Highlights:• Designed, developed, and implemented state-of-the-art production-level solar forecasting software in Python, utilizing terabytes of data. The software helps power system operators and solar plant owners to manage their operations. • Managing the solar forecasting software and its roadmap. • Leading a team of engineers. • Responding to high-profile and critical clients concerns. • Highly proactive and self-driven. • Managed and delivered various solar energy-related applications for client requests, including improving data quality, accuracy reports, rapid data visualization, and forecast post-processing. • Experienced with single and multidimensional temporal and spatial data, such as time-series sensor data, numerical weather predictions, and satellite imagery. • Proficient in data science, machine learning, statistics, Python, and R. • Created a process to efficiently track project’s timeline and deliverables. • Created documentation, user manuals, and training materials.

Skills:Problem solving, Analytical thinking, Product management, Team leading, Proactive, Self-driven, Forecasting, Predictive modeling, Python, R programming, Data science, Data visualization, Machine learning, 3D and spatial data, Satellite imagery, Solar energy, Solar forecasting, GIT, Technical writing

Honor:• Singapore International Graduate Award (SINGA) scholarship, National University of Singapore, 07/2016–07/2020. • High Honor Student, Isik University (2012) • Full scholarship, Isik University (2007)

Scientist 04/2021 - 12/2021
Singapore Institute of Manufacturing Technology, , Singapore
One of the main research collaborators in an industrial project on multi-site inventory positioning for manufacturing companies. Designed and developed an advanced artificial-intelligence-based material demand forecasting tool in R. The technology was successfully validated using the real data from a Singaporean enterprise on the industry of packaging printing. Contributed various project proposals.
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Team Lead, Applied Solar Data Scientist 12/2021 - current
Solar Energy Research Institute of Singapore (SERIS), , Singapore
Led the design, development, and implementation of cutting-edge solar forecasting software in Python, leveraging extensive data resources to support power system operators and solar plant owners. Managed software roadmap and a team of 2 engineers, addressing high-profile client concerns with proactive problem-solving. Delivered tailored solar energy applications, enhancing data quality, accuracy, and visualization. Proficient in temporal and spatial data analysis, data science, and machine learning.
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Scientist 08/2020 - 04/2021
National University of Singapore, , Singapore
Main research collaborators in the AI-based automated demand side management solution for optimal energy management of commercial and industrial scale systems project in collaboration with a startup. Designed, developed and implemented a solar forecasting tool in R programming language. Contributed development of electricity demand forecasting model. Supervised interns and engineers for scientific development and research.
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National University of Singapore 08/2016 - 07/2020
Singapore, Outside U.S./Canada, Singapore
Degree: Doctoral Degree
Major:Electrical and Computer Engineering
Contributed to various aspects of solar forecasting and solar resource assessment, including but not limited to deterministic and probabilistic forecasting, parametric and nonparametric modelling, machine-learning, ensemble forecasting, spatial data analysis, and quality control for solar data. Published multiple high-impact scientific papers in international peer-reviewed journals.

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