Selected Publication

^ : corresponding author

** : directly supervised research staffs (Postdoc, Research Associate, etc.)

* : directly supervised students 

Journals

1. W Ding^, M Abdel-Basset, H Hawash, M Pratama, W Pedrycz, Generalizable Segmentation of COVID-19 Infection From Multi-Site Tomography Scans: A Federated Learning Framework, IEEE Transactions on Emerging Topics in Computational Intelligence, 2023

2. E. Lughofer^, M. Pratama, Evolving multi-user fuzzy classifier system with advanced explainability and interpretability aspects, Information Fusion, 2022 - IF: 17.56 

3. M. De Carvalho*, M. Pratama^, J. Zhang, E. Yapp Kien-Yee, ACDC: Online Unsupervised Cross-Domain Adaptation, Knowledge-based Systems, 2022 - IF: 8.139 (Codes: https://github.com/Ivsucram/ACDC)

4. *W. Weng, M. Pratama^, C. Za'in*, M. De Carvalho*, R. Appan*, A. Ashfahani*, E. Yapp Kien-Yee, Autonomous Cross Domain Adaptation under Extreme Label Scarcity, IEEE Transactions on Neural Networks and Learning Systems, 2022 - IF: 14.255 (Codes: https://github.com/wengweng001/LEOPARD.git )

5. *Abhay M S Aradhya, *Andri Ashfahani, *Fienny Angelina, M. Pratama^, R. F. de Mello, S. Sundaram, Autonomous CNN (AutoCNN): A Data-Driven Approach to Network Architecture Determination, Information Sciences, 2022 - IF: 8.233 (Codes: https://tinyurl.com/AutoCNN)

6. *A. Ashfahani, M. Pratama, Unsupervised Continual Learning in Streaming Environments, IEEE Transactions on Neural Networks and Learning Systems, 2022 - IF: 14.255 (Codes: https://github.com/andriash001/AutonomousDCN.git)

7. M. Pratama^, E. Lughofer, P. Angelov, Editorial: Special Issue on Recent Progress in Autonomous Machine Learning, Information Sciences, 2022 - IF: 8.233

8. R. Xie**, M. Pratama^, Automatic Online Multi-Source Domain Adaptation, Information Sciences, 2021 - IF: 8.233 (Codes: https://github.com/Renchunzi-Xie/AOMSDA.git)

9. M. Pratama^, C. Za’in*, E. Lughofer, E. Pardede, D. Rahayu, Scalable teacher forcing network for semi-supervised large scale data streams, Information Sciences, pp. 407-431, 2021 - IF: 8.233 (Codes: https://doi.org/10.21979/N9/CX0PDV)

10. F. Mao**, W. Weng**, M. Pratama^, E. Yapp Kien-Yee, Continual learning via inter-task synaptic mapping, Knowledge-based Systems, Vol. 222, 2021 - IF: 8.139 (Codes: https://doi.org/10.21979/N9/JVCTU3)

11. S. Subharjit**, M. Pratama, S. Suresh, Bayesian Neuro-Fuzzy Inference System (BaNFIS) for Temporal Dependency Estimation, IEEE Transactions on Fuzzy Systems, 2020 - IF: 12.25

12. M Pratama^, E Dimla, T Tjahjowidodo, W Pedrycz, E Lughofer, Online tool condition monitoring based on parsimonious ensemble+, IEEE transactions on cybernetics 50 (2), 664-677, 2020 - IF: 19.11 (Codes: https://doi.org/10.21979/N9/GGBFMO)

13. MM Ferdaus*, M Pratama^, SG Anavatti, MA Garratt, E Lughofer, PAC: A novel self-adaptive neuro-fuzzy controller for micro aerial vehicles, Information Sciences 512, 481-505, 2020 - IF: 8.233

14. Q Cai**, S Alam, M Pratama, J Liu, Robustness Evaluation of Multipartite Complex Networks Based on Percolation Theory, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020 - IF: 11.471

15. M. Das**, M. Pratama, S. K. Gosh, SARDINE: A Self-Adaptive Recurrent Deep Incremental Network Model for Spatio-Temporal Prediction of Remote Sensing Data, ACM Trans. Spatial Algorithms Syst. 6(3): 16:1-16:26 (2020)

16. S Samanta*, M Pratama^, S Sundaram, A novel spatio-temporal fuzzy inference system (spatfis) and its stability analysis, Information Sciences 505, 84-99, 2019 - IF: 8.233 

17. S Samanta*, M Pratama^, S Sundaram, N Srikanth, Learning elastic memory online for fast time series forecasting, Neurocomputing, Vol. 390, pp. 315-326, 2020 - IF: 5.779

18. A Ashfahani*, M Pratama^, E Lughofer, YS Ong, DEVDAN: Deep evolving denoising autoencoder, Neurocomputing, Vol. 390, pp. 297-314, 2020 - IF: 5.779 (Python Codes: https://doi.org/10.21979/N9/5QAWOV, Matlab Codes: https://doi.org/10.21979/N9/KPULXP)

19. M Pratama^, W Pedrycz, GI Webb, An incremental construction of deep neuro fuzzy system for continual learning of non-stationary data streams, IEEE Transactions on Fuzzy Systems, Vol. 28(7), pp. 1315-1328, 2020 - IF: 12.25 (Codes: https://doi.org/10.21979/N9/LVFNVG)

20. M Pratama^, D Wang, Deep stacked stochastic configuration networks for lifelong learning of non-stationary data streams, Information Sciences 495, 150-174, 2019 - IF: 8.233 (Codes: https://doi.org/10.21979/N9/4KTA08)

21. MM Ferdaus*, M Pratama^, S Anavatti, MA Garratt, Y Pan, Generic evolving self-organizing neuro-fuzzy control of bio-inspired unmanned aerial vehicles, IEEE Transactions on Fuzzy Systems, Vol.28(8), pp. 1542-1556, 2020 - IF: 12.25 (Codes: https://tinyurl.com/dfuefxc2)

22. MM Ferdaus*, M Pratama^, SG Anavatti, MA Garratt, PALM: An incremental construction of hyperplanes for data stream regression, IEEE Transactions on Fuzzy Systems 27 (11), 2115-2129, 2019  - IF: 12.25 (Codes: https://doi.org/10.21979/N9/CZJLQ5)

23. M. Pratama^, W. Pedrycz, E. Lughofer, Evolving Ensemble Fuzzy Classifier, IEEE Transactions on Fuzzy Systems, 26 (5), 2552-2567, 2018 - IF: 12.25 (Codes: https://doi.org/10.21979/N9/9QM7H6) 

24. M. Pratama^, E. Lughofer, P. Angelov, M-J.Er, Parsimonious Random Vector Functional Link Network for Data Streams, Information Sciences, Vol. 430, pp. 519-537, 2018 - IF: 8.233 (Codes: https://doi.org/10.21979/N9/FVZOI9)

25. E.Lughofer, M. Pratama, On-line Active Learning in Data Stream Regression employing Evolving Generalized Fuzzy Models with Certainty Sampling, IEEE Transactions on Fuzzy Systems, Vol. 26(1), pp. 262-309, 2018 - IF: 12.25

26. M. Pratama^, J. Lu, G. Zhang, Evolving Type-2 Fuzzy Classifier. IEEE Trans. Fuzzy Syst. 24(3): 574-589 (2016) - IF: 12.25

27. M. Pratama^, S. Anavatti, E. Lughofer, GENEFIS: Toward an Effective Localist Network. IEEE Trans. Fuzzy Syst. 22(3): 547-562 (2014) - IF: 12.25

28. M. Pratama^, S. Anavatti, P. Angelov, E. Lughofer, PANFIS: A Novel Incremental Learning Machine. IEEE Trans. Neural Networks Learn. Syst. 25(1): 55-68 (2014) - IF: 14.255  

Conferences

1. A. Rakaraddi*, S-K. Lam, M. Pratama, M. De Carvalho*,  Reinforced Continual Learning for Graphs, CIKM 2022 - Core A (Codes: https://github.com/codexhammer/gcl)

2. T. Dam*, MD. M. Ferdaus*, M. Pratama, S. Anavatti, S. Jayavelu, H. Abbass,  Latent Preserving Generative Adversarial Network for Imbalance classification, ICIP 2022 - Core B (Codes: https://github.com/TanmDL/SLPPL-GAN)

3. T. Dam*, M. Pratama^, MD. M. Ferdaus*, S. Anavatti, H. Abbas, Scalable Adversarial Online Continual Learning, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022 - Core A (Codes: https://github.com/TanmDL/SCALE)

4. M. De Carvalho*, M. Pratama, J. Zhang, Y. Sun, Class-Incremental Learning via Knowledge Amalgamation, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022 - Core A (Codes: https://github.com/Ivsucram/CFA)

5. A. Rakaraddi*, M. Pratama^, Unsupervised Learning for Identifying High Eigenvector Centrality Nodes: A Graph Neural Network Approach, IEEE BigData 2021 - Core B (Codes: https://github.com/codexhammer/CUL)

6. M. Pratama^, A. Ashfahani*, E. Lughofer, Unsupervised Continual Learning via Self-Adaptive Deep Clustering Approach, International Joint Conference on Artificial Intelligence Workshop on Continual Semi-Supervised Learning, 2021 (1st CSSL@IJCAI) (Codes: https://doi.org/10.21979/N9/P9DFJH)

7. A. Ashfahani*, M. Pratama, E. Lughofer, E. Yapp, Autonomous Deep Quality Monitoring in Streaming Environments, IJCNN, 2021 - Core B (Codes: https://doi.org/10.21979/N9/LZEBMP)

8. B. Kocer**, A. Hady**, H. Kandath**, M. Pratama, Deep Neuromorphic Controller with Dynamic Topology for Aerial Robots, ICRA, 2021 - Core B (Codes: https://tinyurl.com/2fp7zy2c)

9. M. Das**, M. Pratama, T. Tjahjowidodo, A Self-Evolving Mutually-Operative Recurrent Network-based Model for Online Tool Condition Monitoring in Delay Scenario, KDD, 2020, pp. 2775-2783 - Core A*

10. M. Das**, M. Pratama, J. Zhang, Y-S. Ong, A Skip-connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario, in proceeding of 34th AAAI conference on Artificial Intelligence, 2020, New York, USA - Core A*

11. M. Pratama, A. Ashfahani*, A. Hadi**, Weakly Supervised Deep Learning Approach in Streaming Environments. IEEE BigData 2019: 1195-1202 - Core B (Codes: https://doi.org/10.21979/N9/UU5EVH)

12. K. Anam, S. Bukhori, F. S. Hanggara, M. Pratama, Subject-independent Classification on Brain-Computer Interface using Autonomous Deep Learning for finger movement recognition. EMBC 2020: 447-450 

13. AMS. Aradya*, S. Sundaram, M. Pratama, Metaheuristic Spatial Transformation (MST) for accurate detection of Attention Deficit Hyperactivity Disorder (ADHD) using rs-fMRI. EMBC 2020: 2829-2832 

14. S. Subhajit*, M. Pratama, S. Sundaram, N. Srikanth, A Dual Network Solution (DNS) for Lag-Free Time Series Forecasting. IJCNN 2020: 1-8 - Core B

15. M Das**, M Pratama, S Savitri**, J Zhang, MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification, in proceeding of 2019 IEEE International Conference on Data Mining (ICDM), 110-119, 2019, Beijing, China - Core A*

16. M Pratama, C Za'in*, A Ashfahani*, YS Ong, W Ding, Automatic construction of multi-layer perceptron network from streaming examples, Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 1171-1180, 2019, Beijing, China - Core A (Python Codes: https://doi.org/10.21979/N9/JG7NJS, Matlab Codes: https://doi.org/10.21979/N9/YIEZYN)

17. M Pratama, M de Carvalho**, R Xie**, E Lughofer, J Lu, ATL: Autonomous Knowledge Transfer from Many Streaming Processes, Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 269-278, 2019, Beijing, China - Core A (Python Codes: https://github.com/Ivsucram/ATL_Python, Matlab codes: https://github.com/Ivsucram/ATL_Matlab)

18. A Ashfahani*, M Pratama, Autonomous deep learning: Continual learning approach for dynamic environments, in Proceedings of the 2019 SIAM International Conference on Data Mining, 666-674, 2019, Calgary, Canada - Core A (Python Codes: https://doi.org/10.21979/N9/PR0LV2 , Matlab codes: https://doi.org/10.21979/N9/R97JSN)

19. AMS Aradhya*, A Joglekar, S Suresh, M Pratama, Deep Transformation Method for Discriminant Analysis of Multi-Channel Resting State fMRI, Proceedings of the 33rd AAAI Conference on Artificial Intelligence, 2556-2563, 2019, Hawai, USA - Core A* 

20. C. Za’in*, A. Ashfahani*, M. Pratama, E. Lughofer, E. Pardede, Scalable Teacher-Forcing Networks under Spark Environments for Large-Scale Streaming Problems. EAIS 2020: 1-8 (Codes: https://doi.org/10.21979/N9/BCBECU)

21. B. Kocer**, M. Tiryaki, M. Pratama, T. Tjahjowidodo, G. G. Lem Seet, Aerial Robot Control in Close Proximity to Ceiling: A Force Estimation-based Nonlinear MPC. IROS 2019: 2813-2819 - Core A

22. M. Das**, M. Pratama, A. Ashfahani*, S. Subhrajit*, FERNN: A Fast and Evolving Recurrent Neural Network Model for Streaming Data Classification. IJCNN 2019: 1-8 - Core B

23. MM. Ferdaus*, A. Hady**, M. Pratama, H. Kandath**, S. Anavatti,  RedPAC: A Simple Evolving Neuro-Fuzzy-based Intelligent Control Framework for Quadcopter. FUZZ-IEEE 2019: 1-7 - Core B (Codes: https://doi.org/10.21979/N9/LJX9LZ)

24. H. Kandath**, A. Hady*, M. Pratama, B.F. Ng, Robust Evolving Neuro-Fuzzy Control of a Novel Tilt-rotor Vertical Takeoff and Landing Aircraft. FUZZ-IEEE 2019: 1-6 - Core B (Codes: https://doi.org/10.21979/N9/GVISVM)

25. S. Ozawa, Ah-Hwee Tan, P. P. Angelov, A. Roy, M. Pratama, INNS Conference on Big Data and Deep Learning 2018, Sanur, Bali, Indonesia, 17-19 April 2018. Procedia Computer Science 144, Elsevier 2018 

• For a full list of publication, one can check my google scholar, DBLP or UniSA homepage.

• Other codes of our papers might be made available upon requests. Please kindly approach me.   

Special Issue

• M. Pratama, P. Angelov, E. Lughofer, Recent Progress on Autonomous Machine Learning, Information Sciences

• M. Pratama, E.Lughofer, D. Wang, Online Real-Time Learning Strategies for Data Streams , Neurocomputing

• M. Pratama, E. Lughofer, S. Suresh, M.S. Mouchaweh, Advanced Soft Computing for Prognostics Health Management, Applied Soft Computing

Service

• Associate Editor, IEEE Transactions on Neural Networks and Learning Systems (IF: 14.255)

• Associate Editor, IEEE Transactions on Fuzzy Systems (IF: 12.029) 

• Associate Editor, Information Sciences (IF: 6.795) 

• Associate Editor, Knowledge-based Systems (IF: 8.08) 

• Associate Editor, Complex & Intelligent Systems (IF: 6.859)

• Associate Editor, Complexity (IF: 2.591) 

• Associate Editor, Evolving Systems (IF: 2.070) 

• Associate Editor, Journal of Control and Decision 

• Editor in Chief, International Journal of Business Intelligence and Data Mining (stepped down in 2022)

• IEEE CIS Emergent Technologies, Technical Committee

• IEEE CIS Singapore Chapter, ExCom 

• Tutorial and Keynote Chair, IEEE SSCI 2022

• Koordinator Klaster Keahlian Telekomunikasi, Robotics, IT, AI, Big Data, Ikatan Ilmuwan Indonesia Internasional (2020 - present)

• Program Committee, AAAI, IJCAI, ICONIP, ICMLA, FUZZ-IEEE, CIKM, etc.

• Scientific Committee, 12th Conference on Learning Factories (CLF2022)

• Tutorial on AML in IEEE SSCI 2020 

• Program Chair of IEEE ICA 2022

• Program Chair of INNS BDDL 2018

• General Chair of 1st ICDM Workshop on AML 2019

• Local Arrangement Chair of ICBK 2018

• Publication Chair, IEEE SSCI, 2018