Sijie Xiong

Sijie Xiong

📖 My current research interests are: time series forecasting, medical image segmentation, control theory.

If you are seeking any potential academic collaboration, welcome to contact me by email:

📫: sijiexiongkyushu@gmail.com

📫: xiong.sijie.630@s.kyushu-u.ac.jp

I have been pursuing my Ph.D. degree at Kyushu University, Japan as of April 2024 following Prof. Atsushi Shimada (島田 敬士 シマダ アツシ ), and have a joint background in Control & Optimization, Control Theory, Mechanics, Finance, and Deep Learning.

I graduated from the Department of Electrical and Electronic Engineering at Imperial College London and obtained a Master degree in Control Systems with Distinction in 2021.

Prior to that, I received my Bachelor degree in Automation from the College of Energy and Electrical Engineering, Hohai University in 2020.

I also obtained an honor Bachelor degree in Applied Accounting from Oxford Brookes University jointly with ACCA.

Apart from degrees, I have been a member of the following associations on business:

I have published some small papers in excellent journals and conferences, such as ASOC, CAI, EMBC, SMC. You can find my publications on Google Scholar.

🔥 News

  • The show must go on.
  • 2025.09: 😭 Two papers are rejected by AAAI 2026 Phase 1.
  • 2025.10: 🎉 Attention Mamba will be presented in IEEE SMC 2025.
  • 2025.09: 🎉 FairytaleQA Chinese is accepted by APSCE ICLEA 2025 and online, winning The Best Poster Award.
  • 2025.08: 🎉 CME-Mamba is accepted by ASOC and online.
  • 2025.07: 🎉 GluTANN is accepted by CAI 2025 and online.

📝 Publications

🩸 Diabetes Glucose Monitoring

CAI 2025
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GluTANN: Transformer-Based Continuous Glucose Monitoring Model with ANN Attention
Sijie Xiong, Youhao Xu, Cheng Tang, Jianing Wang, Shuqing Liu, Atsushi Shimada

Project

  • Abstract: In this work, we propose an innovative model based on Transformer architecture, GluTANN, with specially designed ANNs acting as self-attentions and paired correlations preserved by the encoder-decoder structure. Extensive experiments across five recognized datasets demonstrate that GluTANN has great competitiveness in reducing uncertainty while preserving satisfying accuracy, providing a feasible approach to effective glucose management and diabetes medical decisions.
  • Core Idea: Reduce redundant tokens of Transformer-based models as much as we can.
  • Domain: Time Series Forecasting, Diabetes, Glucose Monitoring

🚥🚦 Control & Time Series Forecasting

ASOC
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Enhancing Nonlinear Dependencies of Mamba via Negative Feedback for Time Series Forecasting
Sijie Xiong, Cheng Tang, Yuanyuan Zhang, Haoling Xiong, Youhao Xu, Atsushi Shimada

Project

  • Abstract: In this work, we are inspired by the curvature from financial domains and control systems, proposing CME-Mamba. The effectiveness, stability, robustness, etc., are discussed. Extensive experiments demonstrate that CME-Mamba grows excellent to uncover complex paradigms and predict future states in various domains, especially improving the performance for periodic and high-variate situations.
  • Core Idea: Leverage negative feedback loop to enhance non-linearity for TSF models.
  • Domain: Time Series Forecasting, Control

🏫 Education

ICLEA 2025 (The Best Poster)
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Fine-tuned T5 Models on FairytaleQA Chinese Dataset
Sijie Xiong, Haoling Xiong, Tao Sun, Haiqiao Liu, Fumiya Okubo, Cheng Tang, Atsushi Shimada

Project

  • Abstract: Question Answering (QA) is very important for comprehension learning and FairytaleQA is widely employed in this domain. However, rare versions in a limited number of alphabet languages restricts its application and current translators have five fatal errors. In our study, we manually translate FairytaleQA into Chinese and test its effectiveness via five fine-tuned T5 models.
  • Core Idea: Extend current QA datasets on education for pre-trained models.
  • Domain: Question-Answering, Education, Pre-trained Models

Others

🏅 Honors and Awards

  • Sep. 2025 The Best Poster Award of 2025 International Conference on Learning Evidence and Analytics (ICLEA).

  • Oct. 2020 Honorary Title of Learning Model Student (2019-2020), Hohai University. (1st Student in the 4th Academic Year).

  • Oct. 2020 Academic Excellence Scholarship (2019-2020), Hohai University.

  • Oct. 2020 Spiritual Civilization Scholarship (2019-2020), Hohai University.

  • Oct. 2019 Academic Excellence Scholarship (2018-2019), Hohai University.

📖 Educations

  • 2024.04 - 2027.03, SGU-Ph.D., Kyushu University, Fukuoka, Japan.

  • 2020.10 - 2021.10, M.Sc., Imperial College London, London, UK.

  • 2020.09 - 2021.09, B.Sc. (Hons), Oxford Brookes University, Oxford, UK.

  • 2019.08 - 2019.08, Summer School: World Challenge and Innovation Program, Imperial College London, London, UK.

  • 2016.09 - 2020.06, B.Eng., Hohai University, Nanjing, China.

💬 Employment

  • 2021.12 - 2024.04, Senior Software Engineer, HUAWEI Technologies Co., Ltd., Shanghai.

💻 Internships

  • 2021.09 - 2021.12, Portfolio Investment Strategy Intern, China Futures Co., Ltd., Shanghai.