Yongfeng Li | Mathematics | Best Researcher Award

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Prof. Dr. Yongfeng Li | Mathematics | Best Researcher Award

Zhengzhou University of Light Industry, China

Professor Yongfeng Li is a distinguished academic and researcher in the field of mathematics, currently serving at Zhengzhou University of Light Industry. With over two decades of teaching and research experience, she has made significant contributions in biomathematics, particularly in population ecology and infectious disease dynamics. She is a master’s supervisor, recognized as a young backbone teacher in Henan Province, and has been acknowledged as an Outstanding Postgraduate Supervisor at her institution. Her international academic exposure includes a year as a visiting scholar at York University, Canada, supported by the China Scholarship Council. Professor Li has successfully led multiple funded projects, including a major one supported by the National Natural Science Foundation of China. In addition to her research accomplishments, she is dedicated to teaching, having instructed both undergraduate and postgraduate courses in core mathematical disciplines. She has published more than 40 research papers in reputable journals and contributed to textbook development. Professor Li has actively guided students in academic competitions, earning institutional and provincial recognition. Her service as a journal reviewer underscores her standing in the academic community. Overall, Professor Li’s profile reflects a balance of research excellence, educational leadership, and international engagement.

Professional Profile

Education

Yongfeng Li pursued her academic journey in mathematics, culminating in a Ph.D. from Nanjing Normal University between 2006 and 2009. Prior to that, she earned her Master’s degree in Mathematics from Xinyang Normal University from 2003 to 2006. She also completed her Bachelor’s degree in Mathematics from the same institution between 1999 and 2003. Her educational path reflects a continuous and focused engagement in mathematical sciences, providing her with a solid foundation in both theoretical and applied aspects of the field. Each stage of her academic progression contributed to her growing interest in biomathematics and mathematical modeling. During her doctoral studies, she likely concentrated on more specialized topics in ordinary and partial differential equations, which now serve as the theoretical backbone of her current research in infectious disease dynamics and population ecology. Her educational background not only prepared her for a successful academic career but also equipped her with the tools to contribute meaningfully to applied mathematical problems. The institutions she attended are known for their rigorous programs in science and education, ensuring that she developed both deep disciplinary knowledge and the capacity for interdisciplinary research.

Professional Experience

Since 1999, Professor Yongfeng Li has been affiliated with Zhengzhou University of Light Industry, where she has built a robust academic and research career. Over the years, she has assumed various academic roles, advancing from a teaching position to becoming a full professor and a postgraduate supervisor. Her experience spans teaching undergraduate and postgraduate students, conducting independent and collaborative research, and guiding students in competitive academic environments. From July 2015 to July 2016, she broadened her global academic perspective as a visiting scholar at York University in Canada, under the sponsorship of the China Scholarship Council. This experience enriched her research methodologies and established valuable international academic networks. Throughout her career, Professor Li has been involved in developing and delivering a wide range of mathematics courses, such as Mathematical Analysis, Advanced Mathematics, and Differential Equations. Her practical experience is complemented by administrative and mentoring responsibilities, contributing to the academic governance and development of her department. In addition to her university role, she has contributed to the wider academic community as a reviewer for international journals. Her professional journey reflects dedication to both academic excellence and student development within a structured and evolving academic environment.

Research Interests

Professor Yongfeng Li’s primary research interests lie in the domain of biomathematics, with a specific focus on mathematical modeling in population ecology and infectious disease dynamics. Her work involves developing and analyzing differential equation models to understand complex biological and epidemiological systems. These models help in simulating and predicting the behavior of diseases or populations under varying conditions, contributing to public health strategies and environmental management. Her research bridges theoretical mathematics with real-world biological phenomena, offering insights into how mathematical tools can be applied to address pressing scientific and societal problems. Additionally, she explores the stability, bifurcation, and long-term behavior of nonlinear dynamic systems, particularly in delayed and impulsive differential equations. This reflects a strong foundation in both pure and applied mathematics. Professor Li’s interest in mathematical modeling has also extended into interdisciplinary projects, allowing for collaboration with professionals in biology, medicine, and environmental sciences. Her ability to contextualize mathematics in biological systems has enabled her to lead and contribute to research that is both academically rigorous and socially relevant. These interests underscore her commitment to research that informs practice and policy while advancing mathematical theory.

Research Skills

Professor Yongfeng Li possesses a diverse and comprehensive set of research skills rooted in advanced mathematical analysis, modeling, and applied mathematics. She is highly proficient in developing mathematical models for biological systems, particularly using ordinary differential equations (ODEs), delay differential equations (DDEs), and impulsive differential equations to describe population dynamics and the spread of infectious diseases. Her expertise extends to qualitative and stability analysis of nonlinear systems, bifurcation theory, and numerical simulations. These skills are crucial in assessing the robustness, equilibrium, and long-term behavior of modeled phenomena. She is also adept at using mathematical software tools such as MATLAB and Mathematica to perform simulations, verify theoretical findings, and visualize results. Her strong analytical thinking and problem-solving ability enable her to tackle complex interdisciplinary questions, often in collaboration with experts from the life sciences. As a reviewer for international journals, she demonstrates a refined skill in critical analysis and scholarly evaluation. Furthermore, her experience in curriculum development and textbook compilation reflects her ability to translate complex research into educational content. These competencies collectively enable her to conduct impactful research, contribute to academic discourse, and mentor future scholars effectively.

Awards and Honors

Professor Yongfeng Li has received numerous awards and recognitions throughout her career, highlighting her excellence in teaching, research, and mentorship. In 2023, she was honored as an Outstanding Postgraduate Supervisor by Zhengzhou University of Light Industry, acknowledging her significant role in graduate education and student development. She was also recognized as an Outstanding Instructor in the 2021 National College Students’ Mathematics Competition, reflecting her effectiveness in mentoring students for high-level academic competitions. In 2019, she won the Second Prize in the Fifth Mathematics Micro-course Teaching Design Competition in Henan Province, which demonstrates her innovative approach to teaching. Notably, she was selected as a Young Backbone Teacher by the Henan provincial education authority in 2017, a designation that identifies promising academic leaders. Earlier in her career, she contributed to a project that received the First Prize for Scientific and Technological Achievements from the Education Department of Henan Province in 2013. These accolades underline her consistent performance, leadership, and contributions to both academic scholarship and student success. They also signify her standing as a respected member of the higher education and research community in China.

Conclusion

Professor Yongfeng Li’s academic journey exemplifies dedication, excellence, and impact across teaching, research, and mentorship. With a solid foundation in mathematics and a clear focus on biomathematics, she has consistently contributed to the advancement of knowledge through publications, funded projects, and interdisciplinary applications. Her ability to lead research teams, supervise graduate students, and guide undergraduates in national competitions speaks to her well-rounded academic profile. Her career has been marked by recognition at institutional and provincial levels, reflecting both her scholarly output and her role in nurturing academic talent. International exposure as a visiting scholar has broadened her perspective, while her ongoing role as a journal reviewer ensures she remains actively engaged with current research trends. Though her profile could benefit from further international collaborations and publications in top-tier journals, her current achievements make her a strong candidate for any research-based recognition. Her work contributes not only to the theoretical foundations of mathematics but also to practical solutions in population and health sciences. Professor Yongfeng Li stands out as a committed educator and researcher whose accomplishments align well with the standards of excellence for the Best Researcher Award.

Publications Top Notes

  • Title: Dynamical analysis of a plateau pika disease model with time delay
    Journal: Advances in Continuous and Discrete Models

  • Title: Dynamics of a Filippov airborne infectious disease model with triple-threshold control strategy
    Journal: Journal of Biological Systems

 

Issa Bamia | Mathematics | Best Researcher Award

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Mr. Issa Bamia | Mathematics | Best Researcher Award

Data Scientist at African Institute for Mathematical Sciences, Mali.

Issa Bamia is a mathematician and data scientist with a deep passion for advancing research in adversarial machine learning and AI security. His expertise spans data engineering, digital health solutions, and cloud-based pipeline architecture, with a focus on addressing real-world issues in healthcare and telecommunications. With significant hands-on experience, Issa has optimized data collection processes, improved decision-making tools, and contributed to impactful projects that prioritize AI safety. His work as a data engineer for Muso Health demonstrates his commitment to using data-driven insights for tangible improvements in public health. Furthermore, he has a strong foundation in advanced data science and machine learning techniques, including proficiency with large language models (LLMs), security frameworks, and virtualization. This experience, combined with his commitment to ongoing research and development, positions Issa as a promising figure in the fields of AI safety and adversarial machine learning.

Professional Profile

Education

Issa Bamia holds a Master’s in Mathematical Sciences with a specialization in Data Science from the African Institute for Mathematical Sciences (AIMS), an institution renowned for its focus on African mathematicians and scientists. His education at AIMS included a rigorous curriculum that equipped him with the analytical and technical skills needed for advanced data science research and practical applications. He gained specialized knowledge in AI and adversarial machine learning, which he applied in his professional projects to develop data-driven solutions that impact digital health. Before this, he completed a Bachelor’s degree in Electronic Information Engineering from Tianjin University, where he gained foundational knowledge in data management and engineering principles. Issa’s educational background is complemented by certifications, including a professional certification in Large Language Models (LLMs) from Databricks, which has further refined his ability to work with complex AI models and large datasets. His diverse academic and practical training has laid a strong foundation for his research and professional pursuits in data science and AI security.

Professional Experience

Issa Bamia has a diverse professional background spanning data engineering, software development, and account management. Currently, he works as a data engineer for Muso Health, where he streamlines data collection, optimizes cloud-based data pipelines, and develops dashboards for real-time healthcare data analysis. His work here has been instrumental in improving medication stock management and reducing stockouts, enhancing healthcare delivery for underserved populations. Prior to this, Issa worked as an account manager with Huawei Technologies, where he customized technological solutions to meet telecom operators’ needs, ensuring smooth service delivery and strong client relations. Earlier, he was a software engineer with Whale Cloud Technologies, where he worked on the deployment and maintenance of cloud-based software products and managed system and database maintenance. Throughout these roles, Issa demonstrated an ability to handle complex data infrastructures and security protocols, showcasing his expertise in data science and its applications in both healthcare and telecommunications.

Research Interest

Issa Bamia’s primary research interests lie in adversarial machine learning, AI safety, and the development of secure, resilient AI models. His focus is on understanding and mitigating vulnerabilities in AI systems, particularly those posed by adversarial attacks, which can manipulate machine learning models to produce inaccurate or biased outcomes. He is passionate about exploring solutions that bolster the security and reliability of AI, especially in applications related to digital health, where data integrity is critical for decision-making. Issa is also interested in the ethical and practical implications of AI security, as well as the ongoing evolution of AI governance and control frameworks. Additionally, he seeks to apply his expertise in large language models (LLMs) to further enhance AI’s adaptability and reliability. His dedication to AI safety underscores a commitment to building AI systems that prioritize both performance and ethical responsibility, which is particularly significant in fields like healthcare, where secure and trustworthy AI systems are essential.

Research Skills

Issa possesses a robust set of research skills that are integral to his work in adversarial machine learning and AI security. He is proficient in cloud-based technologies and data pipeline design, with extensive experience in platforms such as Google Cloud Platform (GCP) and Apache Airflow. His technical repertoire includes advanced machine learning frameworks and tools for large language models (LLMs), containerization through Docker, and security protocols that support secure data architectures. In addition to data engineering skills, he has a strong command of SQL, NoSQL, Linux, and various programming languages including Python and JavaScript. Issa is adept at working with virtualization, networking, and incident response, which are crucial in managing and securing complex data systems. His hands-on experience with tools like Looker, Spark, and Hadoop further enhances his capability to analyze, optimize, and visualize large datasets, supporting his research pursuits in AI and data security. His skills in agile project tracking and stakeholder engagement also enable him to lead projects effectively and ensure that his research aligns with organizational goals.

Awards and Honors

Throughout his career, Issa has earned recognition for his contributions to data science and digital health innovation. His academic achievements include a Master’s degree in Mathematical Sciences (Data Science) from the African Institute for Mathematical Sciences (AIMS), an honor that highlights his academic commitment to data science research. While at AIMS, Issa developed a data-driven solution for medication stock management at Muso Health, a project that successfully reduced stockouts and improved patient care outcomes, marking a significant professional achievement in public health. His commitment to professional growth is also evident in his completion of the Databricks Professional Certificate in Large Language Models (LLMs), which reflects his proficiency in implementing, fine-tuning, and managing LLMs in various AI applications. This certification is a testament to his dedication to staying updated with advancements in AI, particularly in AI security, which is a key area of his research focus. These achievements underscore Issa’s commitment to both academic excellence and impactful, socially relevant research.

Conclusion

Issa Bamia’s background in adversarial machine learning, practical impact in digital health, and strong technical skill set make him a strong contender for the Best Researcher Award. His work on AI safety, coupled with impactful public health solutions, aligns well with the criteria for this award. Strengthening his research profile with further publications and collaborations would elevate his contributions in this competitive field. Overall, he demonstrates the qualities of an innovative and impactful researcher.