Zhu, Fangyuan (朱方圆)
关于我
***************************************
Research
My research interests include:
Machine Learning
Deep Learning
Recommender Systems
Computer Vision
Current work
Reinforcement Learning for Knee Osteoarthritis Prediction
Temporal Neural Network for Knee Osteoarthritis Prediction
Expert Neural Network for for Recommendation
Federal Learning for Recommendation
Under review
W. Zhang, Y. Lin, Y. Liu, P. Wu, F. Lin*, and X. Zhou*, "Self-Supervised Reinforcement Learning for Knowledge-aware Recommendation".
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, and X. Zhou*, "Autoencoders for Drug-Target Interaction Prediction".
Recent publications
M. Chen, T. Ma, and X. Zhou*, "CoCNN: Co-occurrence CNN for Recommendation", Expert Systems with Applications, Jun. 2022, 195, pp. 116595. (IF = 6.954) [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 = 7.187) [pdf][code]
M. Chen, X. Zhou*, "DeepRank: Learning to Rank with Neural Networks for Recommendation", Knowledge-Based Systems, Dec. 2020, 209, pp. 106478. (IF = 8.038) [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 = 3.024) [pdf][code]
X. Zhou* and S. Wu, "Rating LDA Model for Collaborative Filtering", Knowledge-Based Systems, Oct. 2016, 110, pp. 135-143. (IF = 8.038) [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 = 6.795) [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 = 6.725)
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.
Full list of publications in Google Scholar.
Academic service
Reviewer
IEEE Transactions on Industrial Informatics
IEEE Access
ACM Transactions on Knowledge Discovery from Data
Mathematical Problems in Engineering
More details in Publons
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
Development of Memorizing Words APP, 06.2017-02.2018
Extracted the records of memorizing words of over 100,000 users from a database
Counted the pairs of error words with the co-occurrence rate to obtain a co-occurrence table
Provided words, along with situation pictures, to enhance memory and showed co-occurrence words from a table
Analysis of Film Review from Douban.com, 09.2016-03.2017
Crawled film reviews and ratings from websites
Segmented words and cleaned and processed texts
Added features learned by neural networks to matrix factorization to predict movie's ratings
Topics Analysis on Weibo, 05.2015-02.2016
Crawled Weibo messages from websites
Segmented words, cleaned and processed texts, converted the data for storage and analytics
Built a topic model LDA by C and applied it to obtain topics of Weibo for discovering hot events
Email-Based User Relationship Analysis, 10.2014-02.2015
Cleaned and processed the contents of over 100,000 emails to obtain message bodies
Built an author-topic model with biterm pattern by C
Used model to identify relationships between users based on communication contents
Smart Home System, 03.2011-02.2012
Designed and built a hardware system including PCB, sensors, and single-chip microcomputer
Developed a program of single-chip microcomputer with language C to realize the function of the system
Developed a human-computer interaction software with C# for signal reception, processing, and transmission
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.
Competitions and awards
First-Class Scholarship, Zhejiang University of Science and Technology, 10.2011
National Encouragement Scholarship, 12.2011 & 12.2010
The 2nd Prize in the National Advanced Mathematics Contest for Undergraduates (Zhejiang), 12.2011
The 2nd Prize in the Zhejiang Advanced Mathematics Contest for Undergraduates, 04.2011
The 3rd Prize in the Zhejiang Advanced Mathematics Contest for Undergraduates, 10.2009 & 04.2010
The 3rd Prize in the Zhejiang Physics Contest for Undergraduates, 12.2009 & 12.2010
The 1st Prize in the Electronics Design Contests, Zhejiang University of Science and Technology, 12.2010
Activities
Teaching Assistant, Xiamen University, 09.2013-01.2014
Assistant Mentor, Zhejiang University of Science and Technology, 09.2010-06.2011
Journalist, Press Corps of Zhejiang University of Science and Technology, 12.2008-06.2011
Founder and Editor in Chief, Say Ourselves, E-magazine, 12.2009-08.2011
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
A brief cv.
|