Dr. Priya Verma is an Assistant Professor of Data Analytics at the Centre for Management Studies, Administrative Staff College of India (ASCI), Hyderabad. She earned a Ph.D. in Data Science and Applied Machine Learning from IIT Hyderabad, followed by a Post-Doctoral Fellowship at the same institution. Dr. Verma also holds a Dual Degree (B. Tech + M. Tech) in Computer Science Engineering from Jayoti Vidyapeeth Women’s University, Jaipur, and has completed Executive Education in Applied Business Analytics from the Indian School of Business (ISB). Additionally, she has undertaken a Faculty Development Program (FDP) in Machine Learning with Business Applications from the Indian Institute of Management Bangalore (IIM-B). With over nine years of diverse experience in research, teaching, and industry, Dr. Verma has been associated with leading business schools, including ICFAI University (Hyderabad), Welingkar Institute of Management Development and Research (WeSchool, Mumbai), and the Institute of Insurance and Risk Management (IIRM, Hyderabad). Her academic expertise spans Data Analytics, Applied Machine Learning, and Fraud Analytics. During her Ph.D. and postdoctoral research at IIT Hyderabad, Dr. Verma collaborated with the Government of Telangana, analysing extensive GST datasets using big data analytics and social network analysis techniques. Her contributions led to a significant enhancement in the state's revenue. She has authored more than 20 research papers published in Springer and IEEE and has presented her work at prestigious international conferences across the US, UK, Spain, Italy, and Japan. Dr. Verma has played a key role in conducting certification courses in business analytics for professionals and has extensive experience in teaching MBA students and executives through courses, workshops, and webinars. Her teaching portfolio includes Machine Learning using R, Artificial Intelligence, Insurance Analytics with Python and R, Fraud and Risk Analytics, Fintech Technologies, and Data Mining. Passionate about research, she continues to explore new applications of machine learning to solve real-world challenges.