Junn Yong Loo
About Me
I am a researcher with a Ph.D. in Robotics and Mechatronics Engineering. My research areas span generative models and state estimation, with applications in medical imaging, industrial informatics, and robotics.
News & Updates
- April 2026: Commenced a new role as a Postdoctoral Research Fellow at Nanyang Technological University (NTU) in the SIGNAL group.
- 2024: Awarded the Fundamental Research Grant Scheme (FRGS) as Principal Investigator for research on autonomous driving.
- 2023: Transitioned to Lecturer (Assistant Professor) at the School of Information Technology, Monash University Malaysia.
Experience
- Postdoctoral Research Fellow, Nanyang Technological University (NTU), SIGNAL Group (April 2026 – Present)
- Lecturer (Assistant Professor), School of Information Technology, Monash University Malaysia (2023 – 2026)
- Postdoctoral Research Fellow, School of Information Technology, Monash University Malaysia (2022 – 2023)
Education
- Ph.D. in Robotics and Mechatronics Engineering, Monash University Malaysia (2018 – 2022)
- Advisor: Prof. Chee Pin Tan
- Dissertation: Development of Estimation Scheme for Soft Robotics System
- Bachelor of Mechanical Engineering (Honours), Monash University Malaysia (2014 – 2018)
Research Grants & Projects
- Principal Investigator, Ministry of Higher Education Malaysia, Fundamental Research Grant Scheme (FRGS) (2024 - 2027).
- Project: Efficient and Interpretable Multi-view Deformable Transformer with 3D Position Embeddings and Intelligent Queries for Autonomous Driving.
- Principal Investigator, Monash University Malaysia, SIT Collaborative Research Seed Grants (2024 - 2025).
- Project: Efficient and Interpretable Modular End-to-end Autonomous Driving System.
Selected Publications
- Loo JY, Ding ZY, Baskaran VM, Nurzaman SG, Tan CP. Robust multimodal indirect sensing for soft robots via neural network-aided filter-based estimation. Soft Robotics, 9(3): 591–612, 2022.
- Loo JY, Ding ZY, Baskaran VM, Nurzaman SG, Tan CP. Sigma-point Kalman filter with nonlinear unknown input estimation via optimization and data-driven approach for dynamic systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 54(10): 6068–6081, 2024.
- Loo JY, Adeline M, Lau JK, Leong FY, Tew HH, Pal A, Baskaran VM, Ting CM, Phan RCW. Learning energy-based generative models via potential flow: A variational principle approach to probability density homotopy matching. Transactions on Machine Learning Research (TMLR) [JCR Certification], 2025.
- Loo JY, Tew HH, Leong FY, Ding ZY, Baskaran VM, Ting C-M, Tan CP. A deep probabilistic flow-based framework for unsupervised cross-domain soft sensing. IEEE Transactions on Industrial Informatics, In Press, 2026.
- Ding ZY, Loo JY, Baskaran VM, Nurzaman SG, Tan CP. Predictive uncertainty estimation using deep learning for soft robot multimodal sensing. IEEE Robotics and Automation Letters, 6(2): 951–957, 2021.
- Ding ZY, Loo JY, Nurzaman SG, Tan CP, Baskaran VM. A zero-shot soft sensor modeling approach using adversarial learning for robustness against sensor fault. IEEE Transactions on Industrial Informatics, 19(4): 5891–5901, 2022.
- Bakibillah ASM, Tan YH, Loo JY, Tan CP, Kamal MAS, Pu Z. Robust estimation of traffic density with missing data using an adaptive-R extended Kalman filter. Applied Mathematics and Computation, 421: 126915, 2022.
- Chor WT, Tan CP, Bakibillah ASM, Pu Z, Loo JY. Robust vehicle mass estimation using recursive least M-squares algorithm for intelligent vehicles. IEEE Transactions on Intelligent Vehicles, 9(1): 165–177, 2023.
- Sapai S, Loo JY, Ding ZY, Tan CP, Baskaran VM, Nurzaman SG. A deep learning framework for soft robots with synthetic data. Soft Robotics, 10(6): 1224–1240, 2023.
- Sapai S, Loo JY, Ding ZY, Tan CP, Phan RCW, Baskaran VM, Nurzaman SG. Cross-domain transfer learning and state inference for soft robots via a semi-supervised sequential variational Bayes framework. IEEE International Conference on Robotics and Automation (ICRA), 2023.
- Sapai S, Baskaran VM, Loo JY, Tan CP. Contrastive autoencoder for robust state modelling of soft robots in incomplete and noisy environments. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025.
- Tan YF, Loo JY, Noman F, Phan RCW, Ting CM, Ombao H. BrainFC-CGAN: A conditional generative adversarial network for brain functional connectivity augmentation and aging synthesis. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.
- Adeline M, Loo JY, Baskaran VM. MDHA: Multi-scale deformable transformer with hybrid anchors for multi-view 3D object detection. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024.
- Yap SY, Loo JY, Noman F, Phan RCW, Ting CM. A deep probabilistic spatiotemporal framework for dynamic graph representation learning with application to brain disorder identification. International Joint Conference on Artificial Intelligence (IJCAI), 2024.
- Tew HH, Loo JY, Tang X, Ombao H, Noman F, Phan RCW, Ting CM. T2I-Diff: fMRI signal generation via time-frequency image transform and classifier-free denoising diffusion models. Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
- Tew HH, Ding F, Li G, Loo JY, Ting CM, Ding ZY, Tan CP. ST-HCSS: Deep spatio-temporal hypergraph convolutional neural network for soft sensing. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025.
- Tew HH, Loo JY, Yu LF, Lau JK, Fan D, Ombao H, Phan RCW, Tan CP, Ting CM. Functional MRI time series generation via wavelet-based image transform and spectral flow matching for brain disorder identification. International Conference on Learning Representations (ICLR), 2026.