Zhuo Huang (黄卓)
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Postdoctor, |
About me
I received my Ph.D. degree (advised by Prof. Song Wu) from Huazhong University of Science and Technology (HUST) in 2023 and was a visiting Ph.D. student (advised by Prof. Song Jiang) at the University of Texas at Arlington (UTA) during 2018-2019.
I am currently a research scientist with the AI Research Institute, Hithink RoyalFlush, China, and a researcher with the School of Smart Education, Jiangsu Normal University, China.
I focus on using AI to solve practical problems. My main research interests include Large Language Model of NLP and Recommendation Systems. Also, I do some research of CV, such as medical image.
Research
My research interests include:
Container Image Building
Cloud-native Sandboxes
Serverless Computing
Current work
RecLLM: Large Language Model for Explainable Recommendation
Large Language Model for Generation of Medical Image Diagnostic Reports
BAT: Battery Assessment Transformer based Large Language Models for Remaining Useful Life Prediction
Layer-wise Contrastive Learning BERT for Sentence Representation
Semi-supervised for for Recommendation
Under review
Y. Lin, W. Zhang, X. Zhou, F. Lin*, W. Zeng, L. Zou*, Y. Liu, P. Wu, "Knowledge-aware Reasoning with Self-supervised Reinforcement Learning for Explainable Recommendation in MOOCs".
M. Chen, T. Ma, and X. Zhou*, "CoGraph: Co-occurrence Graph for Recommendation".
M. Chen, T. Ma, and X. Zhou*, "GraphAE: Graph AutoEncoders for Drug-Target Interaction Prediction".
Recent publications
Y. Ding, S. Jia, T. Ma*, B. Mao, X. Zhou, L. Liu, D. Han, and M. Chen, "Integrating Stock Features and Global Information via Large Language Models for Enhanced Stock Return Prediction", In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI-23), Aug. 2023.
W. Zhang, Y. Lin, Y. Liu, P. Wu, F. Lin*, and X. Zhou*, "Self-Supervised Reinforcement Learning with Dual-reward for Knowledge-aware Recommendation", Applied Soft Computing, Oct. 2022. (IF = 8.263) [pdf][code]
M. Chen, T. Ma, and X. Zhou*, "CoCNN: Co-occurrence CNN for Recommendation", Expert Systems with Applications, Jun. 2022, 195, pp. 116595. (IF = 8.665) [pdf][code]
M. Chen, Y. Li, X. Zhou*, "CoNet: Co-occurrence Neural Networks for Recommendation", Future Generation Computer Systems, Nov. 2021, 124, pp. 308-314. (IF = 7.307) [pdf][code]
M. Chen, X. Zhou*, "DeepRank: Learning to Rank with Neural Networks for Recommendation", Knowledge-Based Systems, Dec. 2020, 209, pp. 106478. (IF = 8.139) [pdf][code]
D. Chen, W. Hong, and X. Zhou*, "Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries", IEEE Access, 2022, 10, pp. 19621-19628. (IF = 3.367) [pdf][code]
X. Wu, W. Zeng, F. Lin*, and X. Zhou, "NeuRank: Learning to Ranking with Neural Networks for Drug-Target Interaction Prediction", BMC Bioinformatics, Nov. 2021, 22, pp. 567. (IF = 3.328) [pdf][code]
X. Zhou* and S. Wu, "Rating LDA Model for Collaborative Filtering", Knowledge-Based Systems, Oct. 2016, 110, pp. 135-143. (IF = 8.139) [pdf]
K. Li, X. Zhou, F. Lin*, W. Zeng, B. Wang, and G. Alterovitz, "Sparse Online Collaborative Filtering with Dynamic Regularization", Information Sciences, Dec. 2019, 505, pp. 535-548. (IF = 8.233) [pdf]
X. Zhou, W. Shu, F. Lin*, and B. Wang, "Confidence-Weighted Bias Model for Online Collaborative Filtering", Applied Soft Computing, Sep. 2018, 70, pp. 1042-1053. (IF = 8.263)
K. Li, X. Zhou, F. Lin*, W. Zeng, and G. Alterovitz, "Deep Probabilistic Matrix Factorization Framework for Online Collaborative Filtering", IEEE Access, Mar. 2019, 7, pp. 56117-56128. (IF = 3.367)
F. Lin, X. Zhou, and W. Zeng*, "Sparse Online Learning for Collaborative Filtering", International Journal of Computers Communications & Control, Apr. 2016, 11 (2), pp. 248-258. (IF = 2.093)
S. Lu, H. Chen, X. Zhou, B. Wang, H. Wang*, and Q. Hong, "Graph-Based Collaborative Filtering with MLP", Mathematical Problems in Engineering, Dec. 2018, 2018, pp. 1-10. (IF = 1.305)
X. Zhou, F. Lin*, L. Yang, J. Nie, Q. Tan, W. Zeng, and N. Zhang, "Load Balancing Prediction Method of Cloud Storage based on Analytic Hierarchy Process and Hybrid Hierarchical Genetic Algorithm", SpringerPlus, Nov. 2016, 5 (1), pp. 1989-2012. (IF = 1.780)
X. Zhou*, and S. Wu, "The Biterm Author Topic in the Sentences Model for E-Mail Analysis", IEICE Transactions on Information and Systems, Aug. 2017, E100.D (8), pp. 1852-1859. (IF = 0.449)
Note: * indicates the corresponding author.
Academic service
Reviewer
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Industrial Informatics
ACM Transactions on Knowledge Discovery from Data
IEEE Access
Projects
Advertising Platform Development, 01.2022-Present
Provide advertising strategies and solutions for advertisers to maximize revenue
Provide automated advertising instead of manual selection
Use users' history information to build their profiles, and then select the target users
Campus Recommender System, 03.2021-12.2021
Built user profiles based on the data crawled from websites
Recommended information, such as courses from MOOC, and publications from Arxiv, to students
Recommended information from within and outside the university based on faculty research, courses taught, and interests
Online Education Explainable Recommender System, NSFC, 06.2018-12.2018
Summarized over 500,000 exercises and classified their knowledge points from all subjects
Applied matrix factorization for online learning and recommendation of exercises based on interaction of users
Added latent features learned by neural networks from exercises to online matrix factorization for better performance
Education
M.E., Pattern Recognition and Intelligent Systems, Xiamen University, 06.2016
Awards: Principal Level Scholarship (1st in admission)
Main Courses: Machine Learning, Design of Neural Networks, Digital Image Processing, Time Series Analysis, Pattern Recognition, Data Mining and Its Application, Artificial Intelligent: Theory and Application, Recommender System.
B.E., Automation, Zhejiang University of Science and Technology, 06.2012
Main Courses: C Programming, Embedded Systems, Computer Network and Communication, Computer Control System.
Work experience
Research Scientist, AI Research Institute, Hithink RoyalFlush, 06.2019-Present
Research the newest machine learning algorithms and recommender system technology on stocks and hot news
Apply neural network models to drug-target interaction prediction and evaluate the performance
Publish papers and apply for relevant patents for the corporation
Give lessons on Artificial Intelligence and Recommender Systems to the staff
Research Assistant, Big Data Lab, Xiamen University, 09.2016-02.2019
Instructed two undergraduate and three graduate students in scientific research
Tracked, studied, reproduced, and improved up-to-date machine learning methods
Published papers on machine learning and recommender systems
Software Engineer, Dragon SOFT, 07.2013-06.2014
Developed an electronic target practice system for security guards’ shooting training
Recorded the track of users' shooting behavior from sensors in a database
Built a model analyzing users’ shooting behavior concerning speed, acceleration and number of cylinders
Assistant Engineer, Gold Electronic, 03.2012-07.2012
Cooperated with motor companies, such as Zotye and BYD, on battery management system development
Developed a testing and analytics platform for performance of a lithium battery with C# (real-time data)
Used CAN bus to collect working data of batteries and analyzed the data for balance power