Principal Scientific Engineering Associate
CurrentLead architect of innovative computational frameworks that leverage cloud services for efficient processing and analysis of massive datasets. Engineered systems enabling unprecedented scale in renewable energy simulations, from utility-scale solar and wind to cutting-edge offshore wind technologies and green hydrogen Developed pioneering methodologies and software tools for:*Assessing renewable energy potential across diverse geographies*Optimizing transmission expansion using advanced algorithms*Analyzing sustainable fuel production pathways for aviation and other hard-to-decarbonize sectors Core technical expertise includes:* Developing large-scale power system simulation models using ReEDS, PLEXOS, and custom Python-based solutions* Architecting and implementing cloud-based data processing pipelines on AWS to handle terabytes of meteorological and geospatial data* Creating machine learning and AI models for renewable energy forecasting and resource assessment* Building high-resolution renewable energy potential and generation profile datasets* Designing and coding scalable data pipelines for energy sector analytics* Constructing techno-economic models for emerging clean energy technologies, including green hydrogen production and industrial decarbonization pathwaysTechnical advisor to senior officials in the White House, Prime Minister's Office of India, and major renewable energy developers like Equinor. Provide data-driven insights to investors on technological trends in the clean energy sector.Work has been covered in major media outlets including The New York Times, Washington Post, SF Chronicle, Economic Times (India), and NewsMax. Recipient of the Berkeley Lab Director's Award for Exceptional Scientific Achievement in Societal Impact. Committed to driving the global energy transition through innovative software solutions and data-intensive modeling techniques.
