Biography
Dr Thanh Thi Nguyen has been a leading researcher in Australia in the field of Artificial Intelligence, recognized by The Australian's Research Magazine in a report published in 2018. He has been ranked among the world's top 2% scientists in the single year impact list of 2019, 2020 and 2021 by Elsevier B.V. and Stanford University.
Dr Nguyen was a Visiting Scholar with the Computer Science Department at Stanford University, California, USA in 2015 and the Edge Computing Lab, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Massachusetts, USA in 2019. He received an Alfred Deakin Postdoctoral Research Fellowship in 2016, a European-Pacific Partnership for ICT Expert Exchange Program Award from the European Commission in 2018, and an Australia–India Strategic Research Fund Early- and Mid-Career Fellowship from the Australian Academy of Science in 2020. Dr Nguyen obtained a PhD in Mathematics and Statistics from Monash University, Australia and has expertise in artificial intelligence, deep learning, reinforcement learning, soft computing, data science, big data, econometrics, time series, signal processing, image processing, computer vision, multi-agent systems, and operational research. He has domain knowledge in various areas, including robotics, autonomous vehicles, defence technologies, cybersecurity, IoT, neuroscience, bioinformatics, health informatics, geoinformatics, remote sensing, business statistics, and financial technologies.
Read more on Thanh Thi's profileCareer highlights
6/2019: Visiting Scholar at the Edge Computing Lab, Harvard University, Cambridge, Massachusetts, USA.
12/2018 - present: Senior Lecturer/Senior Research Fellow, School of Information Technology/Institute for Intelligent Systems Research and Innovation, Deakin University, Australia.
10/2018: Visiting Scholar at Centre for Engagement and Simulation Science, Department of Surgery and Cancer, Imperial College London, UK.
9/2018: Guest Scientist at Robotics Innovation Center, German Research Center for Artificial Intelligence (DFKI GmbH), Bremen, Germany.
7/2015 - 10/2015: Visiting Scholar at the Computer Science Department, Stanford University, California, USA.
12/2012 - 12/2018: Lecturer/Research Fellow, Institute for Intelligent Systems Research and Innovation, Deakin University, Australia.
3/2011 - 11/2012: Teaching Associate, Department of Econometrics & Business Statistics, and Clayton School of Information Technology, Monash University, Australia.
2010 - 2013: PhD Candidate, Department of Econometrics & Business Statistics, Monash University, Clayton, Victoria, Australia.
Research interests
- Artificial Intelligence, Deep Learning, Signal & Image Processing, Computer Vision, Big Data
- Data Science, Natual Language Processing, Health Informatics, Cybersecurity, IoT, Human-Machine Interaction
- Deep Reinforcement Learning, Robotics, Autonomous Machines, Multi-Agent Systems, Defence Technologies
Units taught
Master's Degree:
- SIT706 - Cloud Computing
- SIT717 - Enterprise Business Intelligence
- SIT718 - Real World Analytics
- SIT720 - Machine Learning
- SIT723 - Research Training and Project
- SIT724 - Research Project
- SIT740 - Research and Development in Information Technology
- SIT796 - Reinforcement Learning
Bachelor's Degree:
- SIT113/233 - Cloud Computing
Professional activities
- Program Committee Member of the 20th Pacific Rim Int. Conf. on AI (PRICAI), Nov 2023.
- Program Chair of the 2023 EAI Int. Conf. on AI for CyberSecurity (AICSEC), Oct 2023.
- Program Committee Member of the 32nd Int. Joint Conf. on AI (IJCAI), Aug 2023.
- Editorial Board Member of Artificial Intelligence Advances, Feb 2023.
- Publicity & Social Media Committee of the 16th Int. Conf. on Advanced Computing and Analytics (ACOMPA), Nov 2022.
- Guest Editor of Special Issue "Advances in Artificial Intelligence for Cyber Security", Sensors Journal, Jun 2022.
- Keynote speaker, "Applications of AI in the Battle against COVID-19" at 15th Int. Conf. on Advanced Computing and Applications (ACOMP), Nov 2021.
- Keynote speaker, "Research Directions in AI for Fighting the COVID-19 Pandemic" at Deakin School of IT HDR Annual Conference, Nov 2021.
- Invited talk at International Webinar "AI: Opportunities and Challenges" at Center for AI and Technology, National University of Malaysia, Oct 2021.
- Organising Committee Member of 2021 IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC).
- Invited talk at Monash Faculty of IT, "Human strategies to coordinate multiple deep RL agents", Mar 2021.
- Guest Editor of Special Issue "Deep RL: Methods and Applications", Electronics Journal, Oct 2020.
- Invited talk at Ericsson Company, Chennai, India, "Deep RL and Its Applications", Jul 2020.
- Presenter of the Tutorial "Advances in Deep RL", 2020 IEEE World Congress on Computational Intelligence (WCCI).
- Organizer of Special Session "Methods and Applications of Deep RL to Autonomous Systems", 2020 IEEE Int. Joint Conf. on Neural Networks (IJCNN).
- Invited tutorial, IIT-Kanpur, "Implementing deep RL with OpenAI Gym", Mar 2020.
- Invited talk, IIT-Roorkee, "Multi-objective deep RL", Mar 2020.
- Invited talk, IIT-Madras, "Recent advances in deep RL", Feb 2020.
- Co-Chair of AI & Big Data Analytics Track at the 9th and 10th International Symposium on Information and Communication Technology, Dec 2018 and 2019.
- Invited talk at Robotics Innovation Center, German Research Center for AI (DFKI GmbH), Bremen, Germany, "Deep Reinforcement Learning for Human-Level Agents", Sep 2018.
- TPC Member of IEEE Int. Conf. on SMC, 2016, 2017, 2019.
- Invited talk at IEEE Victorian Chapter Workshop on "Advanced Machine Learning for Big Data Analytics", Dec 2015.
Media appearances
Scipothesis: Uncover how discoveries in the lab could shape our lives in the future, "Episode 01: Deepfakes".
The Wired UK Magazine, "In the battle against deepfakes, AI is being pitted against AI".
The Australian Newspaper, "Engineering & Computer Science: Australia’s Research Field Leaders".
The Australian Academy of Science, "Australia–India Strategic Research Fund Early- and Mid-Career Fellowships 2020".
Deakin University, "Careers in AI: inspiring jobs in artificial intelligence".
Awards
- Deakin University Vice-Chancellor's 10 Years Service Milestone Award, December 2022.
- Best Paper Award at the 2022 International Conference on Artificial Intelligence, Security and Communication (AISC) (2022)
- Australia–India Strategic Research Fund Early- and Mid-Career Fellowship Awarded by the Australian Academy of Science (2020)
- One of the Most Popular Articles in the IEEE Transactions on Cybernetics since September 2020
- One of the Best Deep Reinforcement Learning Research Papers of 2019 by the Open Data Science Conference (ODSC)
- European-Pacific Partnership for ICT (EPIC) Expert Exchange Program Award by the European Commission (2018)
- ON Prime Award by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) (2017)
- Alfred Deakin Postdoctoral Research Fellowship Awarded by Deakin University (2016 - 2017)
- Monash Graduate Research (MGR) PhD Scholarship Awarded by Monash University (2010 - 2013)
- Business and Economics Faculty Postgraduate Research Scholarship (FPRS) Awarded by Monash University (2010 - 2013)
Publications
Artificial intelligence for the metaverse: A survey
Thien Huynh-The, Quoc-Viet Pham, Xuan-Qui Pham, Thanh Nguyen, Zhu Han, Dong-Seong Kim
(2023), Vol. 117, pp. 1-22, Engineering Applications of Artificial Intelligence, Amsterdam, The Netherlands, C1
L Nguyen, N Pham, V Do, L Nguyen, T Nguyen, H Nguyen, Ngoc Nguyen, Thanh Nguyen, S Nguyen, Asim Bhatti, Chee Lim
(2023), Vol. 213, Part C, pp. 1-12, Expert Systems with Applications, Amsterdam, The Netherlands, C1
Example-based explanations for streaming fraud detection on graphs
T Nguyen, T Phan, H Pham, T Nguyen, J Jo, Q Nguyen
(2023), Vol. 621, pp. 319-340, Information Sciences, Amsterdam, The Netherlands, C1
Meta-transfer learning for emotion recognition
D Nguyen, D Nguyen, S Sridharan, S Denman, T Nguyen, D Dean, C Fookes
(2023), Neural Computing and Applications, C1
Validating functional redundancy with mixed generative adversarial networks
T Nguyen, T Huynh, M Pham, T Hoang, T Nguyen, Q Nguyen
(2023), Vol. 264, pp. 110342-110342, Knowledge-Based Systems, C1
Training Spiking Neural Networks with Metaheuristic Algorithms
A Javanshir, T Nguyen, M Mahmud, A Kouzani
(2023), Vol. 13, Applied Sciences (Switzerland), C1
Deep auto-encoders with sequential learning for multimodal dimensional emotion recognition
D Nguyen, D Nguyen, R Zeng, T Nguyen, S Tran, T Nguyen, S Sridharan, C Fookes
(2022), pp. 1-10, IEEE transactions on multimedia, Piscataway, N.J., C1
S Lu, G Christie, T Nguyen, J Freeman, E Hsu
(2022), Vol. 16, Disaster Medicine and Public Health Preparedness, United States, C1
Epileptic seizure detection in EEG using mutual information-based best individual feature selection
Kazi Hassan, Md Islam, Thanh Nguyen, Md Molla
(2022), Vol. 193, pp. 1-11, Expert Systems with Applications, Amsterdam, The Netherlands, C1
S Ramu, P Boopalan, Q Pham, P Maddikunta, T Huynh-The, M Alazab, T Nguyen, T Gadekallu
(2022), Vol. 79, pp. 1-13, Sustainable Cities and Society, Amsterdam, The Netherlands, C1
RanNet: Learning Residual-Attention Structure in CNNs for Automatic Modulation Classification
Thien Huynh-The, Quoc-Viet Pham, Toan-Van Nguyen, Thanh Nguyen, Daniel da Costa, Dong-Seong Kim
(2022), Vol. 11, pp. 1-5, IEEE Wireless Communications Letters, Piscataway, N.J., C1
Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks
A Javanshir, T Nguyen, M Mahmud, A Kouzani
(2022), Vol. 34, pp. 1289-1328, Neural Computation, Cambridge, Mass., C1
Thanh Nguyen, Mohamed Abdelrazek, Dung Nguyen, Sunil Aryal, Duc Nguyen, Sandeep Reddy, Quoc Nguyen, Amin Khatami, Thanh Nguyen, Edbert Hsu, Samuel Yang
(2022), Vol. 8, pp. 1-12, Machine Learning with Applications, Amsterdam, The Netherlands, C1
Towards designing a generic and comprehensive deep reinforcement learning framework
N Nguyen, T Nguyen, N Pham, H Nguyen, D Nguyen, T Nguyen, C Lim, M Johnstone, A Bhatti, D Creighton, S Nahavandi
(2022), pp. 1-22, Applied Intelligence, Berlin, Germany, C1
Detecting rumours with latency guarantees using massive streaming data
T Nguyen, T Huynh, H Yin, M Weidlich, T Nguyen, T Mai, Q Nguyen
(2022), pp. 1-19, VLDB Journal, Berlin, Germany, C1
Deep learning for deepfakes creation and detection: A survey
T Nguyen, Q Nguyen, D Nguyen, D Nguyen, T Huynh-The, S Nahavandi, T Nguyen, Q Pham, C Nguyen
(2022), Vol. 223, pp. 103525-103525, Computer Vision and Image Understanding, C1
3D-IncNet: Head and Neck (H&N) Primary Tumors Segmentation and Survival Prediction
Abdul Qayyum, Abdesslam Benzinou, Imran Razzak, Moona Mazher, Thanh Nguyen, Domenec Puig, Fatemeh Vafaee
(2022), pp. 1-9, IEEE Journal of Biomedical and Health Informatics, C1
A Hybrid Supervised Approach to Human Population Identification Using Genomics Data
S Araghi, T Nguyen
(2021), Vol. 18, pp. 443-454, IEEE/ACM Transactions on Computational Biology and Bioinformatics, United States, C1
T Nguyen, P Pathirana, T Nguyen, Q Nguyen, A Bhatti, D Nguyen, D Nguyen, N Nguyen, D Creighton, M Abdelrazek
(2021), Vol. 11, pp. 3487-, Scientific reports, England, C1
A Prioritized objective actor-critic method for deep reinforcement learning
N Nguyen, T Nguyen, P Vamplew, R Dazeley, S Nahavandi
(2021), Vol. 33, pp. 10335-10349, Neural Computing and Applications, C1
O Tarkhaneh, T Nguyen, S Mazaheri
(2021), Vol. 565, pp. 278-305, Information Sciences, C1
JUDO: Just-in-time rumour detection in streaming social platforms
T Nguyen, T Nguyen, T Nguyen, B Vo, J Jo, Q Nguyen
(2021), Vol. 570, pp. 70-93, Information sciences, Amsterdam, The Netherlands, C1
Automatic Modulation Classification: A Deep Architecture Survey
T Huynh-The, Q Pham, T Nguyen, T Nguyen, R Ruby, M Zeng, D Kim
(2021), Vol. 9, pp. 142950-142971, IEEE Access, C1
Deep Reinforcement Learning for Cyber Security
T Nguyen, V Reddi
(2021), Vol. PP, IEEE Transactions on Neural Networks and Learning Systems, United States, C1
A multi-objective deep reinforcement learning framework
Thanh Nguyen, Ngoc Nguyen, Peter Vamplew, Saeid Nahavandi, Richard Dazeley, Chee Lim
(2020), Vol. 96, pp. 1-12, Engineering Applications of Artificial Intelligence, Amsterdam, The Netherlands, C1
T Nguyen, N Nguyen, S Nahavandi
(2020), Vol. 50, pp. 3826-3839, IEEE transactions on cybernetics, Piscataway, N.J., C1
Evaluation of classification techniques for identifying cognitive load levels using EEG signals
Syed Salaken, Imali Hettiarachchi, Luke Crameri, Samer Hanoun, Saeid Nahavandi, Thanh Nguyen
(2020), SYSCON2020 : Proceedings of the 14th Annual IEEE International Systems Conference, Virtual Conference, E1
Convolutional neural network for medical image classification using wavelet features
Amin Khatami, Asef Nazari, Amin Beheshti, Thanh Nguyen, Saeid Nahavandi, Jerzy Zieba
(2020), pp. 1-8, IJCNN 2020 : Proceedings of the 2020 International Joint Conference on Neural Networks, Online from Glasgow, Scotland, E1
A Review of Situation Awareness Assessment Approaches in Aviation Environments
T Nguyen, C Lim, N Nguyen, L Gordon-Brown, S Nahavandi
(2019), Vol. 13, pp. 3590-3603, IEEE Systems Journal, C1
Seeded transfer learning for regression problems with deep learning
S Salaken, A Khosravi, T Nguyen, S Nahavandi
(2019), Vol. 115, pp. 565-577, Expert Systems with Applications, C1
Multi-agent behavioral control system using deep reinforcement learning
N Nguyen, T Nguyen, S Nahavandi
(2019), Vol. 359, pp. 58-68, Neurocomputing, C1
Multi-agent Deep Reinforcement Learning with Human Strategies
T Nguyen, N Nguyen, S Nahavandi
(2019), pp. 1357-1362, ICIT 2019 : Proceedings of the IEEE Industrial Technology 2019 Conference, Melbourne, Vic., E1
A new tensioning method using deep reinforcement learning for surgical pattern cutting
T Nguyen, N Nguyen, F Bello, S Nahavandi
(2019), Vol. 2019-February, pp. 1339-1344, ICIT 2019 : IEEE International Conference on Industrial Technology, Melbourne, Victoria, E1
Manipulating soft tissues by deep reinforcement learning for autonomous robotic surgery
N Nguyen, T Nguyen, S Nahavandi, A Bhatti, G Guest
(2019), pp. 1-7, SysCon 2019 : Proceedings of the 2019 IEEE International Systems Conference, Orlando, Florida, E1
A GA-based pruning fully connected network for tuned connections in deep networks
A Khatami, P Kebria, S Jalali, A Khosravi, A Nazari, M Shamszadeh, T Nguyen, S Nahavandi
(2019), pp. 3492-3497, IEEE SMC 2019 : Proceedings of the 2019 IEEE International Conference on Systems, Man, and Cybernetics, Bari, Italy, E1
A Khatami, M Babaie, H Tizhoosh, A Khosravi, T Nguyen, S Nahavandi
(2018), Vol. 100, pp. 224-233, Expert Systems with Applications, C1-1
A review on cluster estimation methods and their application to neural spike data
J Zhang, T Nguyen, S Cogill, A Bhatti, L Luo, S Yang, S Nahavandi
(2018), Vol. 15, Journal of Neural Engineering, England, C1-1
A fresh look at functional link neural network for motor imagery-based brain-computer interface
I Hettiarachchi, T Babaei, T Nguyen, C Lim, S Nahavandi
(2018), Vol. 305, pp. 28-35, Journal of Neuroscience Methods, Netherlands, C1-1
Classification of Multi-Class BCI Data by Common Spatial Pattern and Fuzzy System
T Nguyen, I Hettiarachchi, A Khatami, L Gordon-Brown, C Lim, S Nahavandi
(2018), Vol. 6, pp. 27873-27884, IEEE Access, C1-1
A soft computing fusion for river flow time series forecasting
T Nguyen, N Nguyen, S Nahavandi, S Salaken, A Khatami
(2018), pp. 1-7, FUZZ-IEEE 2018 : IEEE International Conference on Fuzzy Systems, Rio de Janeiro, Brazil, E1-1
S Salaken, A Khosravi, T Nguyen, S Nahavandi
(2018), pp. 906-911, SMC 2018 : Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics, Miyazaki, Japan, E1
A human mixed strategy approach to deep reinforcement learning
N Nguyen, S Nahavandi, T Nguyen
(2018), pp. 4023-4028, SMC 2018 : The making of a human-centered cyber world : Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics, Miyazaki, Japan, E1
Medical image analysis using wavelet transform and deep belief networks
A Khatami, A Khosravi, T Nguyen, C Lim, S Nahavandi
(2017), Vol. 86, pp. 190-198, Expert Systems with Applications, C1-1
Extreme learning machine based transfer learning algorithms: A survey
S Salaken, A Khosravi, T Nguyen, S Nahavandi
(2017), Vol. 267, pp. 516-524, Neurocomputing, C1-1
Output uncertainty score for decision making processes using interval type-2 fuzzy systems
S Salaken, A Khosravi, T Nguyen, S Nahavandi
(2017), Vol. 65, pp. 159-167, Engineering Applications of Artificial Intelligence, C1-1
System Design Perspective for Human-Level Agents Using Deep Reinforcement Learning: A Survey
N Nguyen, T Nguyen, S Nahavandi
(2017), Vol. 5, pp. 27091-27102, IEEE Access, C1-1
Modelling RNA-seq read counts by grey relational analysis
T Nguyen, S Nahavandi
(2017), pp. 4293-4298, SMC 2016 : Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, Budapest, Hungary, E1-1
Multiclass EEG data classification using fuzzy systems
T Nguyen, I Hettiarachchi, A Khosravi, S Salaken, A Bhatti, S Nahavandi
(2017), pp. 1-6, FUZZ-IEEE 2017 : Proceedings of the IEEE International Conference on Fuzzy Systems, Naples, Italy, E1-1
Portfolio selection under higher moments using fuzzy multi-objective linear programming
T Nguyen
(2016), Vol. 30, pp. 2139-2156, Journal of Intelligent and Fuzzy Systems, C1
Modified AHP for Gene Selection and Cancer Classification Using Type-2 Fuzzy Logic
T Nguyen, S Nahavandi
(2016), Vol. 24, pp. 273-287, IEEE Transactions on Fuzzy Systems, C1
Unified selective sorting approach to analyse multi-electrode extracellular data
R Veerabhadrappa, C Lim, T Nguyen, M Berk, S Tye, P Monaghan, S Nahavandi, A Bhatti
(2016), Vol. 6, Scientific Reports, England, C1
RNA-seq count data modelling by grey relational analysis and nonparametric Gaussian process
T Nguyen, A Bhatti, S Yang, S Nahavandi
(2016), Vol. 11, PLoS ONE, United States, C1
RNA-seq data analysis using nonparametric Gaussian process models
T Nguyen, S Nahavandi, D Creighton, A Khosravi
(2016), pp. 5087-5093, IJCNN 2016 : Proceedings of the International Joint Conference on Neural Networks, Vancouver, Canada, E1-1
Classification of healthcare data using genetic fuzzy logic system and wavelets
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 42, pp. 2184-2197, Expert systems with applications, Amsterdam, The Netherlands, C1
EEG data classification using wavelet features selected by Wilcoxon statistics
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 26, pp. 1193-1202, Neural computing and applications, Berlin, Germany, C1
EEG signal classification for BCI applications by wavelets and interval type-2 fuzzy logic systems
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 42, pp. 4370-4380, Expert systems with applications, Amsterdam, The Netherlands, C1
Fuzzy portfolio allocation models through a new risk measure and fuzzy sharpe ratio
T Nguyen, L Gordon-Brown, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 23, pp. 656-676, IEEE transactions on fuzzy systems, Piscataway, N.J., C1
Medical data classification using interval type-2 fuzzy logic system and wavelets
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 30, pp. 812-822, Applied soft computing, Amsterdam, The Netherlands, C1
Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 10, pp. 1-23, PLoS one, San Francisco, Calif., C1
Automatic spike sorting by unsupervised clustering with diffusion maps and silhouettes
T Nguyen, A Bhatti, A Khosravi, S Haggag, D Creighton, S Nahavandi
(2015), Vol. 153, pp. 199-210, Neurocomputing, Amsterdam, The Netherlands, C1
A novel aggregate gene selection method for microarray data classification
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 60-61, pp. 16-23, Pattern recognition letters, Amsterdam, The Netherlands, C1
Fuzzy system with tabu search learning for classification of motor imagery data
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 20, pp. 61-70, Biomedical signal processing and control, C1
Hidden Markov models for cancer classification using gene expression profiles
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 316, pp. 293-307, Information sciences, Amsterdam, The Netherlands, C1
Optimal ground control points for geometric correction using genetic algorithm with global accuracy
T Nguyen
(2015), Vol. 48, pp. 101-120, European Journal of Remote Sensing, [Cagiari, Italy], C1
Multi-output interval type-2 fuzzy logic system for protein secondary structure prediction
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2015), Vol. 23, pp. 735-760, International journal of uncertainty, fuzziness and knowlege-based systems, Singapore, C1
Mass spectrometry cancer data classification using wavelets and genetic algorithm
T Nguyen, S Nahavandi, D Creighton, A Khosravi
(2015), Vol. 589, pp. 3879-3886, FEBS letters, Amsterdam, The Netherlands, C1
EEG signal analysis for BCI application using fuzzy system
T Nguyen, S Nahavandi, A Khosravi, D Creighton, I Hettiarachchi
(2015), Vol. 2015-September, pp. 1-8, IJCNN 2015: Proceedings of the 2015 International Joint Conference on Neural Networks, Killarney, Ireland, E1
Statistical modelling of artificial neural network for sorting temporally synchronous spikes
R Veerabhadrappa, A Bhatti, C Lim, T Nguyen, S Tye, P Monaghan, S Nahavandi
(2015), Vol. 9491, pp. 261-272, 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings Part III, Istanbul, Turkey, E1
Multivariate adaptive autoregressive modeling and kalman filtering for motor imagery BCI
I Hettiarachchi, T Nguyen, S Nahavandi
(2015), pp. 3164-3168, SMC 2015 : Big Data Analytics for Human-Centric Systems. Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics, Hong Kong, China, E1
Mass spectrometry-based proteomic data for cancer diagnosis using interval type-2 fuzzy system
T Nguyen, S Nahavandi, A Khosravi, D Creighton
(2015), pp. 1-8, UZZ-IEEE 2015: Proceedings of the IEEE International Conference on Fuzzy Systems, Istanbul, Turkey, E1
Motor Imagery Data Classification for BCI Application Using Wavelet Packet Feature Extraction
I Hettiarachchi, T Nguyen, S Nahavandi
(2014), Vol. 8836, pp. 519-526, Lecture Notes in Computer Science, Kuching, Malaysia, B1
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2014), Vol. 238, pp. 43-53, Journal of neuroscience methods, Amsterdam, Netherlands, C1
From ranking fuzzy numbers to solving fuzzy linear programming: a comprehensive review
T Nguyen
(2014), Vol. 5, pp. 219-235, International journal of computing science and mathematics, Olney, Eng., C1
Selection of the right risk measures for portfolio allocation
Thanh Nguyen
(2014), Vol. 7, pp. 135-156, International journal of monetary economics and finance, Olney, England, C1
Neural signal analysis by landmark-based spectral clustering with estimated number of clusters
T Nguyen, A Khosravi, A Bhatti, D Creighton, S Nahavandi
(2014), pp. 4042-4049, IJCNN 2014 : Proceedings of the 2014 International Joint Conference on Neural Networks, Beijing, China, E1
Medical diagnosis by fuzzy standard additive model with wavelets
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2014), pp. 1937-1944, FUZZ-IEEE 2014 : Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, Beijing, China, E1
Structural classification of proteins through amino acid sequence using interval type-2 fuzzy logic system
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2014), pp. 1123-1130, Proceedings of the 2014 IEEE International Conference on Fuzzy Systems: FUZZ-IEEE 2014, Beijing, China, E1
Classification of neural action potentials using mean shift clustering
T Nguyen, A Khosravi, I Hettiarachchi, D Creighton, S Nahavandi
(2014), pp. 1247-1252, SMC 2014 : Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, California, E1
Solving fuzzy programming with a consistent fuzzy number ranking
T Nguyen, V Lee, A Khosravi, D Creighton, S Nahavandi
(2014), pp. 551-556, SMC 2014 : Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, California, E1
Multivariate Adaptive Autoregressive Modeling and Kalman Filtering for Motor Imagery BCI
Imali Hettiarachchi, Thi Thanh, Saeid Nahavandi
(2014), pp. 3164-3168, 2014 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2014), Austin, TX, E1-1
Epidemiological dynamics modeling by fusion of soft computing techniques
T Nguyen, A Khosravi, D Creighton, S Nahavandi
(2013), IJCNN 2013 : Proceedings of the IEEE Neural Networks 2013 International Joint Conference, Dallas, Texas, E1
Neural network and interval type-2 fuzzy system for stock price forecasting
T Nguyen, A Khosravi, S Nahavandi, D Creighton
(2013), pp. 1-8, FUZZ-IEEE 2013 : Proceedings of the IEEE International Conference on Fuzzy Systems, Hyderabad, India, E1
Constrained fuzzy hierarchical analysis for portfolio selection under higher moments
T Nguyen, L Gordon-Brown
(2012), Vol. 20, pp. 666-682, IEEE transactions on fuzzy systems, Piscataway, N.J., C1-1
Financial time series prediction in cooperating with event knowledge: a fuzzy approach
D Sang, D Woo, D Park, T Nguyen
(2010), pp. 406-417, MICAI 2010 : Proceedings of the Artificial Intelligence 2010 Mexican International Conference, Pachuca, Mexico, E1-1
Standard additive fuzzy system for stock price forecasting
D Sang, D Woo, D Park, T Nguyen
(2010), pp. 279-288, ACIIDS 2010 : Proceedings of Intelligent Information and Database Systems 2010 Asian Conference, Hue City, Vietnam, E1-1
Smoothing supervised learning of neural networks for function approximation
T Nguyen
(2010), pp. 104-109, KSE 2010 : Proceedings of the Knowledge and Systems Engineering 2010 international conference, Hanoi, Vietnam, E1-1
Morphological change at the Snowy River ocean entrance, Victoria, Australia (1851-2008)
P Wheeler, T Nguyen, J Peterson, L Gordon-Brown
(2009), Vol. 40, pp. 1-28, Australian geographer, Abingdon, England, C1-1
Indexing postGIS databases and spatial query performance evaluations
T Nguyen
(2009), Vol. 5, pp. 1-9, International journal of geoinformatics, Pathumthani, Thailand, C1-1
GA-SVM based framework for time series forecasting
T Nguyen, L Gordon-Brown, P Wheeler, J Peterson
(2009), pp. 493-498, ICNC 2009 : Proceedings of the Natural Computation 2009 International Conference, Tianjin, China, E1-1
T Nguyen, L Gordon-Brown, J Peterson
(2008), pp. 1211-1216, CIMCA 2008 : Proceedings of the Computational Intelligence for Modelling, Control and Automation 2008 international conference, Vienna, Austria, E1-1
Enhancing the performance of the fuzzy system approach to prediction
T Nguyen, J Peterson
(2008), pp. 259-265, FSKD 2008 : Proceedings of the Fuzzy Systems and Knowledge Discovery 2008 international conference, Jinan, China, E1-1
Funded Projects at Deakin
Other Public Sector Funding
Critical Review and Forecast - Modelling and Simulation of Dynamic Military Environments Using Machine Learning with Autonomy, Trust and Uncertainty
Prof Saeid Nahavandi, Prof Chee Peng Lim, Dr Lei Wei, Dr Thanh Thi Nguyen, Dr Hailing Zhou
DSTO Grant - Research - Defence Science & Technology Organisation
- 2016: $131,159
Analysis of factors influencing electrical network-related incidents.
Dr Thanh Thi Nguyen
Energy Safe Victoria
- 2021: $10,328
- 2020: $10,000
Utilise Human Expertise to Extend the Capabilities of Reinforcement Learning.
Dr Thanh Thi Nguyen, A/Prof Mohamed Abdelrazek
DSTO contract
- 2021: $5,000
- 2020: $15,000
Holonic-based deep reinforcement learning for multi-agent systems.
Dr Thanh Thi Nguyen, A/Prof Mohamed Abdelrazek
Department of Defence
- 2022: $30,000
Sim to Real Transfer in Deep Reinforcement Learning for Real-World Robots.
Dr Thanh Thi Nguyen, A/Prof Mohamed Abdelrazek, Mr David Azimi
Department of Jobs, Precincts & Regions
- 2022: $15,000
Predicting ground fire incidents using AI and statistical methods.
Dr Thanh Thi Nguyen, Dr Jonathan Kua, Dr Anuroop Gaddam
Energy Safe Victoria
- 2022: $10,425
Industry and Other Funding
Improving Decision Making In Self-adaptive Systems Using Reinforcement Learning.
A/Prof Mohamed Abdelrazek, Dr Thanh Thi Nguyen
Fujitsu Laboratories Ltd
- 2020: $122,886
Other Funding Sources
R3.1.4 Intelligent data fusion and analytics framework for decision support in predictive maintenace services.
Prof Douglas Creighton, Prof Chee Peng Lim, Dr Vu Le, Dr James Zhang, A/Prof Michael Johnstone, Dr Thanh Thi Nguyen
Rail Manufacturing CRC Ltd
- 2020: $558,480
- 2019: $595,318
Augmenting Cyber Defence Capability (ACDC).
Prof Gang Li, Mr Luxing Yang, Dr Nayyar Zaidi, Dr Ye Zhu, Prof Rajesh Vasa, Prof Kon Mouzakis, Prof Robin Ram Mohan Doss, Dr Thanh Thi Nguyen
Cyber Security Research Centre Limited
- 2023: $78,000
- 2022: $39,000
Supervisions
Ngoc Duy Nguyen
Thesis entitled: A Deep Reinforcement Learning Framework for Human-Level Agents.
Doctor of Philosophy (Engineering), Institute for Intelligent Systems Research and Innovation
Roohallah Alizadehsani
Thesis entitled: Uncertainty-Aware Model Training and Decision Making
Doctor of Philosophy (Engineering), Institute for Intelligent Systems Research and Innovation
AmirHossein Javanshir
Thesis entitled: A Multi-Objective Spiking Neural Network
Doctor of Philosophy (Engineering), School of Engineering
Afsaneh Koohestani
Thesis entitled: Towards Identifying Driver Performance Degradation using Physiological Signals
Doctor of Philosophy (Engineering), Institute for Intelligent Systems Research and Innovation
Syed Moshfeq Salaken
Thesis entitled: Solving Computational Bottleneck of Interval Type-2 Fuzzy Systems
Doctor of Philosophy (Engineering), Institute for Intelligent Systems Research and Innovation