Publications

Zhao, R, Wei, M, Shen, S, Wang, X, Prasad, M & Huo, H 2026, 'Efficient Conditional Diffusion Model for Accurate Pedestrian Trajectory Prediction' in Communications in Computer and Information Science, Springer Nature Singapore, pp. 137-152.
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Chen, J, Wu, M, Liu, Q & Zhang, Y 2026, 'Explainable prediction of knowledge recombination: A synergized method with heterogeneous hypergraph learning and large language models', Information Processing & Management, vol. 63, no. 1, pp. 104336-104336.
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Qi, L, Wang, S, Sheng, VS & Yao, L 2026, 'Introduction to the Special Issue on Deep Reinforcement Learning for Recommender Systems', ACM Transactions on Recommender Systems, vol. 4, no. 1, pp. 1-4.
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Deep Reinforcement Learning (DRL) has garnered significant attention as a promising approach for developing intelligent and adaptive recommender systems. This paradigm is especially well-suited for recommendation scenarios characterized by dynamic user environments, temporally delayed feedback signals, and continuously shifting user preferences. However, deploying DRL within recommendation scenarios introduces a range of intricate challenges. These include the design of meaningful and task-aligned reward functions, effective navigation of vast and complex action spaces, and the need to maintain sample efficiency in data-sparse environments. Ensuring robust and stable training dynamics adds further difficulty. This special issue brings together a diverse collection of cutting-edge research that addresses these pressing challenges, showcasing advances that move the field toward more adaptive, robust, and personalized recommendation systems grounded in reinforcement learning.

Reza, MS, Fattah, IMR, Wang, J, Hannan, MA, Zainal, BS, Ong, HC & Mahlia, TMI 2026, 'Hydrogen-based hybrid energy system: A review of technologies, optimization approaches, objectives, constraints, applications, and outstanding issues', Renewable and Sustainable Energy Reviews, vol. 226, pp. 116192-116192.
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Wang, Z, Wang, Q, Yu, G & Chen, S 2026, 'TDML — A Trustworthy Distributed Machine Learning Framework', Future Generation Computer Systems, vol. 174, pp. 107951-107951.
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Yu, E, Lu, J, Zhang, K & Zhang, G 2026, 'Enhancing outdoor vision: Binocular desnowing with dual-stream temporal transformer', Pattern Recognition, vol. 170, pp. 112075-112075.
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Zhou, Y, Xie, Y, Qi, J, Hu, J, Yang, Y, Deng, F, Zhu, Y, Deng, W, Mei, L, Goldys, EM, Zhang, J, Xu, C & Chen, W 2026, 'A leucine derivate-adjuvanted LNP vaccine enhances antitumor immunity through mTOR activation and metabolic reprograming in dendritic cells', Biomaterials, vol. 325, pp. 123539-123539.
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