Ekaba Bisong

Ekaba Bisong is a consultant with expertise in greenhouse gas accounting, applying data science, data engineering and machine learning to climate change challenges. He developed a land cover segmentation model using Landsat imagery to aid forestry emissions estimation for a Tier-3 inventory in Nigeria, and assessed the impact of circular economy principles on waste emissions.

His work covers national GHG inventories using modelling, estimation and accounting with GIS and remote sensing; machine learning models for emissions estimation; scenario analysis of emissions reduction strategies; agent-based modelling of environmental systems; and Monitoring, Reporting and Verification frameworks. He has worked on GHG estimation from land use and forestry at Adam Smith International, on the waste and circular economy analysis for Nigeria's NDC enhancement, and on the circular economy and natural capital agenda with the AfDB, RVO and GGKP.

He holds an MSc in Computer Science from Carleton University, Canada, with a focus on reinforcement learning, and a BSc in Computer Science from Babcock University, Nigeria. He is pursuing a PhD in Computer Science at the University of Victoria, Canada, and a BSc in Mathematics at Athabasca University, Canada.