yunhao zhao | Data Analysis Innovation | Best Researcher Award

Assoc Prof Dr. yunhao zhao | Data Analysis Innovation | Best Researcher Award

Qingdao Huanghai University, China

Author Profile

OrcidΒ 

πŸ§‘β€πŸŽ“ Early Academic Pursuits

Yunhao Zhao was Shandong, P.R. China. His academic journey began with a strong foundation in International Economics and Social Security studies, setting the stage for his future research. After completing his undergraduate education, he became an associate professor at Qingdao Huanghai University, where he also supervises undergraduate students. His quest for further knowledge continues as he pursues a Ph.D. at The Catholic University of Korea, focusing on the evolving fields of economics and social security.

πŸ‘¨β€πŸ« Professional Endeavors

Dr. Zhao’s academic career has been marked by significant contributions in the realms of data analysis and economic research. As an All-Media Operator and Associate Professor, he actively engages in both teaching and research at Qingdao Huanghai University. His dedication to advancing knowledge in the academic sphere extends to overseeing the academic progress of undergraduate students, ensuring they are equipped with the necessary skills and insights to excel in their respective fields.

πŸ“Š Contributions and Research Focus

Dr. Zhao’s primary research areas are data analysis, internet of things (IoT), and auction theory. His most notable work focuses on congestion control in IoT systems, where he applied auction theory to improve performance and efficiency. His research contributions are significant in their potential to drive forward the development of smarter and more efficient IoT networks. Furthermore, his work on energy consumption reduction demonstrates the real-world impact of his methods, achieving a remarkable 24.13% reduction in energy usage in experimental scenarios.

🌍 Impact and Influence

Dr. Zhao’s work has already made notable contributions to the global research community, evidenced by his publication in Scientific Reports (SCI) and recognition in high-impact journals. His research on IoT and auction theory has contributed to solving critical issues in technology and energy efficiency, impacting industries reliant on smart technology. His scholarly output has the potential to influence policy and innovation in areas such as network management and resource optimization.

πŸ”§ Technical Skills

Dr. Zhao possesses advanced technical skills in data analysis, machine learning, and network optimization, particularly within the context of IoT systems. His expertise in auction theory and its applications in real-world scenarios is a testament to his depth of understanding and innovation in these areas. He is also adept at utilizing advanced analytical tools and methods to derive actionable insights from complex datasets.

πŸ‘©β€πŸ« Teaching Experience

As an Associate Professor at Qingdao Huanghai University, Dr. Zhao has extensive experience in educating the next generation of scholars and professionals. His role as a supervisor for undergraduate students allows him to nurture young talent and help shape their academic journeys. His commitment to teaching is evident through his personalized mentorship approach, guiding students to succeed in both their academic and professional aspirations.

🌟 Legacy and Future Contributions

Looking ahead, Dr. Zhao aims to continue contributing to the field of International Economics and Social Security Studies, with a strong emphasis on data-driven solutions. His work has already proven impactful, and he intends to further refine his methodologies to solve pressing global issues such as economic inequality, social security systems, and technological advancements in IoT. His legacy will undoubtedly inspire future researchers and practitioners in these fields, and his work has the potential to pave the way for groundbreaking solutions in economic policy and technological development.

πŸ† Recognition and Awards

Dr. Zhao’s academic achievements have garnered recognition within the research community. He is a strong candidate for the Best Researcher Award for his ongoing contributions to data analysis and IoT research. His ability to surpass existing methodologies, particularly in terms of energy efficiency, sets him apart as an innovator in his field. His commitment to advancing knowledge and solving real-world problems makes him a deserving nominee for such accolades.

 

πŸ“– Top Noted Publications

Congestion control in internet of things (IoT) using auction theory
    • Authors: Zhenlong Li; Yunhao Zhao
    • Journal: Scientific Reports
    • Year: 2024
Enhancing China’s green GDP accounting through blockchain and artificial neural networks (ANNs) and machine learning (ML) modeling
    • Authors: Nasi Wang; Yunhao Zhao; Jun Li; Guanfeng Cai
    • Journal: Scientific Reports
    • Year: 2024
Speech emotion analysis using convolutional neural network (CNN) and gamma classifier-based error correcting output codes (ECOC)
    • Authors: Yunhao Zhao; Xiaoqing Shu
    • Journal: Scientific Reports
    • Year: 2023

Theresa KΓΌhle | Data Analysis | Best Researcher Award

Mrs. Theresa KΓΌhle | Data Analysis | Best Researcher Award

Mrs. Theresa KΓΌhle at UniversitΓ€t MΓΌnster, Germany

πŸ‘¨β€πŸŽ“Professional Profile

🌟 Summary

Theresa KΓΌhle is a dedicated medical student at the University of MΓΌnster, Germany, with a strong focus on pediatric cardiology, prenatal medicine, and psychosomatic disorders. Passionate about research and clinical practice, she has presented at several medical congresses and published research in the field of fetal heart failure. As a Cusanuswerk scholarship recipient, she is committed to advancing in her medical career with international experience.

πŸŽ“ Education

Since 2019, Theresa has been studying medicine at the University of MΓΌnster, Germany. She also gained international medical experience at the Universidad de Valladolid, Spain, in 2023. Theresa completed her Abitur at Gymnasium Schloss Neuhaus, Paderborn, in 2018, with an outstanding grade of 1.0.

πŸ’Ό Professional Experience

Theresa has gained extensive practical experience in hospitals and medical settings. Since 2024, she has been working as an OP student in the Department of Gynaecology and Obstetrics at St. Franziskus-Hospital in MΓΌnster. She also gained clinical experience in pediatrics, cardiology, neurology, urology, and psychosomatic medicine at the University Hospital MΓΌnster. In addition, she has been a tutor for a sonography course at her university since 2024.

πŸ“‘ Academic Citations

In 2024, Theresa presented posters at the 65th DGGG Congress in Berlin and the 47th Tri-Nation Meeting in Salzburg. She has also published a research paper on “Dyssynchronous fetal heart failure in maternal diabetes” with Prof. Dr. Ralf Schmitz, highlighting her active involvement in medical research.

πŸ› οΈ Technical Skills

Theresa possesses advanced skills in sonography, as evidenced by her role as a tutor in the ultrasound course at the University of MΓΌnster. She has a deep understanding of prenatal diagnostics, particularly in echocardiography and M-mode software. In addition, she is fluent in English (C1/C2), Spanish (B2.2), and French (B2), with proficiency in Latin.

πŸ‘©β€πŸ« Teaching Experience

Theresa has enriched her teaching portfolio by serving as a tutor for the sonography course at the University of MΓΌnster since 2024. She has also gained hands-on teaching experience in psychosomatic treatments, pediatrics, and psychotherapeutic practices during her medical training.

πŸ”¬ Research Interests

Her research focuses on pediatric cardiology, particularly congenital heart defects, and prenatal medicine, with a specific interest in fetal heart failure caused by maternal diabetes. Additionally, Theresa is passionate about psychosomatic medicine and psychological health treatments for children and adolescents.

πŸ“–Top Noted Publication

Dyssynchronous Fetal Heart Failure in Maternal Diabetes: Evaluation with Speckle Tracking Echocardiography and Novel M-Mode Software

Authors: Theresa M. KΓΌhle, Angela Burgmair, Georg Schummers, Mareike MΓΆllers, Kathrin Oelmeier, Chiara De Santis, Helen Ann KΓΆster, Ute MΓΆllmann, Daniela Willy, Janina Braun, et al.

Journal: Ultrasound in Medicine & Biology

Year: 2024

Sogand Dehghan | social network analysis | Best Innovation Award

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

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

πŸ‘¨β€πŸŽ“Professional Profiles

Orcid Profile

Google ScholarΒ  Profile

πŸ‘©β€πŸ’» 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.

πŸŽ“ 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.

πŸ’Ό 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.

πŸ“š 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.

πŸ”§ 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.

πŸ‘¨β€πŸ« 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.

πŸ” 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.