Tie-Zhen Ren | Data Science | Best Researcher Award

Prof. Dr. Tie-Zhen Ren | Data Science | Best Researcher Award

Prof. Dr. Tie-Zhen Ren | Data Science – Xinjiang university | China

Profile Verified

Orcid

👤 Summary

Prof. Dr. Tie-Zhen REN is a highly experienced scholar in the field of inorganic materials chemistry and functional nanostructures. With over 20 years of academic and research experience, he has contributed extensively to the development of hierarchical porous materials, photocatalysis, and sustainable material technologies. He is currently a Professor at the School of Chemical Engineering, Xinjiang University, and has a broad international background, having worked and conducted research in Belgium, Sweden, the U.S., and multiple institutions across China.

🎓 Education

Dr. REN received his Ph.D. in Inorganic Materials Chemistry from the University of Namur (FUNDP), Belgium (2001–2005), where his research focused on the synthesis and properties of hierarchically nanoporous materials under the supervision of Prof. Bao-Lian Su. He also holds a Master’s degree in Plant Protection from Anhui Agricultural University (1999–2002), and a Bachelor’s degree in Polymer Engineering from Tianjin Institute of Technology (1994–1998), reflecting a well-rounded foundation in both chemical engineering and material sciences.

💼 Professional Experience

Prof. REN has held several academic and research positions, including his current role as Professor at Xinjiang University since 2021. Prior to that, he served as Professor at Hebei University of Technology from 2007 to 2021. His international experience includes a postdoctoral fellowship at Stockholm University, Sweden, and a visiting researcher position at the City College of New York. He also volunteered as a teacher at BayinGol Vocational and Technical College, and held early roles such as research assistant, documentalist, and industrial trainee, contributing to his comprehensive experience across academia and industry.

📚 Academic Achievements & Projects

Dr. REN has led multiple national and regional research projects, including those funded by the National Natural Science Foundation of China, the Ministry of Science and Technology, and the Xinjiang Autonomous Region. Notable projects involve work on porous titanium oxides, framework germanates, and carbon-modified catalysts. He has received several honors such as the Tianjin Natural Science Award (2015), the China National Scholarship for Excellent Self-Financed Students Abroad (2004), and awards for teaching and student mentorship.

🧪 Technical Skills

He possesses strong technical capabilities in materials characterization and analysis, including TEM (e.g., JEOL JEM-3010), SEM & EDX, XRD, FT-IR, UV-Vis spectroscopy, TGA-DSC, NMR, and electrochemical workstation operation. He is highly proficient in single-crystal and powder X-ray diffraction, nanomaterial synthesis, and ultramicrotome sample preparation, enabling advanced insights into material structure and functionality.

👨‍🏫 Teaching Experience

Throughout his academic career, Prof. REN has been committed to high-quality education. He has taught courses such as General Chemistry (at the City College of New York), Principles of Chemical Engineering (at Xinjiang University and BayinGol College), Principles of Catalysis, and Specialized Reading in English (at Hebei University of Technology). His teaching integrates experimental skills, scientific theory, and practical problem-solving in the chemical sciences.

🔬 Research Interests

His research interests lie in the design, synthesis, and characterization of porous and nanostructured materials, including mesoporous silica, metal oxides, dye-doped silica for optical applications, and crystalline germanium oxides. He is also focused on environmental catalysis, particularly the photodegradation of pesticides, carbon-based energy materials, and biomass transformation for sustainable technologies.

📚 Selected Publication

1. Preparation of Al₂O₃ Nanoparticles via Fluidized Roasting and Their Application in the Pyrolysis of Spent Mulching Film for Hydrocarbon Production
  • Authors: Zhong-He Song, Imran Muhammad, Tie-Zhen Ren, Ablikemu Abulizi, Kenji Okitsu, Huan-Rong Li, Xue-Jun Zhang

  • Journal: ACS Sustainable Resource Management

  • Year: 2025

2. Sulfite Enhanced Permanganate/Fe(II) Moderate Oxidation Coagulation for the Treatment of Algae-Laden Water: Performance and Mechanisms
  • Authors: Jinlong Han, Li Sun, Mathias Ulbricht, Lukas Fischer, Guangming Zhang, Wenfang Gao, Longyi Lv, Tiezhen Ren, Xiaoyang Liu, Zhijun Ren

  • Journal: Chemical Engineering Journal

  • Year: 2025

3. Surfactant-Enhanced ZnOₓ/CaO Catalytic Activity for Ultrasound-Assisted Biodiesel Production from Waste Cooking Oil
  • Authors: Hongyu Fu, Haifeng Bai, Abulikemu Abulizi, Kenji Okitsu, Yasuaki Maeda, Tiezhen Ren, Shengyan Wang

  • Journal: Reaction Chemistry & Engineering

  • Year: 2024

4. Boosting BaTi₄O₉ Photocatalytic H₂ Evolution Activity by Functionalized CuNi Alloy
  • Authors: Meng-Jie Cui, Shan-Shan Li, Tie-Zhen Ren, Abulikemu Abulizi, Ai-Sha Nulahong

  • Journal: Journal of Photochemistry and Photobiology A: Chemistry

  • Year: 2024

5. Isopropanol Assisted Preparation of α-Al₂O₃ Nanoparticles and Its Surface Charge Investigation
  • Authors: Meng-Jie Cui, Imran Muhammad, Jian Feng, Tie-Zhen Ren

  • Journal: Solid State Sciences

  • Year: 2024

 

Zhishui You | Brain-Computer Interface | Best Research Article Award

Mr. Zhishui You | Brain-Computer Interface | Best Research Article Award

Mr. Zhishui You | Brain-Computer Interface – Beihang University | China

Profile Verified

Orcid

🧾 Summary

Zhishui You is a dedicated graduate student at Beihang University with a strong foundation in mathematics and electronic information. His interdisciplinary expertise bridges theoretical concepts and practical applications, particularly in the area of brain-computer interface (BCI) technologies. Zhishui is committed to advancing neural signal processing through innovative research in EEG decoding and generative methods.

🎓 Education

Mr. You earned a Bachelor’s degree in Mathematics and Applied Mathematics and a Master’s degree in Electronic Information from Beihang University. His educational journey reflects both depth in quantitative sciences and a transition into applied engineering research, particularly in EEG signal processing.

💼 Professional Experience

During his master’s studies, Zhishui collaborated with the Boardware-Barco-Beihang BAIoT Brain Computer Intelligence Joint Laboratory. He also engaged in international research with Cranfield University, contributing to a review article in the journal Sensors. He participated in two consultancy projects and has one patent under process.

📚 Academic Citations

Zhishui has authored one peer-reviewed article in an SCI-indexed journal (Sensors, MDPI, Vol. 25, 2025). Although currently early in his academic career, his publication is a stepping stone toward impactful contributions in neural engineering.

🛠️ Technical Skills

His technical portfolio includes EEG signal preprocessing, generative modeling for virtual EEG data, and algorithm development for neural data augmentation. These skills are instrumental in enhancing model training efficiency and performance in BCI systems.

👨‍🏫 Teaching Experience

While not formally involved in teaching roles, Zhishui has mentored junior students and contributed to collaborative learning environments within his research labs.

🧠 Research Interests

His primary interests lie in Brain-Computer Interfaces, EEG decoding, signal generation methods, and neural data augmentation. He is particularly enthusiastic about advancing practical applications in assistive technologies and healthcare.

📚 Selected Publications

Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods
  • Authors: Zhishui You, Yuzhu Guo, Xiulei Zhang, Yifan Zhao
  • Journal: Sensors
  • Year: 2025

Min Cao | multimodal learning | Best Researcher Award

Assoc Prof Dr. Min Cao | multimodal learning | Best Researcher Award

Soochow University | China

Publication Profile

Scopus

👨‍🏫 Professional Summary

Dr. Min Cao is currently an Associate Professor at the School of Computer Science and Technology, Soochow University, where he also serves as Assistant to the Dean at the Artificial Intelligence Research Institute. He is a core contributor in the field of computer vision, particularly in multimodal learning, text-based person retrieval, and person re-identification. With over 22 published papers—including in top-tier journals (SCI Q1) and prestigious conferences such as AAAI, IJCAI, and ICCV—Dr. Cao has established himself as a leading researcher. He is the recipient of multiple research grants and holds 8 authorized invention patents. Actively involved in academic service, he is the Deputy Secretary-General of the Computer Vision Special Committee of the Shanghai Computer Society and an Executive Member of CCF Suzhou.

🎓 Education

Dr. Cao received his Ph.D. in Pattern Recognition and Intelligent Systems from the Institute of Automation, Chinese Academy of Sciences (2016–2020), under the supervision of Professor Silong Peng. Prior to that, he completed his bachelor’s degree in Electronic Information Engineering at Tianjin Polytechnic University in 2014.

💼 Professional Experience

He began his academic career as an Assistant Professor at Soochow University from March 2020 to September 2023, before being promoted to Associate Professor in October 2023. In addition, Dr. Cao was a visiting scholar at the Fraunhofer Institute for Image Data Processing in Germany from 2018 to 2019, where he conducted cutting-edge research in image analysis.

🔬 Research Interests

Dr. Cao’s research interests span across multimodal learning, text-based person search, person re-identification, graph neural networks, and cross-modal retrieval systems. His work aims to enhance retrieval performance in low-source and open-world environments.

📚 Academic Contributions

He has published 22 peer-reviewed papers, including in high-impact journals such as IEEE Transactions on Circuits and Systems for Video Technology and Pattern Recognition, and at top conferences like AAAI, IJCAI, and ACMMM. He has served as the principal investigator on multiple national and provincial-level research projects, including those funded by the National Natural Science Foundation of China. Dr. Cao also holds 8 granted patents related to image-text retrieval, anomaly detection, and multimodal learning systems.

🧑‍🏫 Teaching & Mentorship

Dr. Cao has been recognized for his commitment to teaching and student mentorship, guiding students who have received national graduate scholarships and awards for outstanding theses. In 2023, he was named Outstanding Instructor at the Global Campus Artificial Intelligence Algorithm Elite Competition.

🛠️ Technical Skills

He is proficient in machine learning and deep learning frameworks including PyTorch and TensorFlow, with strong programming skills in Python and C++. His technical toolkit also includes OpenCV, Scikit-learn, LaTeX, and tools for multimodal retrieval and graph-based learning.

🏆 Awards & Honors

His work has earned numerous accolades, including First Prize in the 2024 Suzhou Computer Society Outstanding Paper Award, Second Prize in the 2022–2023 Suzhou Natural Science Academic Paper Award, and recognition for excellence in student supervision and AI competition mentoring.

📚 Top Notes Publications

1. Efficient text-to-video retrieval via multi-modal multi-tagger derived pre-screening
  • Authors: Xu, Yingjia; Wu, Mengxia; Guo, Zixin; Ye, Mang; Laaksonen, Jorma T.

  • Journal: Visual Intelligence

  • Year: 2025

2. Diversified Data Expansion Method Using Text-Based Person Image Search
  • Authors: Wang, Jingyao; Cao, Min

  • Journal: Jisuanji Gongcheng / Computer Engineering

  • Year: 2024