Nurcan Caliskan | Digital Marketing | Women Researcher Award

Prof Dr Nurcan Çalışkan Gazi University, Turkey

Education:

She completed her undergraduate studies in Nursing Principles at Sivas Cumhuriyet University in Turkey from 1994 to 1998. Following her passion for nursing, she pursued a postgraduate degree, specializing in Nursing, with a thesis, at Sivas Cumhuriyet University’s Health Sciences Institute from 1998 to 2001. Building upon her academic foundation, she furthered her expertise by obtaining a doctorate in Nursing from Hacettepe University’s Institute of Health Sciences, focusing on Nursing Principles, between 2003 and 2008. Throughout her educational journey, she demonstrated a commitment to advancing her knowledge and skills in the field of nursing. Her doctoral research likely contributed to the body of knowledge within nursing science, possibly addressing critical areas such as patient care, healthcare policy, or nursing education. With her extensive academic background and dedication to the nursing profession, she is equipped to make meaningful contributions to healthcare practice, research, and education in Turkey and beyond.

Experience:

She currently holds the position of Head of Department at Gazi University, Faculty of Health Sciences, Nursing Department, starting from 2021 and continuing. In this role, she oversees the department’s operations, including curriculum development, faculty management, and research initiatives. Her leadership ensures the delivery of high-quality education and promotes excellence in nursing practice. Prior to her current role, she served at Gazi University, Faculty of Health Sciences, Nursing Department, from 2015 to 2018. During this time, she contributed to the department’s academic programs, teaching courses, mentoring students, and engaging in scholarly activities. Her dedication to nursing education and her commitment to the development of future healthcare professionals were evident throughout her tenure. Throughout her career, she has demonstrated a passion for advancing nursing science and promoting the well-being of individuals and communities. Her expertise in nursing education and her leadership qualities have positioned her as a respected figure within the academic community. She continues to inspire her colleagues and students alike, driving innovation and excellence in nursing education and research at Gazi University.

Adnan Amin | Customer Analytics, Machine Learning, Churn Prediction | Member

Dr Adnan Amin Institute of Management Sciences Peshawar, Pakistan

Adnan Amin earned his M.Sc. in Computer Science from the University of Peshawar in 2008. He received his MS-CS degree (highest 1st class honors with distinction) and a Ph.D. degree (with Scholastic Honours) in data mining and machine learning from the Institute of Management Sciences (IMSciences) Peshawar, Pakistan, in 2015 and 2023, respectively. In November 2015, he joined IMSciences as a lecturer at the Center for Excellence in Information Technology. He is the lead of IM|DigiSol and the faculty adviser for the Computing and Innovation Society (IMCIS) at IMSciences. Before, he worked as an international consultant for curriculum and academic development at the School of ICT, NIMA Kabul, which was connected to the University of Jyvaskyla in Finland. This was part of a World Bank-funded project for Maxwell Stamp PLC, London (Project Code: P102573). Dr. Adnan’s research and innovation interests are industry-driven and cross-disciplinary. He focuses on developing and commercializing digital solutions and data mining/machine learning research innovations for a variety of industries, such as education, telecommunications, and healthcare. He has completed nearly 8 research projects in collaboration with international universities. He has served as the track chair of the WorldCist’21 workshop (LCBUDAMLT), the session chair of the ICITA’22, and a member of the program committees of numerous conferences including WorldCist, SDIWC, and DATA’23. He has (co) authored 29+ publications, including 16 journal articles, 11 conferences, and 2 book chapters in Springer, and obtained nearly 1000 citations with an h-index score of 14 and an i-index score of 16.

Education:

He completed his Ph.D. in Computer Science with a specialization in Data Mining & Machine Learning from the Center for Excellence in IT at the Institute of Management Sciences, Peshawar, Pakistan, in March 2023. His research focused on developing an adaptive learning approach for customer churn prediction using naïve Bayes. Prior to his Ph.D., he earned his MS in Computer Science with the highest 1st class honors and distinction from the same institution in May 2015, where he conducted research on a similar topic. He also holds an M.Sc. in Computer Science from the University of Peshawar, which he completed with a Grade of A+ in March 2008.

🌐 Profile Links:

Experience:

He has been serving as a lecturer at the Institute of Management Sciences in Peshawar, Pakistan, since November 2015. In this role, he teaches both graduate and undergraduate students and leads IM DigiSol, the institute’s in-house software house. Additionally, he holds the position of Web & Database Administrator (BPS-17) at the Directorate of Information Technology, Government of KP, where he spearheads the computerization efforts of the Special Branch Police Department and Counter Terrorism Department. Prior to this, he worked as an I.T/ERP Trainer at Rehman Medical Institute & Hospital in Peshawar, Pakistan, from 2012. He also served as an international consultant for curriculum and academic development at the School of ICT, NIMA Kabul, Afghanistan, from 2009 to 2011, as part of a World Bank-funded project implemented through Maxwell Stamp PLC, London. In this capacity, he provided teaching support to undergraduate students.

Publications:

Comparing oversampling techniques to handle the class imbalance problem: A customer churn prediction case study Cited By : 294, Published By : 2016
Customer churn prediction in the telecommunication sector using a rough set approach Cited By : 258, Published By : 2017
Customer churn prediction in telecommunication industry using data certainty Cited By : 232, Published By : 2018
Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods Cited By : 88, Published By : 2019
Churn prediction in telecommunication industry using rough set approach Cited By : 51, Published By : 2015
Customer churn prediction in telecommunication industry: with and without counter-example Cited By : 40, Published By : 2014
Just-in-time customer churn prediction in the telecommunication sector Cited By : 39, Published By : 2020
Just-in-time customer churn prediction: With and without data transformation Cited By : 30, Published By : 2018
A comparison of two oversampling techniques (smote vs mtdf) for handling class imbalance problem: A case study of customer churn prediction Cited By : 29, Published By : 2015
Compromised user credentials detection in a digital enterprise using behavioral analytics Cited By : 27, Published By : 2019