Who We Are

UNU research experts and personnel

UNU Headquarters Japan
Showing 401-410 of 741 results

Staff Administrative Assistant

Ajsela Masovic

Ajsela Masovic is an Administrative Assistant at UNU-CRIS

Expert Professorial Fellow

Nanditha Mathew

Nanditha Mathew is a Professorial Fellow at UNU-CRIS

Expert Affiliated Researcher

Dr. Nanditha Mathew

Nanditha is a professorial fellow at UNU-CRIS and an affiliated researcher at UNU-MERIT.

Expert Manager, Geospatial, Climate and Infrastructure Analytics Program

Dr. Mir Matin

Dr. Mir Matin is the Manager of the Geospatial, Climate and Infrastructure Analytics Programme at UNU-INWEH, leading a team of scientists and academics using geospatial analysis, climate modeling, and advanced analytics to support evidence-based decision-making.  

Staff Assistant to the Senior Vice-Rector

Namiko Matsuo

Namiko Matsuo is the UNU Assistant to the Senior Vice-Rector.

Expert Research Fellow

Frank Mattheis

Frank Mattheis is a Research Fellow at UNU-CRIS since August 2021.

Expert Student Assistant

Nandita Matthews

Nandita Matthews

Expert International Affairs and Policy Associate

Tariro Mbiba

Tariro is a dedicated International Affairs and Policy Associate specialising in environmental law, justice, and the interconnected sustainable development challenges within water, environment, and health. With a strong background in policymaking and governance, she brings extensive experience from her roles with the United Nations Environment Programme (UNEP) and UNU-INWEH.

Advisory Board Member UNU-IAS Board Member; Professor and Director General at the Ecological Monitoring Centre (CSE)

Prof. Cheikh Mbow

Cheikh Mbow is a Professor and Director General at the Ecological Monitoring Centre (Centre de Suivi Ecologique (CSE)) in Senegal, and Adjunct Professor at Michigan State University (MSU). 

Expert Research Fellow, Artificial Intelligence and Applied Statistics

Dr. Rendani Mbuvha

Dr. Rendani Mbuvha is an actuary and machine learning expert, specializing in the application of machine learning to improve our understanding of climate-related risks.