<span>Dr. Chrispine Nyamweya</span>
Scientist

Dr. Chrispine Nyamweya

Assistant Director, Limnology / Chief Scientist

Kenya Marine and Fisheries Research Institute
 
Senior Research Scientist
KMFRI Kisumu
 
Freshwater Systems Research / Limnology
Ecological Modeling • Fisheries Science • Data Science • AI for Ecosystems
 

Email: sanychris@yahoo.com Email: cnyamweya@kmfri.go.ke 

 
Location
KMFRI Kisumu
Department
Freshwater Systems Research / Limnology
Specialization
Ecological Modeling • Fisheries Acoustics • Fish Stock Assessment
Professional Focus
Ecosystem Modeling • Big Data • Machine Learning • AI • Citizen Science
Research Focus: Ecological modeling, fisheries science, ecosystem functioning, simulation models, big data analytics, and AI-driven decision support for aquatic ecosystem management.
 

Dr. Chrispine Nyamweya is an experienced ecologist with a strong track record in ecological modeling, fisheries science, data science, and smart technologies. He serves as a Senior Research Scientist and Assistant Director at the Kenya Marine and Fisheries Research Institute (KMFRI), where he has built a 13-year research career focused on understanding and managing aquatic ecosystems.

He specializes in simulation modeling of ecosystem functioning. He earned his Doctorate Degree in Ecological Modeling from the University of Iceland in 2017, where he developed two major models: ROMS for Lake Victoria circulation patterns and Atlantis, the first end-to-end ecosystem model for Lake Victoria, used to evaluate ecological and socio-economic fishing strategies.

Chrispine is highly engaged in data-driven ecosystem science, leveraging big data, machine learning, artificial intelligence, and statistical programming (R, Python, MySQL) to support evidence-based decision-making in fisheries and aquatic resource management.

 
Research Interests
Ecosystem Functioning Ecological Modeling Fisheries Science Big Data Machine Learning Artificial Intelligence Fish Stock Dynamics Smart Aquatic Systems
 
Key Activities
  • Development of ecological simulation models (ROMS, Atlantis)
  • Fish stock assessment and fisheries modeling
  • Ecosystem functioning analysis of Lake Victoria and other systems
  • Big data analytics for aquatic ecosystems
  • Machine learning and AI applications in fisheries science
  • Citizen science and collaborative research networks
  • Development of web-based ecological databases (kenyasdata.com)
  • Supervision of research and international collaborations
 
Qualifications
  • PhD in Ecological Modeling – University of Iceland (2017)
  • International Diplomas in Marine & Inland Waters Monitoring and Assessment
  • Fisheries Acoustics Certification
  • FishBase and Taxonomy Training
  • Research Project Design Certification
  • Strong proficiency in R, Python, and MySQL
 
Selected Publications
Nyamweya et al. (2022) Spatiotemporal variation in fishing patterns and fishing pressure in Lake Victoria
Aura et al. (2022) Citizen science and contamination monitoring in small water bodies
Atlantis ecosystem modeling applications in Lake Victoria fisheries management