Professor Olawale Awe
Olawale Awe is an Elected Member of the International Statistical Institute (ISI) and a Fellow of the African Scientific Institute, USA. He is the First LISA Fellow and presently the LISA 2020 Engagement Ambassador to Africa in the LISA 2020 Global Network of the University of Colorado, Boulder, USA. He was a visiting scholar at the Department of Statistics, Virginia Tech and BECCA Lab of the University of Pennsylvania, USA from September 2013-September 2014. He has over fifteen years’ experience as a Researcher, Lecturer, Senior Lecturer and Professor at various institutions in Nigeria and beyond. His research interests include Computational Statistics, Machine Learning, Time Series Econometrics, Statistics Education and Bayesian Methods.
As the President and CEO of ADA Global Concept, he has facilitated several capacity-building workshops and seminars. He has a strong passion for statistical capacity building of researchers in Africa and other developing countries. Awe holds a PhD in Statistics from the University of Ibadan, Nigeria and MBA from Obafemi Awolowo University, Ile-Ife, Nigeria as well as a Certificate in Interdisciplinary Statistics from LISA, Virginia Tech, USA. He is an Affiliate Member of the African Academy of Sciences (AAS) and an immediate past Council Member of the International Society for Business and Industrial Statistics (ISBIS) (2017-2021) as well as a country coordinator (Nigeria) of the International Statistical Literacy Program (ISLP) of the ISI.
Interests
Statistics
Data Science R
Python
Machine Learning
Student Development
Statistics Education
Profile
Prof. Olawale Awe is the President and Chief Executive Officer of Awesome Data Analytics Global Concept. He is the LISA 2020 Outreach and Engagement Ambassador to Africa in the USAID Sponsored Laboratory for Interdisciplinary Statistical Analysis (LISA) Program of the University of Colorado, Boulder, USA. He holds M.Sc., Ph.D. (Statistics) from the University of Ibadan and MBA (Finance) from the Obafemi Awolowo University, Ile-Ife, Nigeria where he lectured for almost a decade. He was a visiting scholar and statistical collaborator at the Department of Statistics, Virginia Tech, USA and Biostatistics Evaluation Collaboration Consulting and Analysis (BECCA) Lab of the University of Pennsylvania, from September 2013 to September 2014 and the Federal University of Bahia in Brazil (2020). He has presented scientific papers at several international conferences and served as a facilitator for various capacity-building workshops in Nigeria and beyond. He was a training consultant for the International Institute for Tropical Agriculture (IITA), Ibadan on their Data Management Course, which had participants from Congo, Senegal, Sierra Leone, Ivory Coast, Nigeria and Ghana. He is an International Research Fellow at the Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Brazil. He is a member of several professional organizations including Nigerian Statistical Association, International Biometric Society, Elected Member of International Statistical Institute (ISI), International Society for Bayesian Analysis, American Statistical Association, World Association of Young Scientists (WAYS), as well as a council member of the International Society for Business and Industrial Statistics (ISBIS) from 2017-2021. He is also a fellow of the African Scientific Institute (ASI), USA and a country coordinator (Nigeria) in the International Statistical Literacy Program (ISLP) of ISI, Netherlands. He was appointed as a Professor and PhD Advisor at Global Humanistic University, Curacao in June 2020. He created the first LISA 2020 Statistical Laboratory in Africa in October, 2014 (www.lisa2020.org). Professor Awe has great passion for research capacity strengthening of early career researchers and he believes in identifying the remote problems affecting the society through research and engaging policy makers to solve them. His research interests includes computational statistics, machine learning, econometric time series analysis with applications in medicine, climate and environment.
