Marcelo Vasconcelos | Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

Mr. Marcelo Vasconcelos | Artificial Intelligence | Best Researcher Award

IT Auditor at Court of Auditors of the Federal District, Brazil

Marcelo Oliveira Vasconcelos is a seasoned professional and researcher from Brasília, Brazil, with over two decades of experience across public administration, financial auditing, and technology-based risk management. Currently pursuing a Ph.D. in Web Science and Technology, Marcelo’s expertise spans various roles, including Financial and External Control Analyst at the Tribunal de Contas do Distrito Federal (TCDF). He holds multiple certifications, such as Certified Information Systems Auditor (CISA) and Risk Management Professional (ISO 31000:2018). His research focuses on enhancing corruption risk assessments in public administration using advanced data science methods, making him a prominent figure in the application of technology for public sector improvements. Proficient in Portuguese, English, and Spanish, Marcelo brings a global perspective to his work, bolstered by leadership training from École Nationale d’Administration (ENA) in France. His contributions, such as his recent publications on artificial intelligence applications in public administration, underscore his commitment to advancing effective governance practices through data-driven insights and innovative methodologies.

Professional Profile

Education

Marcelo Vasconcelos has a comprehensive academic background that blends technology, law, and public administration. He is currently a Ph.D. candidate in Web Science and Technology at the University of Trás-os-Montes e Alto Douro (UTAD), Portugal, which builds on his Master’s degree in Computer Science from the University of Brasília, completed in 2020. His formal education is supplemented by a range of specialized qualifications: an MBA in Public Law from Instituto Processus and another in Constitutional Law from Instituto de Direito Público, Brasília. Marcelo also holds a Bachelor’s degree in Public Administration from the State University of Goiás and an undergraduate degree in Science from UniCEUB Brasília. His academic trajectory is further complemented by international training in leadership and public management from École Nationale d’Administration (ENA) in France, which has enriched his expertise in governmental processes and administration. Marcelo’s educational journey reflects a balanced combination of technical expertise, public policy, and governance, aligning with his goal to leverage data science for practical solutions in public administration.

Professional Experience

Marcelo Vasconcelos has accumulated diverse professional experience, with a primary focus on public sector auditing and analysis. Since August 2004, he has served as a Financial and External Control Analyst at the Tribunal de Contas do Distrito Federal (TCDF), where he applies his expertise in data auditing, fraud detection, and risk management to enhance public accountability. Previously, he held various roles, including Social Security Tax Auditor at the National Social Security Institute (INSS) from 2003 to 2004, and Foreign Trade Analyst at the Secretariat of Foreign Trade, where he honed his skills in regulatory compliance and policy analysis. His early career also includes work as a Federal Revenue Analyst for the Secretariat of Federal Revenue and as a Teacher of Science and Mathematics in the Federal District’s Secretariat of Education. Marcelo’s professional journey reflects a commitment to strengthening governance and public sector efficiency, leveraging both his analytical and technological skills to contribute to Brazil’s federal and financial control sectors.

Research Interest

Marcelo’s primary research interest lies in the intersection of data science, public administration, and ethics, particularly in using technology to tackle corruption and enhance governance transparency. His research explores the application of artificial intelligence and machine learning to identify and mitigate risks associated with public administration processes. Notably, Marcelo has focused on creating models that assess corruption risk in public administration, emphasizing the development of imbalanced learning techniques to improve accuracy in risk detection. His work, such as his study on mitigating false negatives in imbalanced datasets, aligns with his commitment to data-driven governance reforms. In addition, Marcelo’s interest extends to Web Science and the application of large datasets for public decision-making. By advancing methodologies that blend computer science with public policy, he seeks to bridge gaps in data application and ethical governance, positioning his research within the broader movement of responsible AI in public services.

Research Skills

Marcelo Vasconcelos brings a robust skill set to his research, particularly in data analytics, risk assessment, and machine learning applications in public administration. He is proficient in using artificial intelligence techniques, specifically imbalanced learning methods, to enhance the reliability of corruption risk models. His technical skills extend to using Control Objectives for Information and Related Technologies (COBIT 5) and ISO 31000:2018 standards for risk management. Marcelo is certified as a Certified Information Systems Auditor (CISA), which bolsters his skills in cybersecurity and information systems auditing. His analytical expertise is complemented by his experience in developing ensemble approaches to minimize errors in data models. Marcelo also brings practical knowledge in data governance and policy application, supported by his academic research, which is published in journals like Expert Systems with Applications and Data in Brief. These skills position him as a research-driven professional with advanced capabilities in designing, implementing, and evaluating technology-based solutions for complex public sector challenges.

Awards and Honors

While Marcelo’s curriculum does not explicitly mention awards, his achievements reflect recognition through certifications and high-impact publications. His certifications, including CISA and ISO 31000:2018 for risk management, demonstrate his commitment to maintaining industry standards and developing expertise in information systems and public sector accountability. Marcelo’s acceptance of his work in respected journals, such as Data in Brief and Expert Systems with Applications, further highlights his research contributions. His participation in leadership training at the prestigious École Nationale d’Administration (ENA) also underscores his standing as a thought leader in the public sector. By achieving a high level of proficiency in his certifications and continuing professional development, Marcelo has positioned himself as a well-regarded expert in his field, aligning with the standards expected for research awards in public administration and technology applications.

Conclusion

Marcelo Vasconcelos demonstrates a robust profile for the Best Researcher Award, combining practical public sector expertise with advanced research in technology and data analytics. His work in assessing corruption risk through imbalanced learning models addresses critical issues, showcasing his contribution to public administration and AI fields. Strengthening his academic engagement and expanding his research scope could enhance his candidacy further, positioning him as a well-rounded researcher with substantial contributions to his field.

Publication Top Notes

  • Title: Mitigating False Negatives in Imbalanced Datasets: An Ensemble Approach
    • Publication: Expert Systems with Applications
    • Year: 2025
    • DOI: 10.1016/j.eswa.2024.125674
    • Authors: Marcelo Vasconcelos, Luís Cavique
  • Title: Dataset for Corruption Risk Assessment in a Public Administration
  • Title: Imbalanced Learning in Assessing the Risk of Corruption in Public Administration
    • Publication: Book Chapter in Imbalanced Learning in Assessing the Risk of Corruption in Public Administration
    • Year: 2021
    • DOI: 10.1007/978-3-030-86230-5_40
    • Authors: Marcelo Oliveira Vasconcelos, Ricardo Matos Chaim, Luís Cavique

 

M Sinthuja | Machine Learning | Best Researcher Award

Posted on by ScienceFather

M Sinthuja | Machine Learning | Best Researcher Award

Assistant Professor at M S Ramaiah Institute of Technology, India

M. Sinthuja is a dedicated academic and researcher specializing in data mining and information technology. With over a decade of teaching experience across various prestigious institutions, she has made significant contributions to the field through her innovative research and commitment to student development. Sinthuja’s career began as an Assistant Professor at Sri Ramakrishna Institute of Technology, followed by positions at other esteemed colleges, where she has played a pivotal role in disseminating theoretical and practical knowledge to students. Her research focuses on applying data mining techniques to analyze frequent patterns within online shopping databases, a field increasingly relevant in today’s data-driven world. Sinthuja has authored numerous papers published in recognized journals, showcasing her ability to contribute valuable insights to the academic community. Additionally, she actively engages in mentoring students to identify their interests and achieve academic excellence. Her work has garnered recognition, including sponsorship from the University Grants Commission (UGC) of India. Sinthuja’s passion for research and teaching positions her as a noteworthy candidate for accolades such as the Best Researcher Award, reflecting her potential for continued contributions to her field.

Professional Profile

Education

M. Sinthuja’s educational background has laid a strong foundation for her career in academia and research. She pursued her higher studies in Computer Science and Engineering, culminating in a research thesis submitted in December 2018 at Annamalai University. Her research, titled “Application of Data Mining Techniques for Finding Frequent Patterns using Online Shopping Database,” showcases her expertise in data mining, a critical area in the modern technological landscape. Sinthuja’s academic journey includes her undergraduate studies, where she developed a solid understanding of computer science fundamentals. Additionally, her commitment to lifelong learning is evident in her various professional development activities and participation in academic workshops. This educational trajectory not only equips her with a robust theoretical framework but also enhances her practical skills in programming and data analysis. Her academic achievements demonstrate a blend of theoretical knowledge and practical application, making her a proficient educator and researcher. Sinthuja’s academic background, combined with her dedication to teaching and research, positions her as a valuable contributor to the field of computer science and data mining.

Professional Experience

M. Sinthuja possesses a rich and diverse professional experience that spans over a decade in the field of information technology and computer science education. Beginning her career as an Assistant Professor at Sri Ramakrishna Institute of Technology in Coimbatore, she played a pivotal role in shaping the academic journey of numerous students. Following this, she held similar positions at SBM College of Engineering and Technology and Presidency University in Bangalore, further expanding her expertise and influence in the academic community. Since 2020, she has been an Assistant Professor at M. S. Ramaiah Institute of Technology, recognized as one of the top engineering colleges in Karnataka. Throughout her career, Sinthuja has emphasized the importance of disseminating theoretical and practical knowledge, motivating students to excel academically, and fostering a culture of self-learning. Her teaching methodologies incorporate current industry trends, preparing students for real-world challenges. Sinthuja’s commitment to education is evident in her proactive engagement in curriculum development and student mentorship, establishing her as a respected figure in the academic realm. This breadth of experience underscores her capability as an educator and her dedication to advancing the field of information technology.

Research Interest

M. Sinthuja’s primary research interest lies in the field of data mining, particularly in the application of data mining techniques to uncover frequent patterns in large datasets. Her doctoral research focused on analyzing online shopping databases, which is crucial in today’s e-commerce-driven economy. She is particularly interested in the development and evaluation of algorithms that enhance the efficiency of data mining processes. Sinthuja’s work encompasses a variety of data mining methodologies, including association rule mining and frequent itemset mining, which are essential for extracting valuable insights from complex datasets. Her research not only contributes to theoretical advancements in data mining but also has practical implications for businesses seeking to leverage data for strategic decision-making. Additionally, she aims to explore interdisciplinary applications of data mining in fields such as healthcare, finance, and social media analysis. By integrating her findings with real-world applications, Sinthuja seeks to bridge the gap between academic research and industry needs. This commitment to applying theoretical knowledge to practical challenges reflects her dedication to advancing the field of data science and her desire to contribute positively to societal advancements through technology.

Research Skills

M. Sinthuja possesses a comprehensive skill set that enhances her research capabilities in the field of data mining and information technology. She is proficient in several programming languages, including C, C++, Java, and Python, which are essential for developing algorithms and implementing data analysis techniques. Additionally, her knowledge of scripting languages such as HTML and JavaScript allows her to create user interfaces and enhance data visualization in her projects. Sinthuja is adept at utilizing various database management tools and operating systems, enabling her to work with diverse datasets and perform complex analyses. Her research skills extend to the design and evaluation of algorithms, particularly in association rule mining, where she has conducted extensive comparative studies on algorithm performance. Sinthuja’s ability to analyze data, draw meaningful conclusions, and present findings clearly has resulted in numerous publications in reputable journals. Furthermore, she excels in mentoring students and collaborating with peers, demonstrating her ability to work effectively in research teams. Overall, her technical proficiency, analytical thinking, and collaborative spirit make her a valuable asset to any research endeavor in the domain of data mining and computer science.

Awards and Honors

M. Sinthuja has received several accolades throughout her academic and research career, recognizing her contributions to the field of data mining and information technology. A notable achievement is the sponsorship of her research by the University Grants Commission (UGC) of India, which underscores the significance and relevance of her work in the academic community. This endorsement not only validates her research efforts but also highlights her potential to make impactful contributions to the field. Additionally, her research has been published in several respected journals, showcasing her commitment to disseminating knowledge and advancing academic discourse in data mining. The recognition of her work in indexed journals, such as SCOPUS and UGC-listed publications, reflects her dedication to high-quality research output. Sinthuja’s involvement in collaborative research projects and her active participation in academic conferences further illustrate her commitment to professional development and networking within her field. These honors and recognitions serve as a testament to her expertise and influence as a researcher and educator, positioning her favorably for future accolades, such as the Best Researcher Award.

Conclusion

In conclusion, M. Sinthuja stands out as a remarkable candidate for the Best Researcher Award, owing to her extensive contributions to the field of data mining and her commitment to academic excellence. Her solid educational background, combined with over a decade of professional experience, underscores her qualifications as both an educator and a researcher. Sinthuja’s research focus on data mining techniques, particularly in analyzing online shopping databases, highlights her ability to address relevant and pressing issues in the digital age. Her proficiency in various programming languages and her analytical skills further enhance her capacity to contribute to the academic community meaningfully. While there are opportunities for growth in expanding her research scope and increasing her academic visibility, her achievements and dedication to student development are commendable. With the support and recognition that the Best Researcher Award could provide, Sinthuja is well-positioned to continue her impactful work, inspire future generations of researchers, and contribute significantly to the advancement of knowledge in the field of information technology.

Yunxiang Lu | neural network dynamics | Best Researcher Award

Posted on by ScienceFather

Dr. Yunxiang Lu | neural network dynamics | Best Researcher Award 

at Nanjing University of Posts and Telecommunications, China.

Dr. Yunxiang Lu is an accomplished scholar in Control Science and Engineering, currently pursuing a combined Master and Ph.D. program at the College of Automation and Artificial Intelligence at Nanjing University of Posts and Telecommunications, China. His research focuses on nonlinear dynamic systems, bifurcation theory, and the application of control systems in ecological and biological networks. Throughout his academic career, Yunxiang has demonstrated his proficiency through numerous publications in high-impact journals and participation in prestigious conferences. His work contributes significantly to the understanding of neural networks, eco-epidemiological systems, and cyber-physical systems. In addition, Yunxiang has industry experience as a technical engineer, applying advanced control theories in real-world projects like smart factories powered by 5G technology.

Profile

Scopus

ORCID

Education 

Yunxiang Lu is currently pursuing a combined Master and Ph.D. degree in Control Science and Engineering at Nanjing University of Posts and Telecommunications. His studies cover diverse areas such as matrix theory, bifurcation of nonlinear dynamic systems, and adaptive control. Throughout his education, Yunxiang has excelled in courses like Image Analysis and Understanding, Nonlinear Systems and Chaos Control, and Optimization Methods, reflecting his deep understanding of advanced control theories. His exceptional academic performance includes top grades in Matrix Theory (100), Linear System Theory (95), and Image Analysis and Understanding (95), indicating his strong analytical and mathematical capabilities. His educational background equips him to analyze complex networks and systems, which are fundamental to his research in ecological competition networks and neural systems.

Experience 

Yunxiang Lu has gained practical experience through his role as an IT Technical Engineer at China Telecom Corporation’s Nanjing Branch. In this position, he contributed to the 5G+MEC smart factory project, where he applied his knowledge in telecommunications and control systems to enhance smart factory operations. Yunxiang participated in developing a 5G+MEC virtual private network, integrating 5G wireless scanning guns and machine vision systems, which underscores his ability to apply cutting-edge technologies in real-world environments. In academia, Yunxiang presided over the Postgraduate Research and Practice Innovation Program of Jiangsu Province, leading research on bifurcation control in fractional-order ecological networks. His ability to balance academic research with practical engineering projects reflects his diverse expertise and versatility.

Research Interests 

Yunxiang Lu’s research is primarily focused on control theory, bifurcation dynamics, and ecological and biological systems. He is particularly interested in the dynamical behavior of complex networks, such as ecological competition networks and neural networks, under various influences like fractional orders and time delays. His work explores how network topology and control strategies affect the stability and evolution of these systems. Yunxiang has also ventured into cyber-physical systems, investigating tipping points and bifurcation mechanisms in networks. His research aims to develop optimized control strategies for managing the dynamics of anomalous diffusion systems, which include neural networks and ecological competition networks, contributing to both theoretical advancements and practical applications in system stability and control.

Awards 

Yunxiang Lu has received multiple prestigious awards for his academic excellence. In 2022, he was honored as an Excellent Graduate by Nanjing University of Posts and Telecommunications, a reflection of his outstanding performance throughout his Ph.D. program. He was also recognized as an Excellent Postgraduate in both 2021 and 2020, receiving second prizes in the university’s Postgraduate Academic Scholarship competition during those years. These accolades underscore his dedication to academic success and research excellence. Yunxiang’s continuous recognition over the years highlights his consistency and high academic standards, making him a standout student in the College of Automation and Artificial Intelligence.

Publications 

Dr. Yunxiang Lu has contributed extensively to high-impact research in nonlinear systems and control theory. His key publications include:

 

  1. “Stability and bifurcation exploration of delayed neural networks with radial-ring configuration and bidirectional coupling”, IEEE Transactions on Neural Networks and Learning Systems, 2023, in press.
    • Cited by: 10
  2. “A delayed eco-epidemiological competition network with reaction-diffusion terms: Tipping anticipation”, Applied and Computational Mathematics, 2023, accepted.
    • Cited by: 7
  3. “Hybrid control synthesis for Turing instability and Hopf bifurcation of marine planktonic ecosystems with diffusion”, IEEE Access, 2021, 9: 111326-111335.
    • Cited by: 15
  4. “Hopf bifurcation of biological competition network with independent non-cross propagation characteristics”, Complex System and Complexity Science, 2022, 19(1): 1-11.
    • Cited by: 5

Conclusion

Yunxiang Lu, Ph.D., is a strong candidate for the Best Researcher Award, given his extensive contributions to the fields of control science, nonlinear systems, and neural network modeling. His technical expertise, research leadership, and publication record in high-impact journals demonstrate his commitment to advancing scientific knowledge. With a focus on expanding his research’s practical and interdisciplinary impact, he would be a highly deserving recipient of this award.

Amal Shaheen | Machine Learning AI | Excellence in Research

Posted on by ScienceFather

Amal Shaheen | Machine Learning AI | Excellence in Research

Doctrate at UOB, Bahrain.

Amal Shaheen is a distinguished AI Transformation Strategy Leader and Big Data Analytics Expert with over 25 years of experience in government, business, and IT sectors. Renowned for her innovative thinking and strategic vision, she combines practical experience with academic expertise in AI, Machine Learning, and Project Management. Amal excels in driving AI transformation strategies, enhancing organizational efficiency, and overseeing complex projects to achieve impactful outcomes. Her leadership style emphasizes empowerment, collaboration, and resilience, allowing her to navigate dynamic environments effectively. As a current lecturer at the University of Bahrain, she is passionate about guiding students in Project Management and Big Data Analytics, preparing them for successful careers in technology. With a commitment to sustainable growth and continuous improvement, Amal is dedicated to advancing her field and contributing to impactful research and education.

Profile👤

Orcid

Education📝

Amal Shaheen holds a Ph.D. in Computing and Information Technology with a focus on AI and Machine Learning from the University of Bahrain, where she is expected to graduate in December 2024. Her thesis explores novel models in Graph Deep Learning based on Autoencoders, showcasing her commitment to advancing knowledge in the field. She also possesses an MBA in Management Information Systems from the New York Institute of Technology, Bahrain, which complements her technical expertise with essential management skills. Furthermore, her educational background includes a Bachelor’s degree in Computer Science from the University of Qatar. To further enhance her qualifications, Amal has obtained various certifications, including AI Transformation Leader from the United States AI Institute and Professional Co-Active Coach Certified in Leadership. Her diverse education equips her with a strong foundation to excel in both academic and professional environments.

Experience👨‍🏫

Amal Shaheen has amassed extensive experience across various leadership roles, demonstrating her capabilities in both academic and governmental sectors. Currently, she serves as a lecturer at the University of Bahrain, guiding students in Project Management and Big Data Analytics, where she blends practical insights with academic rigor. Previously, she held significant positions at the Civil Service Bureau, including Director of the Management Information Directorate and Acting Director of the Organizational Performance Directorate. In these roles, she managed IT processes, developed strategic business initiatives, and led the transformation of manual services to electronic workflows. Additionally, she spearheaded multiple civil service projects, ensuring their successful implementation and alignment with organizational goals. Her rich background reflects her ability to oversee complex plans, drive innovative solutions, and enhance operational efficiency, establishing her as a prominent leader in her field.

Research Interest🔬 

Amal Shaheen’s research interests lie at the intersection of AI, Big Data Analytics, and Machine Learning, with a focus on developing innovative solutions to real-world challenges. Her current research delves into Graph Deep Learning, exploring novel models that leverage Autoencoders to enhance predictive capabilities and data analysis. Amal is particularly passionate about the application of AI in government and public services, aiming to streamline processes and improve decision-making through data-driven insights. She is also interested in sustainable technology and its role in fostering organizational growth and efficiency. By bridging theoretical knowledge and practical application, Amal aims to contribute significantly to advancing research in AI and data analytics. Her commitment to mentorship and student engagement further enhances her research endeavors, as she encourages the next generation of researchers to explore innovative approaches in their studies and projects.

Awards and Honors🏆

Throughout her illustrious career, Amal Shaheen has received numerous awards and honors in recognition of her contributions to AI, Big Data Analytics, and public service transformation. Among her notable achievements is her designation as an AI Transformation Leader from the United States AI Institute, highlighting her expertise in driving technological advancements. Additionally, she has completed various training programs in leadership, project management, and strategic planning, earning accolades for her commitment to excellence and innovation. Amal’s leadership in spearheading successful civil service initiatives has garnered recognition from government authorities, underscoring her impact on organizational efficiency and effectiveness. Her contributions to education have also been acknowledged, as she continues to inspire students and foster a culture of learning and growth. These accolades reflect her dedication to advancing knowledge and driving positive change within her field.

Skills🛠️

Amal Shaheen possesses a diverse skill set that positions her as a leader in the fields of AI, Big Data Analytics, and Project Management. Her technical skills include proficiency in advanced AI frameworks, Machine Learning models, and data analysis tools such as Spark, Hadoop, Python, and R. Additionally, Amal has strong project management skills, enabling her to guide complex initiatives from conception to execution while ensuring quality and adherence to deadlines. Her leadership abilities are complemented by exceptional interpersonal skills, fostering collaboration and teamwork among colleagues and students. Detail-oriented and adaptable, she thrives in dynamic environments, embracing change and finding innovative solutions to challenges. Furthermore, Amal’s analytical thinking, strategic planning, and problem-solving skills equip her to identify and capitalize on opportunities for improvement and growth within organizations. This well-rounded skill set enables her to drive impactful projects and contribute to advancements in her field.

Conclusion 🔍 

In conclusion, Amal Shaheen exemplifies excellence in her roles as an AI Transformation Strategy Leader, educator, and researcher. With over 25 years of experience, she brings a wealth of knowledge and expertise to the fields of AI, Big Data Analytics, and Project Management. Her innovative mindset, strong leadership skills, and commitment to mentorship position her as a role model for aspiring professionals. Amal’s ongoing research endeavors and dedication to advancing technology for organizational efficiency reflect her passion for creating meaningful impacts in both academic and governmental sectors. As she continues her journey, her contributions to the field of AI and her commitment to nurturing the next generation of leaders are sure to leave a lasting legacy. Amal Shaheen stands poised to drive further innovations and advancements in her field, making her a deserving candidate for recognition in excellence in research.

Publication Top Notes

Title: “Innovative Approaches to Big Data Analytics in Public Sector Applications”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Innovative Approaches to Big Data Analytics in Public Sector Applications. Journal of Government Information, 45(2), 101-115.

Title: “Graph Deep Learning: Novel Models Based on Autoencoder Framework”
Author: Amal Shaheen
Year: 2024
Citation: Shaheen, A. (2024). Graph Deep Learning: Novel Models Based on Autoencoder Framework. International Journal of Artificial Intelligence Research, 12(1), 45-59.

Title: “Transforming HR Processes: The Role of AI in Government Agencies”
Author: Amal Shaheen
Year: 2022
Citation: Shaheen, A. (2022). Transforming HR Processes: The Role of AI in Government Agencies. Journal of Public Administration Research and Theory, 34(3), 375-392.

Title: “AI and Machine Learning in Data-Driven Decision Making”
Author: Amal Shaheen
Year: 2021
Citation: Shaheen, A. (2021). AI and Machine Learning in Data-Driven Decision Making. Computing and Informatics, 40(4), 777-794.

Title: “Project Management Best Practices in AI Implementation”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Project Management Best Practices in AI Implementation. Project Management Journal, 54(1), 28-39.