Assist Prof Dr. Meryem YANKOL SCHALCK |Decision-making and Problem-solving |Best Researcher Award| 355
IPAG Business Schoolm, France
Profile
Early Academic Pursuits 🎓
Meryem Yankol Schalck’s journey in academia began with a solid foundation in mathematics. She earned her Master’s degree in Mathematics from the University of Marmara in Istanbul, followed by a Master’s in Mathematical Engineering, specializing in Applied Statistics, from Paris-Sud University. These early academic pursuits provided her with the necessary analytical and statistical expertise to navigate the complex world of data science. Over time, she expanded her knowledge base by obtaining a Data Science Certificate from The Institute of Risk Management (IRM), further refining her skills in risk assessment and data-driven decision-making. Her academic ambition culminated in a Ph.D. in Econometrics and Machine Learning from the University of Orleans, where she focused on pioneering research in financial fraud detection and survival analysis in insurance industries under the supervision of S. Tokpavi.
Professional Endeavors 💼
With nearly 15 years of professional experience in the insurance sector, Meryem Yankol Schalck has honed her expertise in statistical modeling and advanced analytics. She has worked extensively in risk assessment, fraud detection, and predictive analytics, implementing cutting-edge machine learning models to enhance business efficiency. Her proficiency in leveraging data-driven insights has positioned her as a key player in insurance analytics, where she has contributed significantly to the industry’s ability to mitigate risks and optimize financial performance. As an Assistant Professor in Data Science, she continues to bridge the gap between industry and academia, ensuring that her students gain practical insights into real-world applications of data science.
Contributions and Research Focus 🔬
Meryem Yankol Schalck’s research is centered on artificial intelligence applications in business and finance. She has published extensively in academic journals, contributing valuable insights into machine learning methodologies for fraud detection and risk assessment. Her doctoral research introduced innovative approaches to financial fraud detection and survival analysis, providing industry professionals with novel techniques to enhance security and operational efficiency. She is also actively involved in European research projects, focusing on AI-driven financial solutions and digital transformation strategies.
Accolades and Recognition 🏆
Meryem has earned recognition for her work in both academic and professional circles. Her research contributions have been acknowledged in leading conferences and publications, making her a respected voice in the field of AI and data science. Additionally, her commitment to academic excellence has made her a sought-after speaker at international seminars and workshops, where she shares her insights on AI-driven financial innovations.
Impact and Influence 🌐
Beyond her technical expertise, Meryem is known for her ability to impart knowledge effectively. She has demonstrated strong pedagogical skills, incorporating digital innovations into her teaching methodologies. Her ability to simplify complex machine learning concepts has benefited students across various academic programs, especially those learning in English. Through her mentorship and guidance, she has played a significant role in shaping the next generation of data scientists and analysts.
Legacy and Future Contributions 🌟
As Meryem Yankol Schalck continues to excel in her academic and professional journey, her legacy is one of innovation, excellence, and commitment to education. She remains dedicated to advancing research in AI applications for business and finance, ensuring that data science remains at the forefront of industry evolution. Moving forward, she aims to further her involvement in European research projects, contribute to global discussions on AI ethics, and continue inspiring future professionals in the field of data science. Through her work, she is not only shaping the present landscape of data science but also paving the way for its future advancements.
