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

Published on by Research Data Analysis

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

Sogand Dehghan | social network analysis | Best Innovation Award

Published on by Research Data Analysis

Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👨‍🎓Professional Profiles

Orcid Profile

Google Scholar  Profile

👩‍💻 Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

💼 Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

👨‍🏫 Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.