Bilde av Tran, Ngoc Nha Vi
Bilde av Tran, Ngoc Nha Vi
Associate Professor Department of Computer Science vi.n.tran@uit.no +4777646332 You can find me here

Ngoc Nha Vi Tran


Job description

Dr. Vi Ngoc-Nha Tran is an Associate Professor of Computer Science at UiT The Arctic University of Norway. She earned her Ph.D. in Computer Science from UiT The Arctic University of Norway and has been a visiting scholar at the Department of Computer Science at Rutgers University, USA. Dr. Tran was a recipient of the Erasmus Mundus full scholarship, completing a joint European M.S. in Software Engineering at the Blekinge Institute of Technology, Sweden, and the Technical University of Kaiserslautern, Germany. Her research focuses on High-performance and Energy-efficient Computing, Machine Learning, and Bioinformatics, where she continues to contribute to advancements in these dynamic fields of Computer Science.


  • Solveig Flatebø, Ngoc Nha Vi Tran, Catharina Elisabeth Arfwedson Wang, Lars Ailo Aslaksen Bongo :
    Social robots in research on social and cognitive development in infants and toddlers: A scoping review
    PLOS ONE 15. May 2024 ARKIV / DOI
  • Jingyi Liang, Vi Ngoc-Nha Tran, Colin Hemez, Pia Abel zur Wiesch :
    Current Approaches of Building Mechanistic Pharmacodynamic Drug-Target Binding Models
    Springer 2022 DOI
  • Vi Ngoc-Nha Tran, Alireza Shams, Sinan Ascioglu, Antal Martinecz, Jingyi Liang, Fabrizio Clarelli et al.:
    vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding
    BMC Bioinformatics 2022 ARKIV / DOI
  • Vi Ngoc-Nha Tran, Tommy Skaue Øines, Alexander Horsch, Hoai Phuong Ha :
    REOH: Using Probabilistic Network for Runtime Energy Optimization of Heterogeneous Systems
    Proceedings of the International Conference on Parallel and Distributed Systems 2018 DOI
  • Ngoc Nha Vi Tran, Brendan Barry, Hoai Phuong Ha :
    RTHpower: Accurate Fine-grained Power Models for Predicting Race-to-halt Effect on Ultra-low Power Embedded Systems
    IEEE (Institute of Electrical and Electronics Engineers) 2016 DOI
  • Vi Ngoc-Nha Tran, Hoai Phuong Ha :
    ICE: A General and Validated Energy Complexity Model for Multithreaded Algorithms
    Proceedings of the International Conference on Parallel and Distributed Systems 2016 DOI
  • Vi Ngoc-Nha Tran, Brendan Barry, Hoai Phuong Ha :
    Power models supporting energy-efficient co-design on ultra-low power embedded systems
    IEEE (Institute of Electrical and Electronics Engineers) 2016 DOI
  • Vi Ngoc-Nha Tran, Alireza Shams, Sinan Ascioglu, Antal Martinecz, Jingyi Liang, Fabrizio Clarelli et al.:
    vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding
    2020 FULLTEKST
  • Vi Ngoc-Nha Tran, Tommy Oines, Alexander Horsch, Hoai Phuong Ha :
    REOH: Using Probabilistic Network for Runtime Energy Optimization of Heterogeneous Systems
    2018
  • Vi Ngoc-Nha Tran, Tommy Oines, Alexander Horsch, Hoai Phuong Ha :
    REOH: Runtime Energy Optimization for Heterogeneous Systems
    2018 FULLTEKST / DATA
  • Hoai Phuong Ha, Vi Ngoc-Nha Tran, Ibrahim Umar, Aras Atalar, Anders Gidenstam, Paul Renaud-Goud et al.:
    Power models, energy models and libraries for energy-efficient concurrent data structures and algorithms, EXCESS deliverable D2.3
    2016 PROSJEKT / ARKIV
  • Vi Ngoc-Nha Tran, Hoai Phuong Ha :
    ICE: A General and Validated Energy Complexity Model for Multithreaded Algorithms
    2016 FULLTEKST
  • Vi Ngoc-Nha Tran, Hoai Phuong Ha :
    ICE: A General and Validated Energy Complexity Model for Multithreaded Algorithms
    2016
  • Vi Ngoc-Nha Tran, Hoai Phuong Ha :
    ICE: A General and Validated Energy Complexity Model for Multithreaded Algorithms
    2016
  • Hoai Phuong Ha, Vi Ngoc-Nha Tran, Ibrahim Umar, Aras Atalar, Anders Gidenstam, Paul Renaud-Goud et al.:
    Report on the final prototype of programming abstractions for energy-efficient inter-process communication, EXCESS deliverable D2.4
    2016 ARKIV
  • Ngoc Nha Vi Tran, Brendan Barry, Hoai Phuong Ha :
    Power Models Supporting Energy-efficient Co-design on Ultra-low Power Embedded Systems
    2016
  • Ngoc Nha Vi Tran, Brendan Barry, Hoai Phuong Ha :
    RTHpower: Accurate Fine-grained Power Models for Predicting Race-to-halt Effect on Ultra-low Power Embedded Systems
    2016
  • Yosandra Sandoval, Dennis Hoppe, Dmitry Khabi, Micheal Gienger, Christoph Kessler, Lu Li et al.:
    EXCESS: Execution Models for Energy-Efficient Computing Systems
    2015
  • Christoph Kessler, Lu Li, Usman Dastgeer, Rosandra Cuello, Oskar Sjöström, Hoai Phuong Ha et al.:
    Energy-Tuneable Domain-Specific Language/Library for Linear System Solving, EXCESS deliverable D1.3
    2015
  • Hoai Phuong Ha, Ngoc Nha Vi Tran, Ibrahim Umar, Aras Atalar, Anders Gidenstam, Paul Renaud-Goud et al.:
    White-box methodologies, programming abstractions and libraries for energy-efficient computing, EXCESS deliverable D2.2
    2015 PROSJEKT / ARKIV
  • Ibrahim Umar, Ngoc Nha Vi Tran, Saeed Shariati, Otto Anshus, Hoai Phuong Ha :
    The Arctic Green Computing Group
    2015
  • Dmitry Khabi, Ngoc Nha Vi Tran, Ivan Walulya :
    Report on the first evaluation results and discussion, EXCESS deliverable D5.4
    2015
  • Christoph Kessler, Lu Li, Usman Dastgeer, Philippas Tsigas, Anders Gidenstam, Paul Renaud-Goud et al.:
    Early validation of system-wide energy compositionality and affecting factors on the EXCESS platforms, EXCESS deliverable D1.1
    2014
  • Hoai Phuong Ha, Ngoc Nha Vi Tran, Ibrahim Umar, Philippas Tsigas, Anders Gidenstam, Paul Renaud-Goud et al.:
    Models for energy consumption of data structures and algorithms, EXCESS deliverable D2.1
    2014 PROSJEKT / ARKIV

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    Research interests

    Bioinformatics and Health Technology

    Machine Learning

    High-performance and Energy-efficient Computing

    Teaching

    • INF-2200 Computer Architecture and Organization, 2022-present
    • INF-2900 Software Engineerng, 2022-present
    • INF-2202 Concurrent and Data-Intensive Programming, 2019 

    Member of research group