emblemsvåg :
    Life-cycle cost analysis of an innovative marine dual-fuel engine under uncertainties
    Journal of Cleaner Production 2022 ARKIV / DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    Proactive Collision Avoidance for Autonomous Ships: Leveraging Machine Learning to Emulate Situation Awareness
    IFAC-PapersOnLine 2021 ARKIV / DOI
  • Khanh Quang Bui, Lokukaluge Prasad Perera, Jan Emblemsvåg :
    Development of a Life-cycle Cost Framework for Retrofitting Marine Engines towards Emission Reduction in Shipping
    IFAC-PapersOnLine 2021 ARKIV / DOI
  • Khanh Quang Bui, Lokukaluge Prasad Perera :
    Advanced data analytics for ship performance monitoring under localized operational conditions
    Ocean Engineering 2021 ARKIV / DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    Deep Representation Learning-Based Vessel Trajectory Clustering for Situation Awareness in Ship Navigation
    CRC Press 2021 DOI
  • Lokukaluge Prasad Perera :
    Topological surfaces based advanced data analytics to support industrial digitalization in shipping
    CRC Press 2021 DOI
  • Lokukaluge Prasad Perera, N P Ventikos, Sven Rolfsen, Anders Öster :
    Advanced Data Analytics towards Energy Efficient and Emission Reduction Retrofit Technology Integration in Shipping
    International Society of Offshore & Polar Engineers 2021
  • Yufei Wang, Lokukaluge Prasad Perera, Bjørn-Morten Batalden :
    Particle Filter Based Ship State and Parameter Estimation for Vessel Maneuvers
    International Society of Offshore & Polar Engineers 2021
  • Brian Murray, Lokukaluge Prasad Perera :
    An AIS-based deep learning framework for regional ship behavior prediction
    Reliability Engineering & System Safety 2021 ARKIV / DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness
    Journal of Ocean Engineering and Science 2021 ARKIV / DOI
  • Khanh Q. Bui, Lokukaluge Prasad Perera :
    A Decision Support Framework for Cost-Effective and Energy Efficient Shipping
    The American Society of Mechanical Engineers (ASME) 2020 DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    Unsupervised Trajectory Anomaly Detection for Situation Awareness in Maritime Navigation
    The American Society of Mechanical Engineers (ASME) 2020 ARKIV / DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    A dual linear autoencoder approach for vessel trajectory prediction using historical AIS data
    Ocean Engineering 2020 ARKIV / DOI
  • Khanh Quang Bui, Lokukaluge Prasad Perera :
    The Compliance Challenges in Emissions Control Regulations to Reduce Air Pollution from Shipping
    IEEE (Institute of Electrical and Electronics Engineers) 2019 ARKIV / DOI
  • Lokukaluge Prasad Perera, Bjørn-Morten Batalden :
    Possible COLREGs Failures under Digital Helmsman of Autonomous Ships
    IEEE (Institute of Electrical and Electronics Engineers) 2019 ARKIV / DOI
  • Lokukaluge Prasad Perera, Karen Vanessa Czachorowski :
    Decentralized System Intelligence in Data Driven Networks for Shipping Industrial Applications: Digital Models to Blockchain Technologies
    IEEE (Institute of Electrical and Electronics Engineers) 2019 ARKIV / DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels
    The American Society of Mechanical Engineers (ASME) 2019 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brian Murray :
    Situation Awareness of Autonomous Ship Navigation in a Mixed Environment under Advanced Ship Predictor
    The American Society of Mechanical Engineers (ASME) 2019 DOI
  • Lokukaluge Prasad Perera :
    Deep Learning towards Autonomous Ship Navigation and Possible COLREGs Failures
    Journal of Offshore Mechanics and Arctic Engineering 2019 ARKIV / DOI
  • Lokukaluge Prasad Perera, Mario M. Machado, Anders Valland, Diego A.P. Manguinho :
    Failure intensity of offshore power plants under varying maintenance policies
    Engineering Failure Analysis 2019 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Ship Performance and Navigation Information under High Dimensional Digital Models
    Journal of Marine Science and Technology 2019 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Ship Performance and Navigation Data Compression and Communication under Autoencoder System Architecture
    Journal of Ocean Engineering and Science 2018 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Ship speed power performance under relative wind profiles in relation to sensor fault detection
    Journal of Ocean Engineering and Science 2018 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    An overview of Data Veracity Issues in Ship Performance and Navigation Monitoring
    The American Society of Mechanical Engineers (ASME) 2018 DOI
  • Lokukaluge Prasad Perera :
    Autonomous Ship Navigation under Deep Learning and the challenges in COLREGs
    The American Society of Mechanical Engineers (ASME) 2018 DOI
  • Brian Murray, Lokukaluge Prasad Perera :
    A data-driven approach to vessel trajectory prediction for safe autonomous ship operations
    IEEE (Institute of Electrical and Electronics Engineers) 2018 DOI
  • R Pascoal, Lokukaluge Prasad Perera, Carlos Guedes Soares :
    Estimation of Directional Sea Spectra from Ship Motions in Sea Trials
    Ocean Engineering 2017 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Marine Engine-Centered Data Analytics for Ship Performance Monitoring
    Journal of Offshore Mechanics and Arctic Engineering 31. januar 2017 ARKIV / DOI
  • Lokukaluge Prasad Perera :
    Handling Big Data in Ship Performance and Navigation Monitoring
    Royal Institution of Naval Architects 2017
  • Lokukaluge Prasad Perera :
    Navigation vector based ship maneuvering prediction
    Ocean Engineering 2017 ARKIV / DOI
  • Brage Mo, Christian Steinebach, Lokukaluge Prasad Perera, Petter Dehli, Tow Foong Lim :
    OMAE2017-61219 Automated System for Fleet Benchmarking and Assessment of Technical Condition
    The American Society of Mechanical Engineers (ASME) 2017 ARKIV / DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Development of Data Analytics in Shipping
    IGI Global 2017 DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Machine intelligence based data handling framework for ship energy efficiency
    IEEE Transactions on Vehicular Technology 05. juni 2017 ARKIV / DOI
  • Lokukaluge Prasad Perera :
    Industrial IoT to Predictive Analytics: A Reverse Engineering Approach from Shipping
    CEUR Workshop Proceedings 2017 ARKIV
  • Lokukaluge Prasad Perera, Brage Mo :
    OMAE2017-61011 Digitalization of Seagoing Vessels Under High Dimensional Data Driven Models
    The American Society of Mechanical Engineers (ASME) 2017 DOI
  • Lokukaluge Prasad Perera, Brage Mo :
    Visual analytics in ship performance and navigation information for sensor specific fault detection
    The American Society of Mechanical Engineers (ASME) 2017 DOI
  • Tae Eun Kim, Lokukaluge Prasad Channa Perera, Magne-Petter Sollid, Bjørn-Morten Batalden, Are K. Sydnes :
    Publisher Correction: Safety challenges related to autonomous ships in mixed navigational environments (WMU Journal of Maritime Affairs, (2022), 21, 2, (141-159), 10.1007/s13437-022-00277-z)
    WMU Journal of Maritime Affairs (JoMA) 2022 DOI
  • Tae-Eun Kim, Are Kristoffer Sydnes, Bjørn-Morten Batalden, Lokukaluge Prasad Channa Perera :
    Unlocking long-term safety, environmental and economic values of Maritime Autonomous Surface Ships (MASS)
    WMU Journal of Maritime Affairs (JoMA) 2022 DOI
  • Brian Murray, Lokukaluge Prasad Perera, Egil Pedersen, Henrique Murilo Gaspar :
    Machine Learning for Enhanced Maritime Situation Awareness - Leveraging Historical AIS Data for Ship Trajectory Prediction (PhD Thesis)
    2021 FULLTEKST
  • Lokukaluge Prasad Perera, Brage Mo, Matthias P. Nowak :
    OMAE2017-61120 Visualization of Relative Wind Profiles in Relation to Actual Weather Conditions of Ship Routes
    2017
  • Lokukaluge Prasad Perera, Brage Mo :
    OMAE2017-61011 Digitalization of Seagoing Vessels Under High Dimensional Data Driven Models
    2017
  • Lokukaluge Prasad Perera, Brage Mo :
    OMAE2017-61118 Visual Analytics in Ship Performance and Navigation Information for Sensor Specific Fault Detection
    2017

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    Forskningsinteresser

    Maritime and Offshore Systems & Controls, Instrumentation, Data Analytics, Machine Learning & Artificial Intelligence, Autonomous Navigation, Intelligent Guidance & Decision Support, Condition Monitoring & Condition based Maintenance, Energy Efficiency & Emission Control, Safety, Risk and Reliability.

    Curent Research Projects:

    Undervisning

    • MFA-2016 Marine Marine Systems and Machinery
    • MFA-2100 Maritime Digitalization
    • MFA-2101 Maritime Data Analytics
    • TEK-3017/8017 Applied Optimal Estimation in Engineering Systems
    • TEK-3014 Navigation Systems
    • MFA-8010 Maritime MTO (Human Technology Organization)
    • TEK-8805 Special curriculum

    Medlem i forskningsgruppe


    CV

    L. P. Perera received BSc (1999) in Mechanical Engineering and MSc (2001) in Systems & Controls from Oklahoma State University, USA and PhD (2012) in Naval Architecture and Marine Engineering from Technical University of Lisbon, Portugal. Currently, he is a Professor at UiT The Arctic University of Norway, Norway. His research experience includes SINTEF Ocean – Norway (2014-2017), Centre for Marine Technology and Engineering - Portugal (2008-2012) and Advanced Technology Research Center – USA (1998-2001). His academic experience includes Naval & Maritime Academy - Sri Lanka (2005-2008) and Ocean University of Sri Lanka - Sri Lanka (2003-2005). Furthermore, Dr. Perera was a visiting lecture (2001-2005) for several academic institutes in Sri Lanka: University of Ruhuna, University of Moratuwa, Open University of Sri Lanka, Colombo International Nautical & Engineering College. His industrial experience includes Wartsila Finland - Finland (2012-2014). Prof. Perera has published more than 80 peer-reviewed papers in reputed international journals and conferences. He has also been categorized into a group of the WORLD’S TOP 2% SCIENTISTS in 2021 by the Stanford University study.

    Linkedin Profile