Dr. AHMADOU MUSTAPHA FONTON MOFFO | Machines Learning | Best Researcher Award

Economist | UNESCO | Canada

Short Bio 🌟

Ahmadou Mustapha FONTON is a distinguished economist based in Montréal, Canada, with a Ph.D. in Economics from the Université du Québec à Montréal. Specializing in macroeconomics, financial economics, and applied econometrics, FONTON excels in leveraging machine learning and big data to inform policy decisions and develop robust risk models. His extensive professional experience includes roles at UNESCO and the Ministry of Scientific Research in Cameroon, reflecting his dedication to advancing economic research and policy.

Profile

Google Scholar

Strengths for the Award

Extensive Expertise and Experience: Dr. Fonton brings a wealth of experience in both academic and non-academic settings. His role as an economist at UNESCO and previous positions demonstrate a solid track record in applied econometrics, macroeconomics, and financial economics. His contributions to data collection, statistical analysis, and policy evaluation underscore his broad expertise.
Advanced Technical Skills: His proficiency with a diverse set of software tools (PYTHON, R, MATLAB, STATA, SPSS, etc.) and techniques, including machine learning and big data analysis, highlights his technical acumen. This expertise is critical for modern economic research, especially in forecasting and analyzing complex economic phenomena.
Strong Research Output: Dr. Fonton’s publication record, including his recent work on machine learning in stress testing US banks, demonstrates his ability to contribute valuable insights to the field of economics. His working papers and conference presentations further reflect his active engagement in cutting-edge research.
Academic and Teaching Experience: His roles as a research assistant and instructor at Université du Québec à Montréal and Institut Siantou Superieur show a strong background in teaching and mentoring. This experience is important for fostering new talent and advancing the field through education.
International Perspective and Multilingual Skills: Dr. Fonton’s international experience, combined with his multilingual abilities (English, French, and Bamoun), provides him with a unique perspective on global economic issues. This is especially relevant in the context of UNESCO’s work and cross-border research collaborations.
Policy Impact: His involvement in projects that influence policy, such as his work on forecasting time series for UNESCO and his previous consulting roles, indicates a strong capacity for translating research into practical recommendations. This aligns well with the goals of the Research for Best Researcher Award, which often emphasizes practical impacts of research.

Areas for Improvement

Broader Publication Record: While Dr. Fonton has a notable publication in the International Review of Financial Analysis and several working papers, increasing his publication count in high-impact journals could strengthen his profile further. Broadening his research topics or collaborating on interdisciplinary studies might also enhance his visibility in different research circles.
Increased Collaboration and Networking: Engaging in more collaborative research projects and expanding his network within the global research community could open up additional opportunities for impactful research and visibility. This could involve co-authoring papers with researchers from diverse backgrounds or participating in more international conferences.
Focus on Long-term Projects: While Dr. Fonton’s work on various projects is commendable, focusing on longer-term research initiatives might yield more significant and sustained contributions to the field. Developing comprehensive research programs or longitudinal studies could be beneficial.
Enhanced Public Engagement: Increasing efforts to communicate his research findings to the public and policymakers could amplify the impact of his work. This might include writing policy briefs, engaging in media outreach, or participating in public lectures and forums.

Education 🎓

2023: Ph.D. in Economics, Université du Québec à Montréal, Canada
2010: M.Sc. in Economics, Université Catholique de Louvain, Belgium
2005: B.Sc. in Statistics, ISSEA Yaoundé, Cameroon
2000: Certificate in Mathematics, Cameroon

Experience 💼

2023–Present: Economist-Statistician, UNESCO Institute of Statistics, Canada
Leading data collection and processing for Science and Culture Annual Surveys, developing new survey instruments, and producing statistical reports.

2012–2017: Coordinator of Statistical Projects, Ministry of Scientific Research, Cameroon
Directed national statistical surveys, analyzed data on Research and Development, and assisted in organizing expert meetings and seminars.

2009–2012: Economist, Ministry of Economy and Planning, Cameroon
Monitored macroeconomic indicators and developed socio-economic analyses to guide policy decisions.

2008: Credit Analyst, Afriland First Bank, Cameroon
Analyzed credit portfolios and managed risk assessments to support the bank’s credit-granting process.

Research Interests 🔍

Main Interests:

Econometrics (Forecasting, Machine Learning, Big Data Analysis)

Secondary Interests:

Macroeconomics
Microeconometrics
Finance

FONTON’s research integrates advanced econometric models with machine learning techniques to explore macro-financial linkages and evaluate economic policies.

Award 🏅

Ahmadou Mustapha FONTON has been recognized for his contributions to economic research and policy development through various grants and academic accolades. His innovative work in econometrics and machine learning positions him as a leading candidate for prestigious research awards.

Publications 📚

“A machine learning approach in stress testing US bank holding companies” – Accepted for publication in International Review of Financial Analysis (2024). Read Here

Conclusion

Dr. Ahmadou Mustapha FONTON is a highly qualified candidate for the Research for Best Researcher Award. His extensive experience in econometrics, macroeconomics, and financial economics, coupled with his technical skills and policy impact, positions him as a strong contender. His research contributions, combined with his international perspective and teaching experience, align well with the objectives of the award. Addressing the areas for improvement, such as increasing his publication record and expanding his collaborative efforts, could further enhance his candidacy. Overall, Dr. Fonton’s profile reflects a distinguished researcher with a promising trajectory in the field of economics.

Mr. Jeanfranco David Farfan Escobedo | Machine Learning | Young Scientist Award

Jeanfranco David Farfan at Escobedo State University of Campinas, Brazil

Jeanfranco David Farfan Escobedo is a PhD candidate in Computer Science at the University of Campinas (UNICAMP), Brazil, specializing in deep learning techniques for uncertainty reduction in oil reservoir simulations. He holds an M.Sc. in Computer Science from UNICAMP with a thesis in Conversational Systems and a B.Sc. in Computer and Systems Engineering from Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Peru, focusing on Computer Vision. Jeanfranco’s professional journey includes roles as a researcher at Shell Oil Company, Brazil, and teaching positions at UNICAMP and UTEC, Peru. He has received prestigious awards such as the Shell Oil Company Industry Research Scholarship and has contributed to significant publications in applied computing and artificial intelligence journals. His research timeline demonstrates continuous engagement in advancing deep learning, natural language processing, and computer vision fields.

Author Profile

Google Scholar Profile

Education

Jeanfranco David Farfan Escobedo is currently pursuing a PhD in Computer Science at the University of Campinas (UNICAMP), Brazil. He earned his Master of Science degree in Computer Science from UNICAMP, focusing on Conversational Systems. Previously, he obtained a Bachelor of Science in Computer and Systems Engineering from Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Peru, with a thesis in Computer Vision.

Research Focus

Jeanfranco’s research primarily revolves around applying deep learning techniques to reduce uncertainty in oil reservoir simulations. Additionally, he explores topics in natural language processing, focusing on conversational systems, and computer vision for tasks like image recognition.

Professional Journey

Jeanfranco has accumulated diverse professional experiences. He currently works as a researcher at Shell Oil Company in Brazil, specializing in utilizing deep learning for improving oil reservoir simulations. He has also served as a Teaching Assistant at UNICAMP, where he supported courses in Algorithms and Computer Programming. Furthermore, he has taught Machine/Deep Learning at the Artificial Intelligence University of Engineering and Technology (UTEC) in Peru.

Honors & Awards

Jeanfranco has received several notable awards, including the Shell Oil Company Industry Research Scholarship in 2021, the Sinch Latin America Industry Research Scholarship in 2019, and first place in the AgroHack hackathon for developing a plant disease monitoring app in 2018.

Publications Noted & Contributions

Jeanfranco has contributed significantly to academic publications, including:

“Towards accurate building recognition using convolutional neural networks” (2017) at IEEE XXIV International Conference on Electronics, Electrical Engineering and Computing, showcasing advancements in image recognition through convolutional neural networks.
“A new method of classification with rejection applied to building images recognition based on Transfer Learning” (2018) at IEEE XXV International Conference on Electronics, Electrical Engineering and Computing, presenting innovative techniques in classification using transfer learning.
“Deep hierarchical distillation proxy-oil modeling for heterogeneous carbonate reservoirs” (2023) published in Engineering Applications of Artificial Intelligence, focusing on improving oil reservoir modeling through deep learning techniques.
“Cross-Domain Feature learning and data augmentation for few-shot proxy development in oil industry” (2023) published in Applied Soft Computing, exploring methods to enhance proxy development across different domains within the oil industry.
“Active Learning Approach for Intent Classification in Portuguese Language Conversations” (2021) at IEEE 15th International Conference on Semantic Computing, presenting methodologies for enhancing intent classification in conversational systems using active learning.

Research Timeline

Jeanfranco’s research journey spans from his undergraduate studies through to his current doctoral research. He has consistently explored cutting-edge topics in deep learning, natural language processing, and computer vision, contributing to advancements in these fields.

AHMADOU MUSTAPHA FONTON MOFFO | Machine Learning | Best Researcher Award