🏷 About Me

I am currently pursuing a master’s degree at the School of Mathematics and Statistics, Hainan University, supervised by Prof. Teng Zhou . GPA: 3.96/4.00, ranked 1st among all students in the major. I received my bachelor’s degree from the College of Flexible Electronics, Shaanxi University of Science and Technology. Our team includes PhD students and postdoctoral researchers such as Prof. Youyi Song, Dr. Zhizhe Lin, Postdoc. Farooq Ahmed, and Postdoc. Shahid Ali, who are actively contributing to their respective research areas.

My research interest includes Spatiotemporal Data Mining, Time Series Analysis, Machine Learning, Intelligent Transportation System and Traffic Flow Forecasting.

🔥 News

• 2025.09: 🎉I am honored to be awarded the Graduate National Scholarship (Top 1).
• 2025.05: 🎉I release a personal homepage template specifically designed for academic researchers. Welcome to STAR and FORK!
• 2024.11: 🎉Our team won the National Second Prize in the 21st Huawei Cup China Postgraduate Mathematical Modeling Competition.
• 2024.10: I join ByteDance × Doubao MarsCode AI Youth Training Camp as an intern!

✨ Funding

• Zhikong Aerial Inspection — An AI-powered UAV Road Inspection Service Provider, Scientific and Technological Innovation Project under the Postgraduate Science and Technology Festival of Hainan University, NO. SA2400003062, Principal Investigator, 7,000 RMB, 2024.09-2024.11
• Full-Time Domain Traffic Resilience Prediction System: An Innovative Algorithm Integrating Traffic Flow and Meteorological Data, National Undergraduate Innovation and Entrepreneurship Training Program, NO. 202410589037, Co-Investigator, 90,000 RMB, 2024.07-2025.07
• Research on Key Technologies for Traffic Flow Prediction Based on Deep Learning, Postgraduate Innovative Scientific Research Project of Hainan Province, NO. Qhys2023-127, Co-Investigator, 1,000 RMB, 2024.01-2025.10

📝 Publications

• IEEE TCE Chaozhi Yu, Zhizhe Lin, Hongnan Cheng, Chunjie Cao, Teng Zhou, Man-Fai Leung. Quantum-Inspired Dynamic Spatiotemporal Matching Transformer for Traffic Flow Forecasting. IEEE Transactions on Consumer Electronics. 2025. https://doi.org/10.1109/TCE.2025.3642339. [SCI Q1, 中科院一区Top, IF 10.9] \cite{yu2025quantum}

• IEEE SPL Chaozhi Yu, Hongnan Cheng, Yufei Huang, Zhizhe Lin, Teng Zhou. Multi-Scale Cross-Dimensional Attention Network for Gland Segmentation. IEEE Signal Processing Letters. 2025. https://doi.org/10.1109/LSP.2025.3600374. [SCI Q2, 中科院三区, IF 3.9] \cite{yu2025multi}

• IJCTA Hongnan Cheng, Chaozhi Yu, Chenguang Zhang. Segmentation of IC Images in Integrated Circuit Reverse Engineering Using EfficientNet Encoder Based on U-Net++ Architecture. International Journal of Circuit Theory and Applications. 2025. https://doi.org/10.1002/cta.4485. [SCI Q3, 中科院三区, IF 1.6] \cite{cheng2025segmentation}

• ACM EITCE 2025 Yudi Xu^†, Chaozhi Yu^†,*, Hongnan Cheng, Yulai Wu. Enhancing Stock Price Prediction with GLTCN: A Hybrid Model for Complex Market Dynamics. Proceedings of the 9th International Conference on Electronic Information Technology and Computer Engineering. 2025. https://doi.org/10.1145/3766671.3766792. \cite{xu2025enhancing}

• IEEE CAIBDA 2025 Hongnan Cheng, Chaozhi Yu, Zhiyuan Yang, Chenguang Zhang. A Denoising and Structured Segmentation Method for IC Images via Integration of YOLOv5 and Lightweight Unet. 2025 5th International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA). 2025. https://doi.org/10.1109/CAIBDA65784.2025.11183565. \cite{cheng2025denoising}

🎖 Honors and Awards

• 2025.06 Role Model of Yefeng College Hainan University
• 2024.12 The Second Prize in the 21st Huawei Cup China Postgraduate Mathematical Modeling Competition
• 2024.11 Approval of the National College Student Innovation and Entrepreneurship Training Program Project
• 2024.10 The Gold Award of the China International College Students’ Innovation and Entrepreneurship Competition (Hainan Region)
• 2024.10 Approval of the Graduate Student Science and Technology Festival Innovation Project of Hainan University
• 2024.10 Best Scientific Innovation Project, First Graduate Student Science and Technology Festival, Hainan University
• 2024.07 The Third Prize in the 10th National College Students’ Statistical Modeling Competition (Guangdong Region)
• 2024.06 Bronze Award, 14th “Challenge Cup” China College Students’ Entrepreneurship Competition
• 2023.12 Approval of Hainan Province’s Postgraduate Innovative Scientific Research Project
• 2023.01 The First Prize in the 14th National Undergraduate Mathematics Competition
• 2022.12 The Second Prize in the 5th Hua Jiao Cup National College Student Mathematics Competition
• 2022.06 The First Prize in the 16th College Students Higher Mathematics Competition, Shaanxi University of Science and Technology
• 2022.06 The Silver Medal in the First National College Student Olympiad Mathematics Competition
• 2022.06 The Second Prize in the 3rd National College Mathematics Competence Challenge

📖 Educations

• 2023.09 - 2026.06 (now), Master, School of Mathematics and Statistics, Hainan University, Haikou.
• 2019.09 - 2023.06, Undergraduate, College of Flexible Electronics, Shaanxi University of Science and Technology, Xi’an.

📊 Skills

• Proficient in mainstream time series forecasting algorithms, including Moving Average, Exponential Smoothing, XGBoost, ARIMA, Random Forest, VAR, GARCH, Prophet, and MTS-Mixers.
• Skilled in regression forecasting algorithms such as Ordinary Least Squares Linear Regression, Lasso Regression, Ridge Regression, SGD Regression, ElasticNet, LAR, OMP, Bayesian ARD Regression, Bayesian Ridge Regression, GLM, LightGBM, CatBoost, and DeepForest.
• Well-versed in machine learning algorithms including Logistic Regression, K-Nearest Neighbors (KNN), ensemble methods, Support Vector Machines (SVM), K-means clustering, Naive Bayes, Hidden Markov Models (HMM), and Conditional Random Fields (CRF); proficient in implementing these algorithms using the scikit-learn library.
• Proficient in deep learning frameworks and architectures such as RNN, LSTM, GRU, Seq2Seq, Attention, Transformer, and BERT.
• Familiar with classical CNN architectures including LeNet, LeNet-5, AlexNet, GoogLeNet, VGG-16, and ResNet.
• Experienced in Python development; proficient with scientific libraries such as NumPy, Pandas, and Matplotlib, as well as deep learning frameworks including PyTorch and TensorFlow.
• Knowledgeable in feature engineering, including data cleaning, feature extraction, feature selection, dimensionality reduction, and model evaluation.
• Familiar with Linux command-line operations and experienced in deploying projects in a Linux environment.