Jiaxu (Jacob) Zhang | 张家绪

Hi! I'm Jiaxu Zhang pursing a master's degree in Sun Yat-sen University, Shenzhen, China. I'm with the Lab of Intelligent Photoelectric Sensing under the supervision of Liang Wang. My bachelor's supervisor is Xiaojian Ma. I had a three-month remote internship at the Hong Kong Polytechnic University (PolyU in Hong Kong). I'm also a Visiting Student in China Academy of Railway Sciences.

I will graduate in June 2026. [Click to download my CV]

Email: zhangjx283@mail2.sysu.edu.cn

ORCID: https://orcid.org/0000-0002-6092-3224

News

[2025/11/14] (Coming soon) One paper has been accepted by IEEE Sensors Journal.

[2024/07/16] One paper has been accepted by Engineering Applications of Artificial Intelligence.

[2024/07/03] One paper has been accepted by Information Sciences.

[2024/03/20] I will give an oral presentation in 7th Global Intelligent Industry Conference.

[2024/03/07] One paper has been accepted by IEEE Sensors Journal.

[2024/01/26] One paper has been accepted by IEEE JSTARS.

[2023/03/17] One paper has been accepted by IEEE TIM.

Educational Experiences

· 2023/09-2026/06 | M.S. - Sun Yat-sen University, Shenzhen, China

      - Major: Information and Communication Engineering

      - GPA: 3.25/4.00, Avg Score: 85.13/100.00

· 2023/09-2025/06 | Visiting Student - China Academy of Railway Sciences, Beijing, China

      - Top railway research academy in China

      - Research Direction: Computer Vision, Multi-Modal Fusion Aided by Dempster-Shafer theory

· 2019/09-2023/06 | B.S. - Northeast Forestry University, Harbin, China

      - Major: Information and Computing Science (Computational Mathematics)

      - GPA: 4.26/5.00, Avg Score: 94.57/100.00

      - Ranking: 3/58 (Top 5.17%)

Social Experiences

· 2025/05-2025/09 | AI Algorithm Acceleration Engineer-Intern, Hikvision, Hangzhou

· 2024/05-2024/07 | Computer Vision Engineer-Remote Intern, PolyU, Hong Kong

· 2023/02-2023/09 | Computer Vision Engineer-Intern, China Academy of Railway Sciences, Beijing

Peer-review Experiences

I am a reviewer of High-speed Railway, Information Sciences.

Research Interests

My recent research interests include:

· Uncertainty qualification and information fusion with Dempster-Shafer's theory;

· Pattern recognition problems for high-speed railway;

· (Mathematics) The geometry of information in Dempster-Shafer's theory with oepn-world applications.

Publications

As first author, I have 5 papers published in SCIE. To see my work collection please visit Google Scholar.

1. Information Sciences (JCR Q1, 2024) vol.680 121153
	A new “E-E” paradigm to construct multi-BPAs based belief Jensen divergence in the evidence theory [Paper] Jiaxu Zhang; Shengchun Wang; Juan Tan; Liang Wang. We newly define the “I-P-E” and “E-E” paradigms to guide more belief Jensen divergences. Particularly, the “E-E” paradigm defines a new approach to define belief Jensen divergences with belief entropy.
2. IEEE Transactions on Instrumentation and Measurement (JCR Q1, 2023) vol.72 2508714
	Rail surface defect detection through bimodal RSDINet and three-branched evidential fusion [Paper] [Video] Jiaxu Zhang; Jiong Zhang; Jiejun Chen; Shengchun Wang; Liang Wang. A two-level fusion approach is designed based on RSDINet and evidence fusion aiming at the "false alarming-miss detection" dilemma in bimodal rail surface defect detection.
3. IEEE Sensors Journal (JCR Q1, 2024) vol.24 no.8 pp. 13217-13226
	Robust rail-track section identification with multiple structured light sensors and kernel-based belief sensor-credibility evaluation [Paper] [Video] Jiaxu Zhang; Shengchun Wang; Kunzhen Liu; Liang Wang. We leverage a multi-sensor fusion framework with evidence theory for robust rail-track section identification. We newly construct KIBM(Kernel Induced Belief Metric).
4. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JCR Q1, 2024) vol.17 pp.3799-3820
	Deep evidential remote sensing landslide image classification with a new divergence, multiscale saliency and an improved three-branched fusion [Paper] [Video] [Code] Jiaxu Zhang; Qi Cui; Xiaojian Ma. An evidence-theoretic framework is proposed for remote sensing landslide image classification. We construct Belief Jensen-Renyi divergence and an improved three-branched fusion.
5. Engineering Applications of Artificial Intelligence (JCR Q1, 2024) vol.136 109011
	A deep evidence fusion framework for apple leaf disease classification [Paper] Hang Wang; Jiaxu Zhang; Zhu Yin; Liucheng Huang; Jie Wang; Xiaojian Ma. A new deep evidence fusion framework based on belief Cauchy–Schwarz divergence is proposed to tackle the advent of similar visual symptoms in apple leaf disease classification.

Scholarships

· 2024 | China National Scholarship (Highest Honor for Chinese studenst, Top 1/63) - SYSU [Source]

· 2020 | China National Scholarship (Highest Honor for Chinese studenst, Top 1/122) - NEFU

Awards

· 2023 | Outstanding graduates - NEFU

· 2021 | Finalist award - Mathematical Contest In Modeling & Interdisciplinary Contest In Modeling (MCM/ICM, Top 2%)

· 2021 | National second-class award - China Undergraduate Mathematical Contest in Modeling (CUMCU)