Junwei Du | Computer Science | Best Researcher Award

Published on 17/12/202417/12/2024 by Book of Award

Prof. Junwei Du | Computer Science | Best Researcher Award

Qingdao University of Science and Technology | China

Author Profile

Early Academic Pursuits 🎓

Prof. Junwei Du embarked on his academic journey with a strong foundation in computer science. He earned his Ph.D. in Computer Software and Theory from Tongji University in 2010. His thirst for international exposure led him to become a Visiting Scholar at Arizona State University, USA, in 2014. Further enriching his skills, Prof. Du attended the AI Training Workshop for Young Backbone hosted by the University of Queensland and the University of Technology, Sydney, Australia, in September 2018.

Professional Endeavors 💼

Prof. Junwei Du is currently Executive Vice Dean of the School of Data Science at Qingdao University of Science and Technology. His professional affiliations include being a Distinguished Member of CCF and holding memberships in prestigious committees like the China Computer Society's Software Engineering Specialised Committee and the China Automation Society's Network Information Service Committee. Additionally, he serves as a Director of the Shandong Artificial Intelligence Society, underscoring his leadership in the field.

Contributions and Research Focus 🔬

Prof. Du's research focuses on cutting-edge areas like intelligent software engineering, graph representation learning, and recommendation algorithms. He has led numerous high-impact projects, including a National Natural Science Foundation of China top-level project, two provincial funds, and a key R&D project in Shandong Province. His work has also extended to over 10 national vertical projects and nine enterprise-driven horizontal projects. Prof. Du has published more than 60 academic papers in renowned journals such as Information Sciences, Software Journal, and Expert Systems with Applications. His research has significantly contributed to software fault prediction, cross-domain recommendation systems, and privacy-preserving algorithms in IoT.

Accolades and Recognition 🏆

Prof. Junwei Du’s achievements have earned him notable accolades. As a key participant, he received the Third Prize of Shandong Provincial Scientific and Technological Progress and the Third Prize of Shandong Provincial Teaching Achievement. He has also guided his students to excel in prestigious competitions, leading them to win over 20 national awards in software design and testing.

Impact and Influence 🌍

Through his extensive contributions, Prof. Junwei Du has shaped the landscape of intelligent software systems and data science education. His leadership in research and teaching has inspired countless students to pursue innovation. Prof. Du’s work on ensemble learning, recommendation algorithms, and software fault prediction holds significant implications for industries ranging from IT to industrial IoT, enhancing technological efficiency and reliability.

Legacy and Future Contributions 🔮

Prof. Junwei Du continues to build a legacy of excellence, bridging academia and industry with transformative research and mentorship. His focus on emerging areas like graph representation learning and cross-domain recommendation systems will pave the way for smarter AI applications. By fostering collaboration and innovation, he is set to make lasting contributions to data science and software engineering, empowering the next generation of researchers and professionals.

Publications

📄 Improving Bug Triage with the Bug Personalized Tossing Relationship
Authors: Wei Wei, Haojie Li, Xinshuang Ren, Feng Jiang, Xu Yu, Xingyu Gao, Junwei Du
Journal: Information and Software Technology
Year: 2025

📄 A Privacy-Preserving Cross-Domain Recommendation Algorithm for Industrial IoT Devices
Authors: Yu X., Peng Q., Lv H., Du J., Gong D.
Journal: IEEE Transactions on Consumer Electronics
Year: 2024

📄 Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao C., Du J., Wang F., Li H.
Journal: Applied Mathematics and Nonlinear Sciences
Year: 2024

📄 A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features
Authors: Yu X., Lu Y., Jiang F., Du J., Gong D.
Journal: IEEE Transactions on Network and Service Management
Year: 2024

📄 A Multi-Behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning
Authors: Yu J., Jiang F., Du J.W., Yu X.
Journal/Proceedings: Communications in Computer and Information Science
Year: 2024

Xinhai Wang | Computer Science | Best Researcher Award

Published on 05/10/202405/10/2024 by Book of Award

Mr. Xinhai Wang | Computer Science | Best Researcher Award

Northeastern University | China

Author Profile

Orcid

Early Academic Pursuits 🎓

Mr. Xinhai Wang's academic journey began with an undergraduate degree in Mathematics and Applied Mathematics from Northeastern University, where he achieved a GPA of 3.81/5. His academic excellence earned him several accolades, such as the "Outstanding Student Cadre" and "Three Good Students" awards, reflecting his dedication to both academics and extracurricular activities. Wang was actively involved in numerous projects during his undergraduate years, honing his skills in advanced algebra, data mining, and mathematical modeling, laying the groundwork for his future endeavors.

Professional Endeavors 🏆

In September 2022, Xinhai Wang assumed the role of monitor for Northeastern University's Master of Science Class 2201, demonstrating exemplary leadership and organizational skills. His work extended beyond the classroom, where he helped in the construction of class activities and assisted in Party branch operations. Wang was awarded the honorary title of Outstanding Graduate Student Cadre for his relentless efforts in promoting student engagement and fostering a collaborative environment. As a deputy director in the Project Development Department of the Social Practice Department, he organized impactful student initiatives such as charity sales, making significant contributions to the student community.

Contributions and Research Focus 🔬

Mr. Wang's contributions to academia and research are vast, with his work primarily centered on applying advanced algorithms in real-world scenarios. He has engaged in several high-level projects, including the application of genetic algorithms in mobile chess and using deep learning techniques like Deep Q Networks for stock market predictions. His research has tackled challenges in time series prediction, exploring fractional order random configuration networks (FSCN) to address the inherent non-stationarity in real-world data. These projects showcase his technical expertise in MATLAB and Python, alongside his growing knowledge of reinforcement learning and machine learning.

Accolades and Recognition 🏅

Xinhai Wang's academic brilliance has been recognized throughout his career, both during his undergraduate and graduate studies. His GPA of 3.40/4 ranked him 2nd in his class, further earning him prestigious honors such as the President Scholarship and First-Class Academic Scholarship. His leadership in class and organizational roles has led to multiple "Outstanding Class Cadre" awards. Wang's academic achievements extend beyond his GPA and awards, with his research work being submitted to conferences and awaiting SCI journal reviews, positioning him as a rising star in applied statistics and data science.

Impact and Influence 🌟

Through his roles in student governance and research, Wang has had a lasting impact on both his peers and the academic community. He has innovated branch activities, guided students in social practice initiatives, and created platforms for broader engagement in scientific and social matters. His research endeavors, such as the application of deep learning to stock prediction and time series analysis, contribute to the growing body of knowledge in the field of statistical modeling and artificial intelligence, influencing future technological advancements.

Legacy and Future Contributions 💡

Mr. Xinhai Wang's journey reflects a commitment to excellence in academic leadership, research, and innovation. As he continues to explore the boundaries of machine learning, algorithm design, and data modeling, his future contributions will likely have a profound effect on emerging fields like stock prediction and industrial data analysis. His ongoing projects in MATLAB and Python, combined with his growing expertise in reinforcement learning, position him for future success in both academic and professional arenas.

Publications

📄 Prediction of Ship-Unloading Time Using Neural Networks
Author: Zhen Gao, Danning Li, Danni Wang, Zengcai Yu, Witold Pedrycz, Xinhai Wang
Journal: Applied Sciences
Year: 2024-09

📄 Novel Admissibility Criteria and Multiple Simulations for Descriptor Fractional Order Systems with Minimal LMI Variables
Author: Xinhai Wang, Jin-Xi Zhang
Journal: Fractal and Fractional
Year: 2024-06

Georgiana Burlacu | Economics, Econometrics and Finance | Best Researcher Award

Published on 31/07/202431/07/2024 by Book of Award

Ms. Georgiana Burlacu | Economics, Econometrics and Finance | Best Researcher Award

Alexandru Ioan Cuza University | Romania

Author Profile

Orcid

Early Academic Pursuits 📚

Ms. Georgiana Burlacu began her academic journey at the Faculty of Economics and Business Administration at "Alexandru Ioan Cuza" University in Iasi, Romania. She earned her Bachelor's degree in 2020, focusing on a comprehensive range of subjects including Fundamentals of Accounting, Financial Accounting, and Corporate Finance Management. She continued her education with a Master's degree from the same university, completed in 2022, delving deeper into IAS-IFRS, Financial Diagnosis, and Audit Standards. Currently, she is pursuing her PhD at the Doctoral School of Economics and Business Administration, specializing in Accounting, Financial Auditing, and Quantitative and Qualitative Analysis.

Professional Endeavors 💼

Ms. Burlacu's professional career is marked by significant roles in accounting and economics. She started as an Accountant at IMA Componentes Iasi SRL, where she was responsible for recording and archiving accounting documents, managing internal documents, and maintaining customer and supplier relationships. She then moved to AWWWDUDE SRL as an Accountant, where she continued her previous responsibilities and participated in annual inventory processes. Currently, she serves as an Economist at Thinslices Development SRL, Iasi, Romania, focusing on the analysis and tracking of supplier balances and internal document management.

Contributions and Research Focus 📝

Ms. Burlacu has made notable contributions to the field of accounting and financial auditing. Her research primarily focuses on financial fraud, earnings management, and the impact of global crises on financial practices. She has published several papers, including "The Influence of Covid-19 Pandemy on Financial Fraud Risk Assessment" and "Analysis of Accruals Earnings Management Using the Jones Model: The Case of Romania Listed Companies." Her work often incorporates advanced methodologies such as the Fraud Pentagon Theory and Logistic Regression Analysis.

Accolades and Recognition 🏆

Ms. Burlacu's dedication and expertise have been recognized through various awards and honors. She received the Medal of Excellence in Innovation for her work on fraud risk analysis during the Covid-19 pandemic at the 15th EUROINVENT 2023. Additionally, she earned a Silver Medal for her innovative approach to fraud risk assessment using artificial neural networks at the 16th EUROINVENT 2024. Her academic achievements also include high rankings in her bachelor's and master's studies and the publication of influential research articles.

Impact and Influence 🌍

Ms. Burlacu's research has significantly impacted the field of financial auditing and accounting. Her studies on financial fraud and earnings management provide valuable insights into the challenges and solutions faced by professionals in these domains. Her work during the Covid-19 pandemic highlighted the increased risks of financial fraud during crises, influencing how organizations approach fraud risk management. Her innovative use of statistical and computational models has set new standards for fraud detection and financial analysis.

Legacy and Future Contributions 🌟

Looking forward, Ms. Burlacu is poised to continue her impactful research and contribute further to the field of economics and accounting. Her ongoing PhD studies promise to yield more groundbreaking insights into financial auditing and fraud prevention. With her solid academic background, professional experience, and research prowess, Ms. Burlacu is set to leave a lasting legacy in the world of financial analysis and auditing. Her future contributions will likely continue to shape best practices and innovative approaches in the industry.

Publications 📚

📝Exploring the Influence of Earnings Management on the Value Relevance of Financial Statements: Evidence from the Bucharest Stock Exchange

Authors: Georgiana Burlacu; Ioan-Bogdan Robu; Ionela Munteanu
Journal: International Journal of Financial Studies
Year: 2024

📝The Influence of Covid-19 Pandemic on Financial Fraud Risk Assessment

Authors: Georgiana Burlacu; Ioan-Bogdan Robu
Journal: “Ovidius” University Annals, Economic Sciences Series
Year: 2023

📝Analysis of Accruals Earnings Management Using the Jones Model: The Case of Romania Listed Companies

Authors: Georgiana Burlacu; Ioan-Bogdan Robu
Journal: Journal of Accounting and Management Information Systems
Year: 2024

📝Financial Fraud: Challenges and Solutions for Financial Auditing and Accounting Professionals – a Bibliometric Research

Authors: Georgiana Burlacu; Ioan-Bogdan Robu
Journal: Audit Financiar
Year: 2024

Elaheh Yaghoubi | Energy | Best Researcher Award

Published on 11/07/202411/07/2024 by Book of Award

Dr. Elaheh Yaghoubi | Energy | Best Researcher Award

Karabuk University | Turkey

Author profile

Scopus

Orcid

Early Academic Pursuits

Dr. Elaheh Yaghoubi's academic journey began with an Associate's degree in Electrical Engineering from University College of Rouzbahan, Iran, where she graduated with a GPA of 3.5. She then pursued a Bachelor's degree in Electrical Engineering at Aryan Institute of Science and Technology University, Iran, achieving a perfect GPA of 4. Following this, she completed her Master's degree in Electrical Engineering at Islamic Azad University in Qaemshahr, Mazandaran, Iran, again with a perfect GPA of 4. Her Master's thesis focused on developing a routing algorithm for a proposed topology for a grid on a large-scale chip to detect errors. Dr. Yaghoubi is currently a Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University in Turkey, where she is working on her thesis titled "Optimal power control of grid-connected distributed generation in a hierarchical framework based on Model Predictive Control."

Professional Endeavors

Dr. Yaghoubi has a diverse professional background that complements her academic achievements. From 2015 to 2018, she served as a Senior Manager at Kati Kabl Tabarestan Factory in Mazandaran, Iran, where she was responsible for quality assurance, inspecting products to ensure high quality, and troubleshooting technical issues. She then worked as a Senior Manager at Rico Electronics Company in Mazandaran, Iran, overseeing product quality assurance and implementing design modifications. From 2019 to 2021, she worked as a Website Designer at WebCore Company in Mazandaran, designing front-end interfaces with HTML, CSS, and JavaScript, and back-end systems with PHP and Laravel. Currently, Dr. Yaghoubi is a Principal Researcher at the Power Electrical Developing Advanced Research (PEDAR) group, focusing on investigation, teaching, and designing.

Contributions and Research Focus

Dr. Yaghoubi's research interests are broad and interdisciplinary, encompassing power system analysis, power system stability, power management, microgrids, smart grids, renewable energies, model predictive controllers (MPC), artificial neural networks, machine learning, deep learning, plasmonic applications, and nano-electronic devices. Her current research work involves optimal power control of grid-connected distributed generation using model predictive control, a topic that is crucial for the advancement of smart grids and renewable energy systems. She has also contributed to the understanding and development of routing algorithms for large-scale chips and has experience in quality control and product management in industrial settings.

Accolades and Recognition

Throughout her academic and professional career, Dr. Yaghoubi has been recognized for her excellence and contributions. She successfully passed her Ph.D. qualification exam with a perfect grade of 4 out of 4. Her consistent academic performance, marked by perfect GPAs during her Bachelor's and Master's studies, reflects her dedication and expertise in her field.

Impact and Influence

Dr. Yaghoubi's work has had a significant impact on both academic and industrial fields. Her research on smart grids, optimization techniques, and model predictive control contributes to the development of more efficient and reliable power systems. Her practical experience in quality control and product management ensures that her research is grounded in real-world applications and industrial standards.

Legacy and Future Contributions

Dr. Yaghoubi's legacy lies in her interdisciplinary approach to electronic and electrical engineering, integrating theoretical research with practical applications. Her work in power systems, renewable energy, and advanced control techniques positions her as a key contributor to the future of smart grid technology and sustainable energy solutions. As she continues her research and professional activities, Dr. Yaghoubi is likely to make further significant contributions to the field, driving innovation and excellence in electronic and electrical engineering.

Notable Publications

A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in field of geotechnical engineering 2024

Controlling and tracking the maximum active power point in a photovoltaic system connected to the grid using the fuzzy neural controller 2023 (1)