Ziyu Zhou 周子渔

I am an MPhil student of the CityMind Lab, @HKUST(GZ), under the supervision of Prof. Yuxuan Liang. Previously, I completed my undergraduate degree in Computer Science and Technology at the Beijing University of Technology, where I conducted my research under the guidance of Prof. Gengyu Lyu at the DMS Lab.

During my undergraduate studies, I had the privilege of collaborating with Yiming Huang @HKUST(GZ) and Zihao Wang @HKUST. I aspire to build deep and enduring collaborations with fellow researchers in the future.

My research interests are structured around two principal domains:

  1. Self-Supervised Learning for Time Series:
    • Generative-based Methods: Focusing on diffusion-based generation.
    • Adversarial Attacks and Robust Analysis: Examining the security and reliability of models.
    • Advanced Pretraining Techniques: Utilizing data scaling laws and data distillation to enhance model training.
  2. Multi-Modality Deep Learning:
    • Explainability of Transformer-based models: Improving understanding of how models interpret and process text and image information.
    • Application of Vision-Language Models on Streaming Data: Exploring the use of these models on dynamic inputs such as video.

These areas collectively aim to deepen our understanding of self-supervised learning of time series and enhance interpretability in multi-modal deep learning, pushing the boundaries of what these technologies can achieve.

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My Quote

"The purpose of computing is insight, not numbers." —— Richard Wesley Hamming

News

News
2024/09/02 A new life at HKUST(GZ) has begun! Feel free to say hi if we cross paths on campus!
2024/06/29 I was awarded as Outstanding Graduate Thesis and Outstanding Graduates of Beijing.
2024/04/17 One paper about time series forecasting was accepted by IJCAI'24.
2023/12/01 I decided to accept the MPhil offer from HKUST(GZ) Fok Ying Tung Graduate School.
2023/10/26 One paper about PM2.5 forecasting was accepted by Atmosphere.
2023/08/25 One paper about ASD detection was accepted by PRICAI'23.
2023/03/24 I achieved a satisfactory academic IELTS band score of 7.5 (8,8,6.5,6.5).

Research Programs & Publication

(* denotes corresponding author and ^ indicates equal contribution.)
SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting
Ziyu Zhou, Gengyu Lyu*, Yiming Huang, Zihao Wang, Ziyu Jia, Zhen Yang
The 33rd International Joint Conference on Artificial Intelligence (IJCAI '24, CCF-A & CORE-A*)
The Only Long Oral Paper of the Time Series Session (1/12)

Paper Link / PDF / Code / Poster

We propose a novel Transformer architecture (named SDformer) for long-term time series forecasting. It is the first time to address the problem of smooth attention distribution when modeling time series data with a large number of variates.

TimesNet-PM2.5: Interpretable TimesNet for Disentangling Intraperiod and Interperiod Variations in PM2.5 Prediction
Yiming Huang^, Ziyu Zhou^, Zihao Wang^, Xiaoying Zhi, Xiliang Liu*
Atmosphere (JCR-Q3)
Paper Link

In this paper, we accomplish task-specific adaption of TimesNet (ICLR '23) named TimesNet-PM2.5. This specialized version improved the performance and interpretability of the PM2.5 prediction of Haikou, Hainan Province.

STFM: Enhancing Autism Spectrum Disorder Classification Through Ensemble Learning-Based Fusion of Temporal and Spatial fMRI Patterns
Ziyu Zhou^, Yiming Huang^, Yining Wang^, Yin Liang*
The 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI '23, CCF-C & CORE-B)
Paper Link / PDF

We propose a Spatial and Temporal framework named STFM based on cross-attention for better autism spectrum disorder classification. The results show that STFM's classification accuracy surpassed that of many machine learning models.

CoC-GAN: Employing Context Cluster for Unveiling a New Pathway in Image Generation
Zihao Wang^, Yiming Huang^, Ziyu Zhou^
Arxiv(2023) 2308.11857
arXiv

We employ Context-Clustering Block (ICLR '23) into GAN for better interpretability.

Education Background

Hong Kong University of Science and Technology(GZ)

MPhil in Data Science and Analytics

2024.09 - 2026.06(expected), Guangzhou, Nansha

Bejing University of Technology

BEng in Computer Science and Technology with Honours Degrees

Outstanding Graduate Thesis 北京市优秀毕业设计(论文)(Top 0.7%)

Outstanding Graduates 北京市优秀毕业生(Top 11%)

2020.09 - 2024.07, Beijing, Chaoyang

Beijing No.4 High School

High School Graduate

2017.09 - 2020.07, Beijing, Xicheng