Naresh Neupane, PhD
Researcher • Data Scientist
I'm Naresh Neupane, a Research Professor at Georgetown University with a strong passion for data-driven discovery. I earned my Ph.D. in Atmospheric Dynamics from the University of Texas at Austin in 2015, where I applied advanced mathematical, statistical, and physical frameworks to explore complex atmospheric systems.
Since joining Georgetown in the fall of 2015, I have led and collaborated on a wide range of federally funded research projects as Principal Investigator (PI) and co-PI, including grants from the NSF and USGS. My research bridges statistical modeling, big data analytics, and artificial intelligence to address pressing environmental and ecological questions.
I work closely with collaborators across disciplines - statistics, mathematics, computer science, ecology, and economics to develop solutions to complex scientific challenges. A key focus of my current work is understanding how global warming is reshaping biodiversity patterns and ecosystem dynamics under various greenhouse gas emission scenarios. I am also exploring how climate change influences the evolution of financial markets and risk forecasting.
My recent projects center around computer vision and neural networks. In one, I developed a deep learning model that uses object detection algorithms to identify butterfly species and evaluate their health and developmental stages with high accuracy.
Outside of research, I enjoy spending time with my wife and son, and I've recently discovered a love for writing. For the past three years, I've been working on a science fiction novel that weaves scientific insight into imaginative storytelling, set to be published soon.
My research spans atmospheric modeling, biodiversity conservation, machine learning applications in ecology, and climate-driven economic forecasting. I am particularly interested in understanding how global warming reshapes earth systems, species distributions, and financial markets under various greenhouse gas emission scenarios. By combining large-scale climate models with ecological and economic data, I develop tools and frameworks for near- and long-term forecasting using advanced statistical and AI techniques.
Key Areas of Focus:
- Atmospheric Modeling: Investigating the impact of global warming on atmospheric circulation patterns, monsoon dynamics, and earth systems using climate model projections across emission scenarios.
- Biodiversity & Eco-Forecasting: Modeling current and future distributions of butterfly and bird populations, predicting vegetation greenness and peak green-up, and building short - to long-term forecasts.
- AI for Conservation Science: Leveraging machine learning and computer vision, especially YOLO-based object detection, to automate species identification, monitor insect health, and support biodiversity assessments.
- Climate and Financial Systems: Developing integrated models that couple economic forecasts with climate projections to assess how global finance, GDP, wage rates, and markets evolve in a warming world.
Ries Lab of Butterfly Informatics
Georgetown University, Washington, DC
Washington, DC 20057, USA
Key Collaborators Across U.S. Institutions
- • University of Florida
- • University of North Carolina
- • U.S. Geological Survey (USGS)
- • Michigan State University
- • University of California
- • University of Connecticut