Project: Machine-learning based monitoring system for cyanobacterial blooms in tropical freshwater reservoirs
Year: 2027 - 2030
Team: Bronson Philippa, Mahmood Sadat Noori, Tao (Kevin) Huang
Project: Data-Efficient AI for Precision Weed Monitoring in Tropical Forests
Year: 2026 - 2029
Team: Tao (Kevin) Huang
Project: Feasibility of Vibration-Based Projectile Impact Localisation on Steel Targets
Year: 2026
Team: Tao (Kevin) Huang, Bruce Belson, and Laurance Papale
Project: AI Foundations for Fire-Risk Vegetation Mapping: Aerial Data Collection and Dataset Suitability Assessment
Year: 2026
Team: Tao (Kevin) Huang, Yvette Everingham, Stephanie Baker, and Nico Adams
Project: Foundations for AI-Based Ground-Level Weed Detection in Australian Forestry Plantations: Data Acquisition and Feasibility
Year: 2026
Team: Tao (Kevin) Huang, Euijoon Ahn, Eric Wang, Mostafa Rahimi Azghadi
Project: 3D Tracking Videography Equipment Grant
Year: from July 2025
Team: Tao (Kevin) Huang, Bronson Philippa, Myles Menz, Stephanie Baker, Martijn van de Pol, Lori Lach
Project: Remote saltwater crocodile (Crocodylus porosus) detection using digital video AI
Year: 2025 - 2027
Team: Tao (Kevin) Huang, Euijoon Ahn, Mostafa Rahimi Azghadj, Bouchra Senadji
Project: Detection of animals with low-cost radar
Year: 2023
Team: Myles Menz, Bronson Philippa, Tao (Kevin) Huang.
About: This project will investigate the potential of millimetre-wave imaging radar for the detection of animals in airspace. These radar systems have been developed for the automotive industry but have yet to be assessed for their capability as a detection tool for biological targets such as insects, birds, and bats. There is a huge market gap for low-cost biological sensors in industries such as agriculture, environmental management and conservation, and human health. This project will provide a proof of concept that can then be used to generate further funding and a start-up to further develop this product, with the intention of deploying a network of units as a sensor array.
Project: Fusion of wearable and environmental sensors for remote monitoring of health and well-being in elderly populations
Year: 2023
Team: Stephanie Baker, Euijoon Ahn, Tao (Kevin) Huang, Bronson Philippa, Caryn West, and Christopher Rouen.
About: This project aims to improve healthcare access for aged care in remote areas of Australia by developing an intelligent home health monitoring prototype. The system will use wearable sensors, mmWave technology, and AI to monitor vital signs, physical activity, and environmental conditions. It will analyse the data collected and provide early warning alerts to medical professionals and caregivers. By demonstrating the feasibility of this innovative solution, the project seeks to improve the quality of life for older adults in remote areas and provide peace of mind to caregivers and family members.
Project: Low-cost Sensing Methods and Hybrid Learning Models (DP220101634)
Year: 2022, 2023, 2024, 2025
Team: Professor Wei Xiang; Professor Yi-Ping Phoebe Chen; Dr. Tao (Kevin) Huang; Dr. Peng Cheng; Dr. Tran Khoa Phan; Professor Lajos Hanzo.
About: This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine-learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.
Project: Lightweight Blockchain Development for Healthcare IoT
Year: 2022
Team: Jusak Jusak (JCUS), Tao (Kevin) Huang (JCUA), and Steven Kerrison(JCUS).
Project: Design low-cost computer-vision-based discharge sensing technology
Year: 2020
Team: Tao (Kevin) Huang and Jason Holdsworth.
Wei Xiang, Tao (Kevin) Huang, Lei Lei, and Mostafa Rahimi Azghadi, “Internet of Things and Big Data Analytics for Cairns Marine,” Australian Government Department of Industry, Innovation and Science, Innovations Connections Program, May 2019 - May 2020.
Tao Huang, “Improving the throughput of the wireless data link in Australia rural area,” Endeavour Australia Cheung Kong Research Fellowship, Australian Government Department of Education, Apr. 2014 - Sept. 2014.
Tao Huang, “Dataset Collection for Multi-modal Perception System in Complex Tropical Terrain,” College of Science and Engineering Adopt an End-User Research Facilitation Scheme, James Cook University, 2023.
Tao Huang, “Enhancing Perception Capabilities through Cooperative Sensor Fusion and Information Sharing in Multi-Agent Systems,” College of Science and Engineering ECR/New staff Research Support Scheme, James Cook University, 2023.
Tao Huang, “Deep learning-based radar perception for autonomous vehicle/robot,” Earlier Career Researcher Research Support Scheme, James Cook University, 2022.
Tao Huang, “Real-time Live Coral Health Monitoring System,” Adopt an End-User Research Facilitation Scheme, James Cook University, 2021.
Tao Huang, “Low-cost sensing and deep learning-based water quality monitoring,” Earlier Career Researcher Research Support Scheme, James Cook University, 2021.
M. U. Zia, W. Xiang, T. Huang, and J. N. Chattha, “Deep learning-based estimation and detection enhancements in HRIS mMIMO systems,” IEEE Trans. Commun., accepted for publication, 24 Aug., 2026. [IF: 8.3]
W. Ai, L. Zheng, L. Yang, M. Liu, X. Zhu, J. Bai, T. Huang, W. Xiang, and Z. Ma, “SRCDet: Sparse fusion of surround-view radar and camera for 3D object detection,” Meas. Sci. Technol., accepted for publication, 12 Aug., 2026.
X. Zhou, T. Huang, Q.-L. Han, R. Abbas, and M. Rahimi Azghadi, “AFFormer: Adaptive feature fusion transformer for V2X cooperative perception under channel impairments,” IEEE Trans. Intell. Transp. Syst., accepted for publication, 10 Aug., 2026. [IF: 9.1]
Q. Liu, T. Huang, J. Yang, and W. Xiang, “From pixels to images: A structural survey of deep learning paradigms in remote sensing image semantic segmentation,” IEEE Access, vol. 14, pp. 125360–125394, 2026, doi: 10.1109/ACCESS.2026.3721042. [IF: 4.2]
Q. Liu, Y. Dong, T. Huang, L. Zhang, and B. Du, “KnowCL: A universal knowledge-embedded contrastive learning framework for hyperspectral image classification,” Knowl.-Based Syst., accepted for publication, 30 Aug., 2026. [IF: 8.0]
R. Guan, J. Liu, N. Ouyang, S. Liang, D. Liu, X. Sun, L. Zheng, M. Xu, T. Huang, Y. Yue, G. Mao, and H. Xiong, “Enhance 3D visual grounding through LiDAR and radar point clouds fusion for autonomous driving,” IEEE Trans. Intell. Transp. Syst., accepted for publication, 20 Jul., 2026. [IF: 9.1]
M. U. Zia, W. Xiang, T. Huang, J. Ahmad, J. N. Chattha, R. Abbas, and A. Mahmood, “Deep learning-enabled CSI estimation and detection in modern multi-antenna systems,” IEEE Open J. Commun. Soc., early access, 2026, doi: 10.1109/OJCOMS.2026.3705258. [IF: 6.1]
L. Wang, T. Chen, X. Li, T. Huang, B. Zhou, Y. Zhang, and S. Ke, “GeoSAT: Long-term time series forecasting with GeoSparse attention and tempo-spatial feature extraction,” J. King Saud Univ. Comput. Inf. Sci., vol. 38, Art. no. 442, 2026, doi: 10.1007/s44443-026-00855-8.[IF: 6.4]
M. Islam, T. Huang, E. Ahn, and U. Naseem, “Multimodal generative AI for human motion understanding and generation: A survey and way forward,” Inf. Fusion, vol. 135, Art. no. 104435, Nov. 2026, doi: 10.1016/j.inffus.2026.104435. [IF: 17.4]
L. Liu, R. Ji, C. Zhou, Y. Zhang, Z. Kong, and T. Huang, “Joint beamforming for internet of vehicles via IBKA-driven intelligent reflecting surface optimization,” Alexandria Eng. J., vol. 144, pp. 1–11, 2026, doi: 10.1016/j.aej.2026.04.022. [IF: 6.8]
Y. Liu, Z. Kong, T. Huang, Y. Yang, C. Song, Q.-L. Han, and B. Huang, “Latent abstraction bridge transformer for generalizable nonintrusive load monitoring,” Sci. Rep., vol. 16, no. 1, Art. no. 20046, 2026, doi: 10.1038/s41598-026-48516-0. [IF: 4.9]
M. Hou, G. Wang, R. Guan, J. Liu, T. Huang, and Q.-L. Han, “ScopeDrive: Text-anchored cross-modal calibration and density-aware modulation for autonomous driving,” IEEE Trans. Ind. Informat., vol. 22, no. 8, pp. 7124–7135, 2026, doi: 10.1109/TII.2026.3683432. [IF: 9.9]
H. Li, J. Liu, M. Schell, T. Huang, A. Lauer, K. Schregel, J. Jesser, D. F. Vollherbst, M. Bendszus, S. Heiland, and T. Hilgenfeld, “Performance of a GPU- and time-efficient pseudo-3D network for magnetic resonance image super-resolution and motion artifact reduction,” Sci. Rep., 2026, doi: 10.1038/s41598-026-43804-1. [IF: 4.9]
H. Yu, J. Guo, X. Cao, X. Li, Y. Li, J. Hao, H. Yang, X. Zhou, and T. Huang, “DEGF-Net: Dual-encoder global–local joint feature aggregation network for colorectal polyp segmentation,” Biomed. Signal Process. Control, vol. 120, Part A, Art. no. 110023, Jul. 2026, doi: 10.1016/j.bspc.2026.110023. [IF: 4.9]
B. Li, J. Yang, and T. Huang, “Lyapunov compatibility-based adaptive consensus algorithm in PV-BESS integrated island DC microgrids: A dynamic state of charge balancing,” IEEE Trans. Sustain. Energy, early access, 2026, doi: 10.1109/TSTE.2026.3669896. [IF: 10.3]
S. Zou, Y. Yang, Y. Wen, T. Huang, X. Du, Y. Wang, and Y. Li, “Intelligent hardware acceleration optimization method for real-time junction temperature evaluation of power IGBT modules,” Microelectron. Reliab., vol. 179, Art. no. 116041, 2026, doi: 10.1016/j.microrel.2026.116041.
S. Guo, Y. Yang, H. Ma, and T. Huang, “Junction temperature estimation method for power modules based on gate voltage undershoot amplitude-phase 2-D features with load current independence,” IEEE Trans. Ind. Electron., early access, 2026, doi: 10.1109/TIE.2025.3639820. [IF: 7.2]
C. Song, Z. Kong, S. Liu, L. Ding, B. Huang, W. Xiang, and T. Huang, “ADMM-enhanced CNN training framework with global convergence guarantees,” IEEE Trans. Artif. Intell., vol. 7, no. 6, pp. 3205–3220, Jun. 2026, doi: 10.1109/TAI.2025.3636117.
H. Wang, S. Li, B. Bai, J. Li, R. Fei, and T. Huang, “From clutter to clarity: Enhancing radar-based human activity recognition with deep attention and feature denoising,” IEEE Sensors J., vol. 26, no. 1, pp. 753–766, Jan. 2026, doi: 10.1109/JSEN.2025.3633200. [IF: 4.5]
Z. Wei, L. Zheng, J. Liu, T. Huang, Q.-L. Han, W. Zhang, and F. Zhang, “MS-Occ: Multi-stage LiDAR-camera fusion for 3D semantic occupancy prediction,” IEEE Robot. Autom. Lett., vol. 11, no. 1, pp. 370–377, Jan. 2026, doi: 10.1109/LRA.2025.3632759. [IF: 5.3]
I. E. Khudaa, A. Aftab, M. U. Zia, S. Ikram, and T. Huang, “Construction of physiological anxiety beyond individual pathology: Integrating psychophysiological biomarkers and socio-digital contexts among university students in a post-pandemic world,” Crit. Public Health, vol. 35, no. 1, 2025.
G. Ding, Y. Xia, R. Guan, Q. Wu, T. Huang, W. Ding, J. Sun, and G. Mao, “OptiPMB: Enhancing 3D multi-object tracking with optimized Poisson multi-Bernoulli filtering,” IEEE Trans. Intell. Transp. Syst., vol. 26, no. 12, pp. 22312–22328, Dec. 2025, doi: 10.1109/TITS.2025.3619674. [IF: 9.1]
M. U. Zia, W. Xiang, T. Huang, J. Ahmad, J. N. Chattha, I. H. Naqvi, and F. A. Butt, “Unifying ground and air: A comprehensive review of deep learning-enabled CAVs and UAVs,” Artif. Intell. Rev., vol. 59, Art. no. 19, 2026, doi: 10.1007/s10462-025-11425-1. [IF: 18.8]
Z. Wei, T. Huang, and F. Zhang, “LiGaussOcc: Fully self-supervised 3D semantic occupancy prediction from LiDAR via Gaussian splatting,” Sensors, vol. 25, no. 18, Art. no. 5889, 2025. [IF:4.0]
Z. Han, D. Wu, J. Zhang, T. Huang, Q.-L. Han, M. Zhang, and J. W. Ringsberg, “Adaptive spatio-temporal voxel-based trajectory planning and optimization for close-quarters ships collision avoidance,” IEEE Trans. Intell. Transp. Syst., vol. 26, no. 12, pp. 23151–23166, Dec. 2025, doi: 10.1109/TITS.2025.3610986. [IF: 9.1]
M. Wang, Z. Kong, S. Liu, T. Huang, S. Yan, M. Allahbakhsh, and J. Yuan, “Reinforcement learning-based secure communications over MIMO interference channels,” IEEE Trans. Veh. Technol., vol. 75, no. 3, pp. 5139–5144, Mar. 2026, doi: 10.1109/TVT.2025.3608774. [IF: 7.1]
X. Huang, T. Huang, S. Zhao, W. Xiang, W. Zhang, and G. Zhang, “Joint optimization of task partial offloading and resource allocation in a dual-blockchain-enabled MEC system with parallelism constraints,” IEEE Trans. Commun., vol. 73, no. 12, pp. 13725–13740, Dec. 2025. [IF: 8.3]
Z. Zhang, J. Liu, Y. Xia, T. Huang, Q.-L. Han, and H. Liu, “LEGO: Learning and graph-optimized modular tracker for online multi-object tracking with point clouds,” IEEE Trans. Circuits Syst. Video Technol., vol. 36, no. 2, pp. 2419–2432, Feb. 2026, doi: 10.1109/TCSVT.2025.3600881. [IF: 8.3]
T. Huang*, J. Liu*, X. Zhou*, D. C. Nguyen, M. Rahimi Azghadi, Y. Xia, Q.-L. Han, and S. Sun, “Vehicle-to-everything cooperative perception for autonomous driving,” Proc. IEEE, vol. 113, no. 5, pp. 443–477, 2025, doi: 10.1109/JPROC.2025.3600903. [IF: 30.9] (* Co-First Authors)
L. Wang, T. Huang, Y. Zhang, K. An, and J. Yuan, “Predicting retweets using social trust-aware graph neural network approach,” Multimedia Syst., vol. 31, no. 6, Art. no. 404, 2025.
B. Zhu, Z. He, W. Xiong, G. Ding, T. Huang, and W. Xiang, “ProbRadarM3F: mmWave radar-based human skeletal pose estimation with probability map guided multi-format feature fusion,” IEEE Trans. Aerosp. Electron. Syst., vol. 61, no. 6, pp. 15832–15842, 2025. [IF: 7.0]
X. Huang, T. Huang, P. Cheng, J. Yuan, S. Zhao, and G. Zhang, “Optimizing task migration for public and private services in vehicular edge networks: A dual-layer graph neural network approach,” IEEE Trans. Mobile Comput., vol. 24, no. 12, pp. 13191–13208, Dec. 2025, doi: 10.1109/TMC.2025.3589245. [IF: 9.2]
D. Fan, T. Huang, L. Guan, J. Li, R. Fei, and L. Sevgi, “Noncontact multi-person respiration detection using time modulated array,” IEEE Sensors J., early access, 2025, doi: 10.1109/JSEN.2025.3589182. [IF: 4.5]
Q. Liu, T. Huang, Y. Dong, and W. Xiang, “Enhancing oil spill detection with controlled random sampling: A multimodal fusion approach using SAR and HSI imagery,” Remote Sens. Appl. Soc. Environ., vol. 38, Art. no. 101601, 2025, doi: 10.1016/j.rsase.2025.101601. [IF: 4.5]
W. Xiang, M. U. Zia, J. Ahmad, P. Cheng, K. Yu, and T. Huang, “Deep learning-enabled RIS massive MIMO systems in industrial IoT: A joint communication and computation approach,” IEEE J. Sel. Areas Commun., pp. 2981–2996, 2025. [IF: 17.2]
P. Hu, Z. Kong, T. Huang, and L. Ding, “Multi-risk factor and knowledge entropy framework for alternating current arc fault detection,” Electronics, vol. 14, no. 4, 12 Feb. 2025.
A. Langley, M. Lonergan, T. Huang, and M. Rahimi Azghadi, “Analyzing mixed construction and demolition waste in material recovery facilities: Evolution, challenges, and applications of computer vision and deep learning,” Resour. Conserv. Recycl., vol. 217, Art. no. 108218, 2025. [IF: 10.9]
T. Meng, C. Fu, M. Huang, T. Huang, X. Wang, J. He, and W. Shi, “Localization-guided track: A deep association multi-object tracking framework based on localization confidence of camera detections,” IEEE Sensors J., vol. 25, no. 3, pp. 5282–5293, Feb. 1, 2025, doi: 10.1109/JSEN.2024.3522021. [JIF: 4.5]
Y. Yang, J. Liu, T. Huang, Q.-L. Han, G. Ma, and B. Zhu, “RaLiBEV: Radar and LiDAR BEV fusion learning for anchor box free object detection systems,” IEEE Trans. Circuits Syst. Video Technol., vol. 35, no. 5, pp. 4130–4143, May 2025, doi: 10.1109/TCSVT.2024.3521375. [JIF: 10.8]
F. Guo, Z. Guo, H. Tang, T. Huang, and Y. Wu, “A multi-gated deep graph network with attention mechanisms for taxi demand prediction,” Appl. Soft Comput., vol. 169, Art. no. 112609, Jan. 2025, doi: 10.1016/j.asoc.2024.112609. [JIF: 7.8]
Z. Kong, L. Gan, J. Song, T. Huang, W. Yin, S. Yan, and J. Yuan, “Robust outage-constrained secrecy rate of hybrid power line and wireless communication with artificial noise-aided beamforming for smart grid,” IEEE Trans. Commun., vol. 73, no. 6, pp. 3940–3955, Jun. 2025, doi: 10.1109/TCOMM.2024.3502678. [JIF: 8.4]
H. Yu, K. Yan, J. Chen, X. Li, J. Guo, X. Xing, and T. Huang, “Study on the methods of hyperspectral image saliency detection based on MBCNN,” Vis. Comput., vol. 41, no. 8, pp. 5251–5266, 2025, doi: 10.1007/s00371-024-03719-2.
L. Sun, Z. Chen, T. Huang, F. Shu, and S. Yan, “Near-field communication with random frequency diverse array,” IEEE Wireless Commun. Lett., vol. 14, no. 1, pp. 213–217, Jan. 2025, doi: 10.1109/LWC.2024.3495653. [JIF: 5.5]
W. Zhang, L. Tan, T. Huang, X. Huang, M. Huang, and G. Zhang, “Resource allocation and trajectory optimization in multi-UAV collaborative vehicular networks: An extended multiagent DRL approach,” IEEE Internet Things J., vol. 12, no. 8, pp. 9391–9404, Apr. 2025, doi: 10.1109/JIOT.2024.3492953. [JIF: 8.9]
W. Zhu, L. Shi, J. Li, B. Cao, K. Wei, Z. Wang, and T. Huang, “Trustworthy blockchain-assisted federated learning: Decentralized reputation management and performance optimization,” IEEE Internet Things J., vol. 12, no. 3, pp. 2890–2905, Feb. 1, 2025, doi: 10.1109/JIOT.2024.3480995. [JIF: 8.9]
B. Jia, Z. Guo, T. Huang, F. Guo, and H. Wu, “A generalized Lorenz system-based initialization method for deep neural networks,” Appl. Soft Comput., vol. 167, Part A, Art. no. 112316, Dec. 2024, doi: 10.1016/j.asoc.2024.112316. [JIF: 6.6]
Z. Han, D. Wu, J. Zhang, T. Huang, Q.-L. Han, and M. Zhang, “COLREGs-Adaptive trajectory planning and decision-making in maritime autonomous surface ships,” Ocean Eng., vol. 312, Part 3, Art. no. 119308, Nov. 2024, doi: 10.1016/j.oceaneng.2024.119308. [JIF: 5.5]
Z. Kong, J. Song, S. Yang, L. Gan, W. Meng, T. Huang, and S. Chen, “Distributed robust artificial-noise-aided secure precoding for wiretap MIMO interference channels,” IEEE Trans. Inf. Forensics Security, vol. 19, pp. 10130–10140, 2024, doi: 10.1109/TIFS.2024.3486548. [JIF: 8.0]
Z. Zhang, J. Liu, X. Zhou, T. Huang, Q.-L. Han, J. Liu, and H. Liu, “On the federated learning framework for cooperative perception,” IEEE Robot. Autom. Lett., vol. 9, no. 11, pp. 9423–9430, Nov. 2024, doi: 10.1109/LRA.2024.3457374. [JIF: 5.3]
Y. Zhou, H. Li, J. Liu, Z. Kong, T. Huang, E. Ahn, Z. Lv, J. Kim, and D. D. Feng, “Explicit abnormality extraction for unsupervised motion artifact reduction in magnetic resonance imaging,” IEEE J. Biomed. Health Inform., vol. 29, no. 6, pp. 3853–3863, Jun. 2025, doi: 10.1109/JBHI.2024.3444771. [JIF: 6.8]
X. Cao, H. Yu, K. Yan, R. Cui, J. Guo, X. Li, X. Xing, and T. Huang, “DEMF-Net: A dual encoder multi-scale feature fusion network for polyp segmentation,” Biomed. Signal Process. Control, vol. 96, Part A, Art. no. 106487, Oct. 2024, doi: 10.1016/j.bspc.2024.106487. [JIF: 5.1]
Y. Zhou, Z. Kong, T. Huang, E. Ahn, H. Li, and L. Ding, “WaveletDFDS-Net: A dual forward denoising stream network for low-dose CT noise reduction,” Electronics, vol. 13, no. 10, Art. no. 1906, May 2024, doi: 10.3390/electronics13101906.
H. Ma, Y. Yang, Z. Fan, T. Huang, W. Xiang, Y. Wen, and S. Cobreces, “A Fourier series-based steady-state thermal resistance model for power module,” IEEE J. Emerg. Sel. Topics Power Electron., vol. 12, no. 4, pp. 3912–3924, Aug. 2024, doi: 10.1109/JESTPE.2024.3398440. [JIF: 4.9]
J. Liu, H. Li, T. Huang, E. Ahn, K. Han, A. Razi, W. Xiang, J. Kim, and D. D. Feng, “Unsupervised representation learning for 3-D magnetic resonance imaging super-resolution with degradation adaptation,” IEEE Trans. Artif. Intell., vol. 5, no. 9, pp. 4660–4674, Sept. 2024, doi: 10.1109/TAI.2024.3397292. [IF: 6.1]
Z. Kong, J. Cui, L. Ding, T. Huang, and S. Yan, “Jamming precoding in AF relay-aided PLC systems with multiple eavesdroppers,” Sci. Rep., vol. 14, Art. no. 8335, Apr. 2024, doi: 10.1038/s41598-024-58735-y. [JIF: 4.9]
S. Sloan, R. R. Talkhani, T. Huang, J. Engert, and W. F. Laurance, “Mapping remote roads using artificial intelligence and satellite imagery,” Remote Sens., vol. 16, no. 5, Art. no. 839, Mar. 2024, doi: 10.3390/rs16050839. [JIF: 4.1]
B. Li, T. Huang, Z. Kong, L. Chen, J. Yang, and S. Sun, “Discrete control for state of charge balance in DC microgrids considering the disturbance of photovoltaics,” Int. J. Electr. Power Energy Syst., vol. 157, Art. no. 109879, Jun. 2024, doi: 10.1016/j.ijepes.2024.109879. [JIF: 5.0]
Z. Mi, Z. Kong, T. Huang, P. Shi, Z. Yu, and L. Ding, “Fixed-time hierarchical distributed control for flexible thermostatically controlled loads,” IEEE Syst. J., vol. 18, no. 2, pp. 1344–1355, Jun. 2024, doi: 10.1109/JSYST.2024.3366226. [JIF: 4.1]
X. Huang, T. Huang, S. Gu, S. Zhao, and G. Zhang, “Responsible federated learning in smart transportation: Outlooks and challenges,” IEEE Internet Things Mag., vol. 7, no. 5, pp. 22–28, Sept. 2024, doi: 10.1109/IOTM.001.2300286. [JIF: 5.7]
M. Haider, M. K. Peyal, T. Huang, and W. Xiang, “Road crack avoidance: A convolutional neural network-based smart transportation system for intelligent vehicles,” J. Intell. Transp. Syst., vol. 28, no. 5, pp. 605–617, 2024, doi: 10.1080/15472450.2023.2175613.
S. Liu, Z. Kong, T. Huang, Y. Du, and W. Xiang, “An ADMM-LSTM framework for short-term load forecasting,” Neural Netw., vol. 173, Art. no. 106150, May 2024, doi: 10.1016/j.neunet.2024.106150. [JIF: 7.2]
J. Liu, Q. Zhao, W. Xiong, T. Huang, Q.-L. Han, and B. Zhu, “SMURF: Spatial multi-representation fusion for 3D object detection with 4D imaging radar,” IEEE Trans. Intell. Veh., vol. 9, no. 1, pp. 799–812, Jan. 2024, doi: 10.1109/TIV.2023.3322729. [JIF: 14.3]
W. Xiong, J. Liu, T. Huang, Q.-L. Han, Y. Xia, and B. Zhu, “LXL: LiDAR excluded lean 3D object detection with 4D imaging radar and camera fusion,” IEEE Trans. Intell. Veh., vol. 9, no. 1, pp. 79–92, Jan. 2024, doi: 10.1109/TIV.2023.3321240. [JIF: 14.3]
X. Huang, T. Huang, W. Zhang, C. K. Yeo, S. Zhao, and G. Zhang, “Pricing optimization in MEC systems: Maximizing resource utilization through joint server configuration and dynamic operation,” IEEE Trans. Mobile Comput., vol. 23, no. 5, pp. 5863–5879, May 2024, doi: 10.1109/TMC.2023.3315334. [JIF: 9.2]
J. Ahmad, M. U. Zia, I. Naqvi, J. Chattha, F. Butt, T. Huang, and W. Xiang, “Machine learning and blockchain technologies for cybersecurity in connected vehicles,” WIREs Data Min. Knowl. Discov., vol. 14, no. 1, Art. no. e1515, Jan./Feb. 2024, doi: 10.1002/widm.1515. [JIF: 7.3]
X. Zhou, W. Xiang, and T. Huang, “A novel neural network for improved in-hospital mortality prediction with irregular and incomplete multivariate data,” Neural Netw., vol. 167, pp. 741–750, Oct. 2023, doi: 10.1016/j.neunet.2023.07.033. [JIF: 7.2]
X. Dang, W. Xiang, L. Yuan, Y. Yang, E. Wang, and T. Huang, “Deep unfolding scheme for grant-free massive-access vehicular networks,” IEEE Trans. Intell. Transp. Syst., vol. 24, no. 12, pp. 14443–14452, Dec. 2023, doi: 10.1109/TITS.2023.3296452. [JIF: 9.1]
M. M. Hasan, T. Saleh, A. Sophian, M. A. Rahman, T. Huang, and M. S. M. Ali, “Experimental modeling techniques in electrical discharge machining (EDM): A review,” Int. J. Adv. Manuf. Technol., vol. 127, nos. 5–6, pp. 2125–2150, 2023, doi: 10.1007/s00170-023-11603-x.
S. Kerrison, J. Jusak, and T. Huang, “Blockchain-enabled IoT for rural healthcare: Hybrid-channel communication with digital twinning,” Electronics, vol. 12, no. 9, Art. no. 2128, May 2023, doi: 10.3390/electronics12092128.
W. Meng, Y. Gu, J. Bao, X. Cui, L. Gan, T. Huang, and Z. Kong, “Cooperative jamming with AF relay in power monitoring and communication systems for mining,” Electronics, vol. 12, no. 4, Art. no. 1057, Feb. 2023, doi: 10.3390/electronics12041057.
Z. Kong, H. Ouyang, Y. Cao, T. Huang, E. Ahn, M. Zhang, and H. Liu, “Automated periodontitis bone loss diagnosis in panoramic radiographs using a bespoke two-stage detector,” Comput. Biol. Med., vol. 152, Art. no. 106374, Jan. 2023, doi: 10.1016/j.compbiomed.2022.106374. [JIF: 6.3]
S. Gu, Z. Yu, Q. Zhang, and T. Huang, “Energy-aware coded transmission strategy for hierarchical cooperative caching networks,” IEEE Wireless Commun. Lett., vol. 12, no. 1, pp. 178–182, Jan. 2023, doi: 10.1109/LWC.2022.3220810. [JIF: 5.5]
U. Zia, W. Xiang, G. M. Vitetta, and T. Huang, “Deep learning for parametric channel estimation in massive MIMO systems,” IEEE Trans. Veh. Technol., vol. 72, no. 4, pp. 4157–4167, Apr. 2023, doi: 10.1109/TVT.2022.3223896. [JIF: 7.1]
J. Liu, L. Bai, Y. Xia, T. Huang, B. Zhu, and Q.-L. Han, “GNN-PMB: A simple but effective online 3D multi-object tracker without bells and whistles,” IEEE Trans. Intell. Veh., vol. 8, no. 2, pp. 1176–1189, Feb. 2023, doi: 10.1109/TIV.2022.3217490. [JIF: 14.3]
U. Zia, W. Xiang, T. Huang, and I. H. Naqvi, “Deep learning-aided TR-UWB MIMO system,” IEEE Trans. Commun., vol. 70, no. 10, pp. 6579–6588, Oct. 2022, doi: 10.1109/TCOMM.2022.3199489. [JIF: 8.3]
M. Zhang, T. Huang, Z. Guo, and Z. He, “Complex-network-based traffic network analysis and dynamics: A comprehensive review,” Physica A: Stat. Mech. Appl., vol. 607, Art. no. 128063, Dec. 2022, doi: 10.1016/j.physa.2022.128063. [JIF: 3.1]
J. Liu, W. Xiong, L. Bai, Y. Xia, T. Huang, W. Ouyang, and B. Zhu, “Deep instance segmentation with automotive radar detection points,” IEEE Trans. Intell. Veh., vol. 8, no. 1, pp. 84–94, Jan. 2023, doi: 10.1109/TIV.2022.3168899. [JIF: 14.3]
R. Li, J. Cui, T. Huang, L. Yang, and S. Yan, “Optimal pulse-position modulation order and transmit power in covert communications,” IEEE Trans. Veh. Technol., vol. 71, no. 5, pp. 5570–5575, May 2022, doi: 10.1109/TVT.2022.3151197. [JIF: 7.1]
K. Han, W. Xiang, E. Wang, and T. Huang, “A novel occlusion-aware vote cost for light field depth estimation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 44, no. 11, pp. 8022–8035, Nov. 2022, doi: 10.1109/TPAMI.2021.3105523. [JIF: 18.6]
S. Gu, F. Wang, Q. Zhang, T. Huang, and W. Xiang, “Global repair bandwidth cost optimization of generalized regenerating codes in clustered distributed storage systems,” IET Commun., vol. 15, no. 19, pp. 2469–2481, Dec. 2021, doi: 10.1049/cmu2.12289.
S. Gu, X. Sun, Z. Yang, T. Huang, W. Xiang, and K. Yu, “Energy-aware coded caching strategy design with resource optimization for satellite-UAV-vehicle-integrated networks,” IEEE Internet Things J., vol. 9, no. 8, pp. 5799–5811, Apr. 2022, doi: 10.1109/JIOT.2021.3065664. [JIF: 8.7]
L. Powell, H. S. Lim, I. Brown, T. Huang, N. Munksgaard, M. Randall, J. Holdsworth, and H. Cook, “Innovation through collaboration: Improving urban water management for a reef council,” Water e-Journal, vol. 5, no. 3, 2020, doi: 10.21139/wej.2020.018.
S. Shi, Y. Li, S. Gu, T. Huang, and X. Gu, “Time allocation optimization and trajectory design in UAV-assisted energy and spectrum harvesting network,” IEEE Access, vol. 8, pp. 160537–160548, 2020, doi: 10.1109/ACCESS.2020.3021672. [JIF: 4.2]
T. Huang, X. Yuan, J. Yuan, and W. Xiang, “Optimization of data exchange in 5G vehicle-to-infrastructure edge networks,” IEEE Trans. Veh. Technol., vol. 69, no. 9, pp. 9376–9389, Sept. 2020, doi: 10.1109/TVT.2020.2971080. [JIF: 7.5]
R. Abbas, M. Shirvanimoghaddam, T. Huang, Y. Li, and B. Vucetic, “Novel design for short analog fountain codes,” IEEE Commun. Lett., vol. 23, no. 8, pp. 1306–1309, Aug. 2019, doi: 10.1109/LCOMM.2019.2910517. [JIF: 4.5]
W. Xiang, T. Huang, and W. Wan, “Machine learning based optimization for vehicle-to-infrastructure communications,” Future Gener. Comput. Syst., vol. 94, pp. 488–495, May 2019, doi: 10.1016/j.future.2018.10.047. [JIF: 5.9]
Q. Sun, T. Huang, and J. Yuan, “On lattice-partition-based physical-layer network coding over GF(4),” IEEE Commun. Lett., vol. 17, no. 10, pp. 1988–1991, Oct. 2013, doi: 10.1109/LCOMM.2013.081313.131410. [JIF: 4.4]
Q. Sun, J. Yuan, T. Huang, and W.-K. Shum, “Lattice network codes based on Eisenstein integers,” IEEE Trans. Commun., vol. 61, no. 7, pp. 2713–2725, Jul. 2013, doi: 10.1109/TCOMM.2013.050813.120759. [JIF: 8.3]
T. Huang, T. Yang, J. Yuan, and I. Land, “Design of irregular repeat-accumulate coded physical-layer network coding for Gaussian two-way relay channels,” IEEE Trans. Commun., vol. 61, no. 3, pp. 897–909, Mar. 2013, doi: 10.1109/TCOMM.2013.012313.110631. [JIF: 8.3]
T. Yang, I. Land, T. Huang, J. Yuan, and Z. Chen, “Distance spectrum and performance of channel-coded physical-layer network coding for binary-input Gaussian two-way relay channels,” IEEE Trans. Commun., vol. 60, no. 6, pp. 1499–1510, Jun. 2012, doi: 10.1109/TCOMM.2012.051712.110224. [JIF: 8.3]
G. Wang, W. Xiang, J. Yuan, and T. Huang, “Outage analysis of non-regenerative analog network coding for two-way multi-hop networks,” IEEE Commun. Lett., vol. 15, no. 6, pp. 662–664, Jun. 2011, doi: 10.1109/LCOMM.2011.050311.110006. [JIF: 4.4]
Abdullah, T. Huang, I. Lee, and E. Ahn, “DAMST: Domain-adaptive medical slice transformer for multi-center breast MRI classification,” in Proc. 3rd Deep Breath Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care (Deep-Brea3th), MICCAI 2026, Strasbourg, France, Sep. 2026.
Y. Yang, Z. Kong, Y. Liu, T. Huang, and W. Xiang, “Kronecker generative networks: A general neural architecture for parameter-efficient learning across classification tasks,” in Proc. 43rd Int. Conf. Mach. Learn. (ICML), Seoul, South Korea, 2026. [ICORE2026 A*]
D. Fan, T. Huang, B. Li, R. Fei, and J. Li, “Contactless cardiopulmonary monitoring using Wi-Fi channel features,” in Proc. 14th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Shenzhen, China, Jul. 13–16, 2026.
Abdullah, T. Huang, I. Lee, and E. Ahn, “Generating non-melanoma skin cancer histopathology images using latent diffusion representation learning,” in Computational Biomechanics for Medicine, CBM 2025, Lecture Notes in Bioengineering. Cham, Switzerland: Springer, 2026, pp. 55–65, doi: 10.1007/978-3-032-29494-4_6.
C. Chen, S. Liang, R. Guan, X. Sun, H. Zhao, H. Jiang, T. Huang, H. Ding, and Q.-L. Han, “AerialMind: Towards referring multi-object tracking in UAV scenarios,” in Proc. AAAI Conf. Artif. Intell., vol. 40, no. 4, pp. 2805–2813, 2026, doi: 10.1609/aaai.v40i4.37270. [ICORE2026 A*, Oral Presentation]
X. Zhang, X. Zhou, Y. Ren, and T. Huang, “Priority-driven instant delivery system with drone resupply,” in Proc. 2025 IEEE Int. Conf. Syst., Man, Cybern. (SMC), Vienna, Austria, Oct. 5–8, 2025, pp. 297–302, doi: 10.1109/SMC58881.2025.11342507.
J. Chen, L. Shi, N. Cheng, X. Zhou, Y. Shao, and T. Huang, “Decentralized cooperative caching for Web3.0: Framework design and latency optimization,” in Proc. 2025 IEEE/CIC Int. Conf. Commun. China (ICCC), Shanghai, China, Aug. 10–13, 2025, doi: 10.1109/ICCC65529.2025.11148724.
Q. Liu, T. Huang, Y. Dong, and W. Xiang, “Cross-modality learning privileged information for multimodal data,” in Proc. 2025 IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), Brisbane, Australia, Aug. 3–8, 2025, pp. 7589–7592, doi: 10.1109/IGARSS55030.2025.11242315.
Abdullah, T. Huang, I. Lee, and E. Ahn, “High-resolution histopathology whole slide image generation using wavelet diffusion model,” in Proc. 2025 IEEE 22nd Int. Symp. Biomed. Imaging (ISBI), Houston, TX, USA, May 14–17, 2025, doi: 10.1109/ISBI60581.2025.10981258.
J. Li, C. Lin, H. Wang, Y. Zhi, J. Chen, and T. Huang, “Adversarial training and cross-modal feature fusion in multimodal sentiment analysis,” in Proc. 2025 IEEE Int. Conf. Acoust., Speech Signal Process. (ICASSP), Hyderabad, India, Apr. 6–11, 2025, pp. 1–5, doi: 10.1109/ICASSP49660.2025.10890023.
G. Ding, J. Liu, Y. Xia, T. Huang, B. Zhu, and J. Sun, “LiDAR point cloud-based multiple vehicle tracking with probabilistic measurement-region association,” in Proc. 27th Int. Conf. Inf. Fusion (FUSION), Venice, Italy, 2024, pp. 1–8, doi: 10.23919/FUSION59988.2024.10706503.
J. Liu, G. Ding, Y. Xia, J. Sun, T. Huang, L. Xie, and B. Zhu, “Which framework is suitable for online 3D multi-object tracking for autonomous driving with automotive 4D imaging radar?” in Proc. 2024 IEEE Intell. Veh. Symp. (IV), Jeju Island, Republic of Korea, Jun. 2–5, 2024, pp. 1258–1265, doi: 10.1109/IV55156.2024.10588837. [Oral presentation, Top 5%]
K. Wen, Z. Guo, T. Huang, and F. Guo, “Domain knowledge-enhanced contrastive learning for industry classification of enterprises,” in Proc. 2024 IEEE 4th Int. Conf. Softw. Eng. Artif. Intell. (SEAI), Xiamen, China, Jun. 21–23, 2024, pp. 210–214, doi: 10.1109/SEAI62072.2024.10674144.
H. Li, Q. Liu, J. Liu, X. Liu, Y. Dong, T. Huang, and Z. Lv, “Unpaired MRI super resolution with contrastive learning,” in Proc. 2024 IEEE Int. Symp. Biomed. Imaging (ISBI), Athens, Greece, May 27–30, 2024, pp. 1–5, doi: 10.1109/ISBI56570.2024.10635265.
R. Bhope, K. Talele, and T. Huang, “Adaptive ambiance mode for noise cancelling headphones,” in Proc. 2023 IEEE Industrial Electronics and Applications Conference (IEACon), Penang, Malaysia, Nov. 6–7, 2023, pp. 231–236, doi: 10.1109/IEACon57683.2023.10370069.
L. Gardner, D. Phelps, J. Koci, T. Huang, B. Jarihani, P. Nelson, and G. Penton, “Rapid assessment of Mitchell Grass on Southern Gulf rangelands using drone imagery and machine learning,” presented at the 22nd Australian Rangeland Society Biennial Conference, Broome, WA, Australia, Sep. 18–22, 2023. [Oral Presentation only - Best Early Career Presentation - L. Gardner, who was an honours thesis student.]
K. Liu, T. Huang, and Z. Guo, “Classification of pathological images of skin diseases based on deep learning,” in Proc. 4th Int. Conf. Data-Driven Optimization of Complex Systems (DOCS), Chengdu, China, Oct. 28–30, 2022, pp. 489–494, doi: 10.1109/DOCS55193.2022.9967728.
W. Xiong, J. Liu, Y. Xia, T. Huang, B. Zhu, and W. Xiang, “Contrastive learning for automotive mmWave radar detection points based instance segmentation,” in Proc. 2022 IEEE 25th Int. Conf. Intell. Transp. Syst. (ITSC), Macau, China, Oct. 8–12, 2022, pp. 1255–1261, doi: 10.1109/ITSC55140.2022.9922540.
R. Abbas, M. Shirvanimoghaddam, T. Huang, Y. Li, and B. Vucetic, “Performance analysis of short analog fountain codes,” in Proc. 2019 IEEE Globecom Workshops (GC Wkshps), Waikoloa, HI, USA, Dec. 9–13, 2019, pp. 1–6, doi: 10.1109/GCWkshps45667.2019.9024699.
T. Huang, J. Yuan, X. Cheng, and W. Lei, “Design of degrees of distribution of LDS-OFDM,” in Proc. 9th Int. Conf. Signal Process. Commun. Syst. (ICSPCS), Cairns, QLD, Australia, Dec. 14–16, 2015, pp. 1–6, doi: 10.1109/ICSPCS.2015.7391767.
T. Huang, J. Yuan, X. Cheng, and W. Lei, “Advanced link-to-system modeling of MMSE-SIC receiver in MIMO-OFDM systems,” in Proc. 9th Int. Conf. Signal Process. Commun. Syst. (ICSPCS), Cairns, QLD, Australia, Dec. 14–16, 2015, pp. 1–6, doi: 10.1109/ICSPCS.2015.7391768.
T. Huang, X. Yuan, and J. Yuan, “Degrees of freedom of half-duplex MIMO multi-way relay channel with full data exchange,” in Proc. 2014 IEEE Global Commun. Conf. (GLOBECOM), Austin, TX, USA, Dec. 8–12, 2014, pp. 4336–4341, doi: 10.1109/GLOCOM.2014.7037489.
T. Huang, J. Yuan, and Q. T. Sun, “Opportunistic pair-wise compute-and-forward in multi-way relay channels,” in Proc. 2013 IEEE Int. Conf. Commun. (ICC), Budapest, Hungary, Jun. 9–13, 2013, pp. 4614–4619, doi: 10.1109/ICC.2013.6655298.
Y. Ma, T. Huang, J. Li, J. Yuan, Z. Lin, and B. Vucetic, “Novel nested convolutional lattice codes for multi-way relaying systems over fading channels,” in Proc. 2013 IEEE Wireless Commun. Netw. Conf. (WCNC), Shanghai, China, Apr. 7–10, 2013, pp. 2671–2676, doi: 10.1109/WCNC.2013.6554983.
T. Huang, J. Yuan, and J. Li, “Analysis of compute-and-forward with QPSK in two-way relay fading channels,” in Proc. 2013 Australian Commun. Theory Workshop (AusCTW), Adelaide, SA, Australia, Jan. 29–Feb. 1, 2013, pp. 75–80, doi: 10.1109/AusCTW.2013.6510048.
T. Huang, T. Yang, J. Yuan, and I. Land, “Convergence analysis for channel-coded physical layer network coding in Gaussian two-way relay channels,” in Proc. 8th Int. Symp. Wireless Commun. Syst. (ISWCS), Aachen, Germany, Nov. 6–9, 2011, pp. 849–853, doi: 10.1109/ISWCS.2011.6125282.
T. Yang, I. Land, T. Huang, J. Yuan, and Z. Chen, “Distance properties and performance of physical layer network coding with binary linear codes for Gaussian two-way relay channels,” in Proc. 2011 IEEE Int. Symp. Inf. Theory (ISIT), St. Petersburg, Russia, Jul. 31–Aug. 5, 2011, pp. 2070–2074, doi: 10.1109/ISIT.2011.6033920.
G. Wang, W. Xiang, J. Yuan, and T. Huang, “Outage performance of analog network coding in generalized two-way multi-hop networks,” in Proc. 2011 IEEE Wireless Commun. Netw. Conf. (WCNC), Cancun, Mexico, Mar. 28–31, 2011, pp. 1988–1993, doi: 10.1109/WCNC.2011.5779434.
T. Huang, B. Guo, and M. Trinkle, “FPGA implementation of GPS carrier and code tracking loops,” in Proc. Int. Global Navigation Satellite Systems Society Symp. (IGNSS), Sydney, Australia, Dec. 4–6, 2007, pp. 1–11.
R. Talkhani, T. Huang, S. Gu, Z. Guo, G. Zhang, and W. Xiang, “Deep learning for vehicle safety,” in Deep Learning and Its Applications for Vehicle Networks, F. Hu and I. Rasheed, Eds. Boca Raton, FL, USA: CRC Press, 2023, pp. 3–16, doi: 10.1201/9781003190691-2. [R. Talkhani was a Master of Engineering (Professional) Student when working on this book chapter.]
T. Huang, S. Yan, G. Zhang, T. H. Yuen, Y. Park, C. Lee, and J. Jusak, Eds., Security and Privacy for Modern Wireless Communication Systems, 2nd ed. Basel, Switzerland: MDPI, 2025, 264 pp., doi: 10.3390/books978-3-7258-4758-7.
T. Huang, S. Yan, G. Zhang, L. Sun, T. H. Yuen, Y. Park, and C. Lee, Eds., Security and Privacy for Modern Wireless Communication Systems. Basel, Switzerland: MDPI, 2023, 308 pp., doi: 10.3390/books978-3-0365-8229-0.
X. Zhang, G. Liu, M. Qiu, W. Xiang, and T. Huang, Eds., Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications: 9th EAI International Conference, CloudComp 2019, and 4th EAI International Conference, SmartGIFT 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Cham, Switzerland: Springer, 2020, doi: 10.1007/978-3-030-48513-9.
Satellite images and road-reference data for AI-based road mapping in Equatorial Asia [Dataset]
Sean Sloan, Raiyan R. Tallhano, Tao Huang, Jayden Engert, and William Laurance
If using this dataset, please cite the paper: Sean Sloan, Raiyan R. Talkhani, Tao Huang, Jayden Engert, William F. Laurance, "Mapping Remote Roads Using Artificial Intelligence and Satellite Imagery," Remote Sens., vol. 16, no. 5, Art. no. 839, Mar. 2024, doi: 10.3390/rs16050839.
J. Yuan, Y. Zhao, T. Huang, and X. Cheng, “Method, apparatus and receiver for computing signal-to-interference-and-noise ratio,” PCT Patent Publication WO2017049633A1, Huawei Technologies Co., Ltd., 30 Mar. 2017. Chinese patent family member: CN107534530B, 17 Jul. 2020.
Z. Cao, D. Tian, R. Guan, Y. Mu, X. Sun, S. Liang, D. Liu, T. Huang, Y. Yue, H. Ding, B. Fang, A. Zhou, Q.-L. Han, and H. Xiong, “Tactile-based multimodal fusion in embodied intelligence: A survey of vision, language, and contact-driven paradigms,” arXiv preprint arXiv:2605.17336, 2026.
R. Guan, S. Liang, N. Ouyang, W. Fei, S. Yao, W. Dai, C. Ge, P. Sun, X. Zhu, T. Huang, R. W. Liu, and H. Xiong, “WaterVideoQA: ASV-centric perception and rule-compliant reasoning via multi-modal agents,” arXiv preprint arXiv:2602.22923, 2026.
H. Ma, Y. Yang, S. Guo, T. Huang, Y. Li, S. Cóbreces Álvarez, and Z. Pang, “Quantifying thermal coupling effects in multi-chip power modules: An efficient Fourier series-based approach,” SSRN, 2025, doi: 10.2139/ssrn.5194267.
R. Guan, J. Liu, S. Liang, F. Ding, S. Yao, X. Bai, D. Liu, T. Huang, G. Mao, and H. Xiong, “Wavelet-based multi-view fusion of 4D radar tensor and camera for robust 3D object detection,” arXiv preprint arXiv:2512.22972, 2025.
Z. Liu, Y. Du, X. Chen, X. Li, T. Huang, and K. Yan, “Determine PV-battery dynamic firm capacity using deep reinforcement learning,” SSRN, 2026, doi: 10.2139/ssrn.6913457.
Y. Yang, J. Liu, G. Luo, H. Li, E. Ahn, M. Rahimi Azghadi, and T. Huang, “Unsupervised radar point cloud enhancement via arbitrary LiDAR guided diffusion prior,” arXiv preprint arXiv:2505.09887, 2025.
Abdullah, T. Huang, I. Lee, and E. Ahn, “Computationally efficient diffusion models in medical imaging: A comprehensive review,” arXiv preprint arXiv:2505.07866, 2025.
T. Meng, C. Fu, X. Yan, Z. Liang, P. Ji, J. Wang, and T. Huang, “Deep LG-Track: An enhanced localization-confidence-guided multi-object tracker,” arXiv preprint arXiv:2504.01457, 2025.
H. Li, Y. Zhou, J. Liu, X. Liu, T. Huang, Z. Lyu, W. Cai, and W. Chen, “Efficient MRI parallel imaging reconstruction by K-space rendering via generalized implicit neural representation,” arXiv preprint arXiv:2309.06067, 2023.
R. Abbas, T. Huang, B. Shahab, M. Shirvanimoghaddam, Y. Li, and B. Vucetic, “Grant-free non-orthogonal multiple access: A key enabler for 6G-IoT,” arXiv preprint arXiv:2003.10257, 2020.
2026 — Project Talk, “Remote Saltwater Crocodile Water-Surface Detection Using Digital Video AI,” Marine Creature Symposium, Cairns, Australia, 18 May 2026.
2025 — Technical Talk, “V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges,” 22nd Australian Communications Theory Workshop (AusCTW 2025).
2024 — Invited Talk, “How to Start and Improve Academic Writing,” Xi’an University of Technology, Xi’an, China, 14 June 2024.
2023 — Invited Technical Talk, “Deep Learning-Aided TW-UWB MIMO Systems,” 20th Australian Communications Theory Workshop (AusCTW 2023).
2022 — Seminar, “Interested in Adopting AI in Your Domain Research but Lacking Labeled Data? An Introduction to Contrastive Learning,” JCU TESS Seminar Series.
2020 — Technical Talk, “Automating STIV Measurements,” NZHS Technical Workshop: The Future of Surface Velocity Measurement, Tauranga, New Zealand.
2019 — Technical Talk, “Application of Low-Cost Real-Time Computer Vision Learning-Based Water Discharge Sensing System,” STIV Data Processing Training Workshop, Queensland Government, Cairns, Australia.
2019 — Technical Talk, “Real-Time Water Quality Monitoring at Saltwater Creek and Low-Cost Real-Time Computer Vision Learning-Based Water Discharge Sensing System,” Towards a Real-Time Water Quality Monitoring Community of Practice Workshop, CSIRO, Cairns, Australia.