Environmental Economist & Co-Founder, Ecosonus
AI · Biodiversity · Nature Tech
I am an Environmental Economist and Co-Founder of Ecosonus, working at the intersection of biodiversity, artificial intelligence, data science, and environmental decision-making.
I bring extensive international experience from the United Nations, where I managed multi-million-dollar environmental and development portfolios, led complex international programmes, mobilized resources, and worked with governments, international organizations, and multidisciplinary teams across countries.
My background combines Environmental Economics, Data Science, Ecology, and Food Technology & Engineering. Today, I apply this interdisciplinary expertise to develop scalable solutions for biodiversity, climate resilience, sustainable food systems, and responsible AI.
Nature Tech for biodiversity monitoring and environmental intelligence
I co-founded Ecosonus, a nature-tech initiative developing AI-powered solutions for biodiversity monitoring and environmental decision-making.
Our work combines bioacoustics, remote sensing, geospatial modelling, artificial intelligence, and ecological data to generate actionable insights for conservation, ecosystem management, climate resilience, and nature-based tourism.
Lead the development of AI-powered Nature Tech solutions combining bioacoustics, remote sensing, geospatial modelling, and ecological data for biodiversity monitoring and environmental decision-making.
Lead Junior Fellows in responsible AI assessments for startups, covering AI governance, risk assessment, data practices, evaluation, monitoring, and implementation roadmaps.
Teach Ethics & Sustainable Development, integrating sustainability strategy, ESG, climate and nature-related risks, biodiversity, impact assessment, and responsible AI.
Led international environmental and development programmes, managed multi-million-dollar portfolios, mobilized resources, and worked across research, impact assessment, data-driven decision-making, and policy engagement.
Selected projects at the intersection of biodiversity, climate, artificial intelligence, geospatial analysis, and environmental decision-making.
This project links forest conservation with disaster risk reduction in Peru’s Yanachaga-Chemillén National Park and surrounding communities.
Using Google AlphaEarth and Sentinel satellite data, it identifies and monitors forest areas that help reduce landslide and flood risks and integrates ecosystem and risk information into decision-support tools.
Second Place, 2nd Copernicus Latin America Hackathon, European Union — 2025.
A multimodal AI application designed to support biodiversity conservation and nature-based tourism in remote, species-rich environments.
Predictive modelling of infectious disease outbreaks using SMA, ARMA, RNN, and LSTM models together with digital-stream data such as Google search trends.
Deep learning models outperformed traditional baselines in forecasting COVID-19 cases.
Analysis of the impact of COVID-19 on global primary education completion rates using Linear, Lasso, k-NN, and AdaBoost regression models.
UNESCO and World Bank data were used to estimate counterfactual 2020 outcomes without the pandemic.
Selected research spanning biodiversity, spatial econometrics, rural development, remote sensing, and international policy.
Structural Topic Modeling and NLP applied to more than 5,000 pages of UN biodiversity policy speeches, identifying thematic shifts and regional variation from 1994 to 2024.
Analysis of Alternative Development as a long-term strategy addressing illicit crop cultivation, drawing on evidence from international programmes and rural development interventions.
Spatial econometric modelling of opium poppy cultivation likelihood across Afghanistan, examining accessibility, population, climatic variables, and other potential drivers.
Examines how alternative development initiatives can reduce reliance on illicit crop cultivation through improved rural livelihoods, food security, market access, and training.
Evaluation of Landsat 8 imagery for identifying opium poppy crops in Afghanistan, including spatial resolution and crop-signature challenges.
Global analysis of Alternative Development initiatives, including coordination, data, project duration, funding, and long-term rural livelihood challenges.
Analysis of infrastructure, governance, food security, market access, environmental pressures, and livelihood vulnerability in Shan State.
Examination of the relationship between opium poppy cultivation, rural livelihoods, and sustainable development challenges in Afghanistan.
Survey-based analysis of livelihood conditions, infrastructure, health care, markets, and regional differences associated with opium cultivation.
Additional information on my professional experience, research, and current work.
For collaboration, research, consulting, partnership, or speaking enquiries, please get in touch.