Dinh Ngoc Minh

Dinh Ngoc Minh

dinh ngoc minh engineering
School: Science & Technology
Department: Software Engineering
Position: Senior Lecturer
Location: RMIT Saigon South
Email: minh.dinh4@rmit.edu.vn

Dr. Minh Ngoc Dinh received a Ph.D. in Computer Science from Monash University, Australia. His research expertise is in computational science, high-performance computing, and artificial intelligence (AI). His expertise is developed through his previous positions at Monash University, The University of Queensland, and the Queensland Cyber Infrastructure Foundation.

Dr. Dinh's recent research projects develop a Deep Neural Network debugger, an OCR pipeline for recognizing and transcribing Vietnamese doctor handwritings, and a scalable machine-learning pipeline for enhancing computational modeling techniques.

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  • Doctor of Philosophy in Computer Science Monash University, Caulfield Campus. Thesis: “Data-centric parallel debugging technique for petascale computers”
  • Bachelor of Computer Science (First Class Honours) Monash University, Caulfield Campus. Thesis: “A high throughput Grid based environment for real time bio-medical imaging”
  • Graduate Certificate in Higher Education The University of Queensland, St Lucia Campus
  • Software Engineering
  • Computer Science
  • High Performance Computing 
  • Distributed Computing and Context Aware Computing 
  • Computational Science 
  • Artificial Intelligence and Machine Learning

Advanced Technologies for Social Impact:

  • M. N. Dinh, J. Nygate, V. H. M. Tu, and C. L. Thwaites, "New technologies to improve healthcare in low- and middle-income countries: Global Grand Challenges satellite event, Oxford University Clinical Research Unit, Ho Chi Minh City, 17th-18th September 2019," Wellcome Open Research, vol. 5, 2020. 
  • R. G. Dwyer, H. A. Campbell, R. D. Pillans, M. E. Watts, B. J. Lyon, S. M. Guru, M. N. Dinh, H. P. Possingham, C. E. Franklin, “Using individual‐based movement information to identify spatial conservation priorities for mobile species”, in Journal of Conservation Biology, 2019. 
  • L. M. Bland, T. J. Regan, M. N. Dinh, R. Ferrari, D. A. Keith, R. Lester, D. Mouillot, N. J. Murray, H. A. Nguyen, E. Nicholson, "Using multiple lines of evidence to assess the risk of ecosystem collapse," in Proceedings of The Royal Society B, 2017

HPC and Computational Science:

  • M. N. Dinh, D. Abramson, and C. Jin, A. Gontarek, B. Moench, and L. DeRose, "A data-centric framework for debugging highly parallel applications", Journal of Software: Practice and Experience, Volume 45, issue 4, 501-526, 2014. 
  • M. N. Dinh, D. Abramson, and C. Jin, "Scalable Relative Debugging", IEEE Transactions on Parallel and Distributed Systems, Volume 25, issue 3, 740-749, 2014 
  • M. N. Dinh, C. T. Vo, and D. Abramson, "Tracking scientific simulation using online time-series modelling," in IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, Melbourne, Australia, 2020, pp. 202-211

AI and Machine Learning:

  • T. Phung, M. N. Dinh, D. Dang-Pham, H. M. T. Van, and C. L. Thwaites, "A Machine Learning-based Approach to Vietnamese Handwritten Medical Record Recognition," in Australasian Conference on Information Systems, Wellington, New Zealand, 2020 
  • C. T. Vo, M. N. Dinh, and E. Dimla, "Predicting Phase-field Behavior of Brittle Fracture Model based on LSTM Time Series Forecasting Model," in IEEE International Conference on Research, Innovation and Vision for the Future, Ho Chi Minh City, Vietnam, 2020
  • RMIT Internal Research Grant 2020: In-transit technique for analysing running scientific codes on a Cloud-based HPC system
  • RMIT Thematic Research Fund 2021: Public sentiment in the age of AI and social media: Improving Service Provision Quality in public and private sectors by mining citizens and users’ feedback
  • 2015-2019 - Energy Efficiency Models for Scientific Applications on Supercomputers. Co-supervised a PhD student to investigate how to optimize the energy usage of large-scaled scientific applications running on supercomputing systems.
  • 2016 - An in-situ processing engine for tracking parallel scientific simulations. Supervised a Master of Computer Science student to investigate how data from a scientific simulation can be tracked at runtime to provide in-situ analysis.
  • 2017 - Enabling in-situ visualisation of large-scale scientific simulations. Supervised an Honours student to leverage an existing data-centric tool to extract and pre-process raw simulation data for simulation-time visualisation.
  • 2017 - Runtime verification of large-scale scientific application. Supervised a student from the National University of Singapore (NUS) as part of the Student Internship Program with the School of Information Technology and Electrical Engineering.
  • Doctoral Medal, Award to the PhD candidates who demonstrate research excellence, Monash University, Australia.
  • Postgraduate Publications Award, Monash University, Australia
  • Australian Postgraduate Awards (APA/Industrial) Monash University, Australia
  • Outstanding Scholastic Achievement and Excellence Golden Key International Honour Society, Monash University Chapter, Australia
  • Sir John Monash International Deans Scholar Award, Faculty of Information Technology, Monash University, Australia
  • Redflex Traffic Systems Inc.
  • Leica Microsystems
  • Cray Inc.
  • 2021-Present: RMIT Vietnam Senior Lecturer, Software Engineering
  • 2019-2021: RMIT Vietnam Lecturer, Software Engineering
  • 2017-2019: The University of Queensland Lecturer, School of Information Technology and Electrical Engineering
  • 2014-2019: The University of Queensland Research Fellow, Research Computing Centre (RCC)
  • 2014-2019: Queensland Cyber Infrastructure Foundation (QCIF) eResearch Analyst
  • 2012-2014: Monash University Research Fellow
  • 2008-2012: Monash University Teaching Associate
  • 2007-2009: Monash University Research Assistant
  • 2005-2007: Redflex Traffic Systems Inc. Software Engineer