Lecturers and Speakers
Atinuke Adebanji is a statistician with requisite theoretical and analytical skills acquired over time as a career academician with research interests in Theoretical and Applied Statistics (with a bias for classification), and Statistics in Health. In the course of her career, she has carried out interdisciplinary collaborative research whiles teaching and supervising students at undergraduate and postgraduate levels within and outside Ghana. She currently heads the Department of Mathematics, KNUST, Ghana. Atinuke is a protagonist for females in STEM which has seen her playing a focal role in WiSTEMGh.
As Lead Data Scientist at R&D, Air Liquide (France), Dr. Habiboulaye Amadou-Boubacar manages Machine Learning and Health Care projects. He holds a PhD in Learning Algorithms and Data Mining from the University of Sciences & Technologies of Lille, (USTL, France). He has 10+ years of hands-on experience using Machine learning, Text Mining & Data Science to address various real-world challenges in the industry. Habiboulaye supervises research activities in strong collaboration with academics to explore the next frontiers of Machine Intelligence for industrial applications. He is also a Lecturer of applied Machine Learning at the University of Technology of Troyes (UTT, France), African Institute of Mathematical Sciences (AIMS, Cameroon), and Institute of Mathematics and Physical Sciences (IMSP, Benin).
Bubacarr Bah is a Senior Researcher, designated the German Research Chair of Mathematics with specialization in Data Science, at the African Institute for Mathematical Sciences (AIMS) South Africa and a Senior Lecturer (Asst. Professor) at the Division of Applied Mathematics, Department of Mathematical Sciences, Stellenbosch University. Prior to this he held a postdoc positions at EPFL, Switzerland, and then at UT Austin, USA. He also held a Graduate Assistant position at University of The Gambia (UTG) prior to his graduate studies. His PhD degree is in Applied and Computational Mathematics from the University of Edinburgh, UK, his MSc degree in Mathematical Modelling and Scientific Computing from the University of Oxford, UK, and his BSc degree (summa cum laude) in Mathematics and Physics from UTG. He underwent teacher training (has a Higher Teachers’ Certificate) at Gambia College and taught at secondary schools in The Gambia before his undergraduate studies at UTG.
Viani Djeundje Biatat
Viani is a Senior Research Fellow at the University of Edinburgh, and an Examiner at The Institute and Faculty of Actuaries in the United Kingdom. His current research interest lies in Statistical Modeling, Machine Learning & Data Analytics, with applications to Insurance, Credit Risk, Mortality & Demography. Viani holds a PhD in Statistics & Actuarial Mathematics from Heriot-Watt University. Prior to his current position, he held a post-doctoral position in Statistics at the University of Oxford, and thereafter, Viani spent a couple of years working in the financial industry on various projects related to the quantification and management of actuarial risks.
Olivier Menoukeu Pamen
Olivier Menoukeu Pamen is a Reader (Associate Professor) in Mathematics at the University of Liverpool and the German Research Chair in Mathematics and its Applications at the African Institute for Mathematical Sciences (AIMS) Ghana. Prior to this, he completed an MSc in Mathematics at the University of Yaound I and received a PhD in Financial Mathematics from the University of the Witwatersrand. He then joined the Centre of Mathematics for Applications in the University of Oslo as a Post-Doctorate research fellow. From there, he took up a permanent position in the Institute for Financial and Actuarial Mathematics at the University of Liverpool. His research interests lie in stochastic analysis and its applications. In the past years, he has focused on stochastic optimal control theory and their applications to finance and insurance, existence and uniqueness of strong solutions of stochastic differential equations (SDEs) via Malliavin calculus approach, and more recently, numerical approximation of SDEs.
Franck Kalala Mutombo
Prof. Dr. Franck Kalala Mutombo is the Academic Manager of AIMS-Senegal and a Professor in the Department of Mathematics and the Computer Science at the University of Lubumbashi, Democratic Republic of Congo. Franck is an AIMS South Africa Alumni (2007). He completed his honors degree in Mathematics at Lubumbashi University (UNILU), received his Master degree in Mathematics from the University of Paris-Sud XI, in France and completed his PhD in complexity science at the Department of Mathematics and Statistics from the University of Strathclyde, Glasgow, United Kingdom. Following this, Franck became a Post-Doctoral Research Fellow with a joint position between AIMS-South Africa and the University of Cape Town at the Center for Research in Computational and Applied Mechanics (CERECAM). Funded by Robert Bosch Stiftung (Germany), and in collaboration with Prof. Dr Antoine Tambue, he looked for “Efficient Numerical Methods for Multiphase Flow in Porous Media.” The overall project was to propose an alternative robust time step method to fully couple highly non-linear systems of partial differential equations modelling multiphase flow in serial and in the Parallel setting within deal. Additionally, he is interested in the field of complex networks or networks analytics and its applications. Networks analytics is important tools of data analytics data seeks trend and pattern in networks data. Franck contributed to the implementation of the sub-graph centrality and communicability algorithms in NetworkX.
Olaf Kouamo holds a PhD in Statistics and application obtained at Telecom ParisTech in 2010. As such, he has solid theoretical and practical knowledge in statistical modelling, the development and application of machine learning algorithms with a strong understanding of business issues. Today, Olaf is the Chief Data Scientist at a CAC40 company. As such, he is involved in many topics around Data Science, artificial intelligence and Big Data based on concrete cases and ground reality. He works mainly with Python, R and Spark. He also supports, acculturates all the directions of the company to the use of data to generate plus value and efficiency. Olaf is also involved in machine learning modules under python in universities and colleges in Paris (University of Dauphine, ENSIIE). Therefore, not only does he have the pedagogical skills necessary for good transmission of learning but also a good understanding of the business environment by his functions.
Naila Murray is a Senior Research Scientist and computer vision lead at NAVER LABS Europe. She graduated with a PhD in computer science from the Unversität Autònoma de Barcelona. Naila also holds a master’s degree in computer vision and artificial intelligence from the Unversität Autònoma de Barcelona, and a bachelor’s degree in electrical engineering, cum laude, from Princeton University. Her research includes fine-grained visual categorization.