People

REACH-ENDS Staff Profile

Our company is composed of senior staff with international work and research experience.

Bedassa R. Cheneka (PhD)

Bedassa is a senior meteorologist by profession and specialized in wind energy resources and climate change. Bedassa has worked and research experience in industry and higher education both at national and international level. Currently, he is a postdoctoral senior researcher at University of Antwerpen, Belgium working on modeling and building a global microclimate database, and also a part-timer guest researcher at Utrecht University, The Netherlands.

Bedassa has a solid strong technical experience in modeling, programming and applied research in the areas of weather and climate, agro-meteorology and wind energy resources. Some of the pioneer area of experience are:

Weather and climate model (mainly WRF) configuration, set-up and simulation.
Develop agrometeorology advisory to mitigate climate risk
Analysis and modeling of renewable energy resource visibility

Moreover, Bedassa is an expert in data analysis and model verification tools using the popular programming languages: Python, Matlab and R. He has used these programming languages to analyze weather and climate model output, and quantity climate change impact on wind energy resources.

Last but not least, Bedassa has used the state of art machine learning to model and forecast climate variables and is familiar with the emerging machine learning techniques and algorithm of multi layer perceptron, convolutional neural network and recurrent neural netwrork.

Sisay E. Debele (PhD)

Sisay Debele is an experienced Senior Mathematical Modeller with over a decade of expertise in hydrology, climate science, and environmental risk management. His work focuses on assessing and reducing risks from floods, droughts, and climate change. Using advanced hydrodynamic modeling, system dynamics, and data science, he helps organizations develop effective solutions for disaster risk reduction and sustainable water management.

Sisay has led and contributed to major international projects with organizations like the United Nations, the European Commission, and top research institutions. He specializes in using cutting-edge tools such as predictive modeling, machine learning, and GIS to analyze environmental challenges and improve climate adaptation strategies.

Currently, he works as a Senior Mathematical Modeller at the London School of Hygiene & Tropical Medicine (LSHTM), where he develops models to study how climate change affects public health and natural water systems. He also has extensive experience in teaching, mentoring, and designing professional training programs on climate science, data analysis, and nature-based solutions for managing environmental risks.

Amina Aliyi

Amina is a versatile web developer with expertise in React, JavaScript, and WordPress, creating modern, high-performance websites and applications. With a strong foundation in frontend development, backend, SEO, and digital marketing, she builds websites that are not only visually stunning but also optimized for search engines and user engagement.

Proficient in Next.js, TypeScript, Tailwind CSS, and API development, Amina ensures scalable and efficient solutions. Additionally, she specializes in WordPress customization, on-page SEO, and digital marketing strategies to drive traffic and conversions.

With a passion for technology and results-driven solutions, Amina is committed to helping businesses establish a strong online presence.

Expertise

🔹 Climate, Hydrological & Hydraulic Modeling – Expertise in flood/drought risk analysis and forecasting
🔹 Remote Sensing & GIS – Earth observation for climate and disaster risk assessment
🔹 Statistical & Machine Learning Modeling – Copula models, Bayesian networks, Monte Carlo simulations
🔹 System Dynamics & Agent-Based Modeling – Proficient in STELLA Architect, AnyLogic
🔹 Nature-Based Solutions (NbS) – Designing sustainable flood & drought risk mitigation strategies
🔹 Data Science & Visualization – Advanced techniques for climate analytics and decision-making
🔹 AI for Climate Adaptation – Machine learning-based hydrological forecasting
🔹 Systematic Literature Review (SLR) – Skilled in evidence synthesis for hydrology and climate research

Sample Works

🔹 Elbe River Flood Modeling – Coupled global and regional climate models with HEC-HMS and HEC-RAS to simulate flood risk and assess floodplain management strategies.
🔹 Seasonal Flood Peak Dependence Analysis – Applied copula-based models to enhance flood quantile estimation and infrastructure design.
🔹 Non-Stationary Flood Frequency Analysis – Used MLE, WLS/TS, and GAMLSS methods to improve flood risk assessment under climate change.
🔹 AI for Climate & Hydrology – Developed AI-driven flood prediction models integrating deep learning, Bayesian Networks, and remote sensing data.
🔹 Spercheios River Basin, Greece (OPERANDUM EU Project) – Used Sentinel-1 & 2 imagery for flood monitoring and NbS evaluation in flood and drought mitigation.
🔹 Machine Learning-Based SLR Frameworks – Developed automated frameworks to extract and synthesize scientific knowledge.
🔹 Nature-Based Solutions (NbS) Research – Reviewed 547+ NbS case studies, co-developed the NbS Catalogue in the GeoIKP web platform.

Trainings & Capacity Building

🔹 Data Science & Visualization for Public Health & Policy – LSHTM, UK
🔹 Advanced Statistical Methods for Climate & Hydrology – IGF PAN, Poland
🔹 Machine Learning for Environmental Science – University of Surrey, UK
🔹 Water Resources Management & Hydraulic Modeling – University of Surrey, UK
🔹 Climate Change & Planetary Health Methods – LSHTM, UK
🔹 Systems Thinking & System Dynamics Modeling – LSHTM, UK
🔹 Agent-Based Modeling for Environmental & Public Health Systems – LSHTM, UK
🔹 Hydrodynamic Flood Modeling with HEC-RAS – University of Surrey, UK
🔹 Remote Sensing & GIS for Climate Adaptation – University of Surrey, UK
🔹 Climate Risk & Multi-Hazard Assessment for Policy Makers – UNESCO, Paris