Meshesha Zewdie | Development Economics | Best Researcher Award

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Mr. Meshesha Zewdie | Development Economics | Best Researcher Award

Meshesha Zewdie Amare 🇪🇹 is a dedicated economist and researcher specializing in Development Economics. He serves as a Lecturer and Researcher at the Ethiopian Civil Service University, where he also coordinates Master’s programs. With a strong background in microeconomics, econometrics, and policy analysis, he has led various research projects on economic growth, child labor, and foreign direct investment. His extensive work experience spans academia, government, and project coordination roles. He has contributed significantly to national policy discussions through research presentations and training programs.

Profile

Education 🎓

📖 Ph.D. (Development Economics) – Arba Minch University (2020-Present, Defense Pending) 🎓 CGPA: 3.97/4.00
📖 MSc (Development Economics) – Ethiopian Civil Service University (2014-2016) 🎓 CGPA: 4.00/4.00
📖 BSc (Agricultural Economics) – Haramaya University (2005-2011) 🎓 CGPA: 3.49/4.00
📖 Diploma (General Agriculture) – Jimma University (1999-2001) 🎓 CGPA: 3.88/4.00

Experience 👨‍🏫

👨‍🏫 Lecturer & Researcher – Ethiopian Civil Service University (2016-Present)
📌 Teaching economics, program coordination, and leading major research projects
📌 Conducting grand research on child labor and foreign direct investment
📌 Delivering training on STATA & SPSS for research professionals

📊 Planning & Monitoring Expert – Sululta Town Administration (2009-2014)
📌 Managing MSE projects, business plan development, and government project evaluations

🌱 WFP-MERET & UNDP Coordinator – Bureau of Agriculture (2002-2009)
📌 Overseeing rural development projects and coordinating agricultural programs

Research Interests 🔬

📊 Economic Growth & Development – Impact of resource endowments on African economies
👶 Child Labor & Socioeconomic Policies – Analyzing labor exploitation in Addis Ababa
💰 Foreign Direct Investment – Attraction, retention, and corporate responsibility in Ethiopia
📈 Entrepreneurship & MSMEs – Investigating micro and small enterprise dynamics post-COVID
📊 Statistical & Econometric Modeling – Applying STATA, SPSS, and policy impact evaluation

Awards & Recognitions 🏅

🏆 Outstanding Academic Excellence (CGPA 4.00/4.00) – MSc at ECSU
🏆 Best Research Presentation – Ethiopian Civil Service University (2022)
🏆 Certificate of Excellence – 11th Biennial Microfinance Conference (2022)
🏆 Best Policy Impact Evaluation Trainee – Ethiopian Economic Association (2023)
🏆 Numerous Certifications in Research & Project Management

Publications 📚

  • 1.Amare, M.Z., Mulugeta, W. & Mencha, M. Nexus
    between natural resource endowments and economic
    growth in selected African countries. Discov Sustain 5,
    255 (2024). https://doi.org/10.1007/s43621-024-00448-3
  • Meshesha Z.,and Dessalegn Sh.(2020) Graduate
    Unemployment and Its Duration: Evidence from
    Selected Cities of Oromia National Regional State.
    Journal of African Development studies (JADS) Volume
    7, No. 2, Dec 2020. ISSN: 2079-0155 (print): 2710-
    0022(Online) Website:
    http://ejol.aau.edu.et/index.php/JADS/index
  • Meshesha, Z.,and Dessalegn, Sh.(2021). Saving
    Behavior of Women Entrepreneurs in Addis Ababa,
    Ethiopia. Journal of Economics and Sustainable
    Development: ISSN 2222-1700 (Paper) ISSN 2222-
    2855 (Online) Vol.12, No.20, 2021www.iiste.org.
  • Meshesha, Z., and Dessalegn. Sh.(2021). Economic
    Effects of COVID-19 on Micro and Small Enterprises in
    Addis Ababa Surrounding Towns of Oromia National
    6 |M e s h e s h a Z e w d i e , c v ( N o v e m b e r , 2 0 2 4 )
    Regional State: JADS Vol 8 No. 2, Dec 2021 Issue; DOI:
    https://doi.org/10.56302/jads.v8i2.3262.

Anne Demulder | Development Economics | Best Researcher Award

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Prof. Anne Demulder | Development Economics | Best Researcher Award

🇧🇪 Anne Demulder, born on September 1, 1957, in Ixelles, Belgium, is a Belgian medical biologist specializing in hematology. She is a faculty member at Université libre de Bruxelles (ULB) and a consultant at LHUB-ULB. With a distinguished career in clinical biology, she has played a key role in hematology diagnostics, research, and laboratory management. Her contributions extend to academia, where she has trained pharmacists and biologists. Fluent in French, Dutch, English, and Spanish, she has also been involved in international medical cooperation.

Profile

Education 🎓

📚 Dr. Demulder earned her MD from ULB in 1982, specializing in clinical biology. She completed postgraduate training in clinical chemistry, bacteriology, radioisotopes, and hematology at CHU Brugmann. In 1990-1991, she pursued postdoctoral research in hematology and endocrinology at the University of Texas Health Science Center, USA. She obtained a Master in Health Institution Management (2012-2013) and has been a clinical biology supervisor at ULB’s Faculty of Pharmacy.

Experience 👨‍🏫

🏥 Dr. Demulder has been a medical biologist at LHUB-ULB since 1992, serving as Chief of Hematology. She supervises hematological diagnostics, oversees laboratory quality assurance, and contributes to medical research. She previously worked as a postdoctoral fellow in the USA (1990-1992) and a resident in hematology at CHU Brugmann (1985-1989). She has played an active role in medical education, training pharmacists, biologists, and clinicians. She also contributed to international academic cooperation, particularly in Burkina Faso and Guinea.

Research Interests 🔬

🧪 Dr. Demulder’s research explores global hemostasis testing for hematologic disorders. She investigates hypercoagulability in sickle cell disease and leukemia patients undergoing asparaginase treatment. Her work also focuses on thrombin generation tests for personalized hemophilia therapy. Recently, she has studied coagulation abnormalities in acute and long COVID patients. Her research aims to enhance diagnostic accuracy and therapeutic approaches in hematology.

Awards & Recognitions 🏅

🎖️ Dr. Demulder has received recognition for her contributions to hematology, clinical biology, and international cooperation. As an academic leader, she played a key role in laboratory standardization (ISO 15189) and was a member of the CHU Brugmann Medical Council. Her work in developing biomedical sciences in Africa through targeted university projects has been widely acknowledged. She has also been a pivotal figure in the integration of hematology services at LHUB-ULB.

Publications 📚

  • Exploring Hypercoagulability in Post-COVID Syndrome (PCS): An Attempt at Unraveling the Endothelial Dysfunction

    Journal of Clinical Medicine
    2025-01-25 | Journal article
    DOI: 10.3390/jcm14030789
    CONTRIBUTORS: Maxim Muys; Anne Demulder; Tatiana Besse-Hammer; Nathalie Ghorra; Laurence Rozen

  • Assessment of Arteriovenous Fistula Maturation in Hemodialysis Patients with Persistently Positive Antiphospholipid Antibody: A Prospective Observational Cohort Study

    Life
    2025-01-24 | Journal article
    DOI: 10.3390/life15020168
    CONTRIBUTORS: Maxime Taghavi; Lucas Jacobs; Saleh Kaysi; Yves Dernier; Edouard Cubilier; Louis Chebli; Marc Laureys; Frédéric Collart; Anne Demulder; Marie-Hélène Antoine et al.

  • Rivaroxaban presents a better pharmacokinetic profile than dabigatran in an obese non-diabetic stroke patient

    Journal of the Neurological Sciences
    2014-11 | Journal article
    DOI: 10.1016/j.jns.2014.09.008
    CONTRIBUTORS: Apostolos Safouris; Anne Demulder; Nikos Triantafyllou; Georgios Tsivgoulis

Meryem Yankol-Schalck | Insurance and Machine Learning | Best Researcher Award

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Assist. Prof. Dr. Meryem Yankol-Schalck | Insurance and Machine Learning | Best Researcher Award

 

Profile

Education

She holds a Ph.D. in Econometrics and Machine Learning from the University of Orleans (2018–2022), where she investigated new machine learning approaches for financial fraud detection and survival analysis in the insurance industry under the supervision of S. Tokpavi. In addition, she earned a Data Science Certificate (Executive) from the Institute of Risk Management (IRM) in 2016–2017. Her academic background also includes a Master’s degree in Mathematical Engineering (Applied Statistics) from Paris-Sud University (2004–2007) and a Master’s degree in Mathematics from the University of Marmara in Istanbul (1995–1999). Since September 2022, she has been an Assistant Professor of Data Science at IPAG Business School in Nice and Paris. With extensive experience in the insurance sector, she integrates her professional insights into the classroom, emphasizing practical AI applications. Her curriculum reflects the latest trends in data science, fostering a dynamic learning environment tailored to students’ needs. She adapts resources and pedagogical methods to specific course objectives, utilizing tools such as Tableau for data visualization and exploring real-world business applications, including Netflix, Uber, ChatGPT, Gemini, and facial recognition technologies.

 

Work experience

She has held various academic and professional roles, combining her expertise in data science, machine learning, and business analytics. From September 2022 to January 2023, she was an adjunct faculty member at the International University of Monaco, where she taught Mathematics for Business. Prior to that, from September 2021 to August 2022, she served as an adjunct faculty member at IPAG Business School (Nice), teaching courses such as “Data Analysis for Business Management” (BBA3), “Data Processing” (MSc, e-learning), “Digital and Sales” (GEP 5th year), and “Introduction to Statistics” (BBA1). Between September 2020 and October 2021, she was an adjunct faculty member at EMLV (Paris), where she taught “Quantitative Data Analytics – SPSS” (GEP 4th year, hybrid learning) and supervised master’s theses for GEP 5th-year students.

In addition to her academic roles, she has extensive experience in the consulting and insurance sectors. From March to November 2020, she worked as a Senior Consultant at Fraeris (Paris), supporting clients in project development and providing technical solutions. She collaborated with the “Caisse de Prévoyance Sociale” (CPS) of French Polynesia, modeling healthcare expenditures using machine learning techniques. She developed predictive models to analyze healthcare costs from both the insured’s and CPS’s perspectives, offering actionable insights and data-driven forecasts to aid long-term financial planning. Prior to that, in 2019–2020, she was a Senior Manager in Pricing & Data P&C at Addactis (Paris), where she supported clients in project development, innovation, and strategic planning. As an expert referent for ADDACTIS® Pricing software, she worked on database processing for BNP Paribas Cardif, facilitating APLe software operations for quarterly account closings.

Memberships and Projects:

• Membership of the American Risk and Insurance Association (ARIA)
• Membership of the academic association AFSE.
• Member of the RED Flag Project of the University of Orléans in cooperation with CRJPothier.
• Participation at 3 Erasmus+ Projects: Artificial Intelligence to support Education (EducAItion).
• Virtual Incubator Tailored to All Entrepreneurs (VITAE).
• Artificial Intelligence in high Education (PRAIME),

Research topics:

Studies focus on the application of data science techniques to business issues, particularly in the insurance
sector, and on climate change. Another topic of study is the relationship between AI and education.

Publication

  • Yankol-Schalck, M. (2023). Auto Insurance Fraud Detection: Leveraging Cost Sensitive and Insensitive
    Algorithms for comprehensive Analysis, Insurance: Mathematics and Economics.(
    (https://www.sciencedirect.com/science/article/abs/pii/S0167668725000216)
    Banulescu‐Radu, D., & Yankol‐Schalck, M. (2024). Practical guideline to efficiently detect insurance fraud
    in the era of machine learning: A household insurance case. Journal of Risk and Insurance, 91(4), 867-
    913.
    Yankol-Schalck, M. (2022). A Fraud Score for the Automobile Insurance Using Machine Learning and
    Cross-Data set Analysis, Research in International Business and Finance, Volume 63, 101769.
    Schalck, C., Yankol-Schalck, M. (2021). Failure Prediction for SME in France: New evidence from
    machine learning techniques, Applied Economics, 53(51), 5948-5963.
    On- going research:
    Yankol-Schalck (2025). Auto Insurance Fraud Detection: Machine Learning and Deep Learning
    Applications, submitted in Journal of Risk and Insurance.
    Schalck, C., Yankol-Schalck, M. (2024). Churn prediction in the French insurance sector using Grabit
    model, revision in Journal of Forecasting.
    Schalck, C., Seungho, L., Yankol-Schalck, M. (2024). Characteristics of firms and climate risk
    management: a machine learning approach. Work in progress for The Journal of Financial Economics.
    Yankol-Schalck M.and Chabert Delio C., (2024). The application of machine learning to analyse changes in
    consumer behaviour in a major crisis. Work in progress.
    Yankol-Schalck M. and Nasseri A. (2024).An investigation into the integration of artificial intelligence in
    education: Implications for teaching and learning methods. Work in progress.