Datasphere

Fellowship Program

Fellow

Lukman Enegi Ismaila

Adopting a multistakeholder approach ensures sustainable and implementable policies around data access and usage. The Datasphere promotes a collaborative effort among stakeholders ensuring effective data governance.

Adopting a multistakeholder approach ensures sustainable and implementable policies around data access and usage. The Datasphere promotes a collaborative effort among stakeholders ensuring effective data governance.

Lukman Ismaila is a doctoral researcher in deep learning applications for medical imaging with a speciality in “neurosurgical planning for brain tumor removal” at LARIS Laboratory, University of Angers, France.

He has accumulated years of professional experience as a software developer using web and mobile technologies to drive innovative company and research products. He also has more than 3 years of university lecturing experience where he supports students towards their academic success by demystifying complex theoretical concepts in computer science. Currently, he volunteers as Lead Machine Learning Engineer and Project Manager at Omdena, where he enables direct impact by contributing to solutions to address pressing problems in society through his several project engagements.

Lukman collaborates excellently with multidisciplinary teams in a wide range of domains. He is a self motivated problem solver and continues to demonstrate his passion to undertake challenging problems in machine learning algorithms, medical image processing, graph representation learning, image reconstruction, reinforcement learning, predictive modeling, and scalable algorithms.

Lukman firmly believes that data policies are essential for enabling ordinary people to benefit from the outcomes of the unbounded potential offered, and Datasphere is making an uncommon effort to support this discussion.

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Lukman Enegi Ismaila

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