Texas Tech University

Ashish Sedai, Ph.D.

WiSE Ph.D. Student at Renewable Energy

Email: ashish.sedai@ttu.edu

Linkedin Website

Ashish is a renewable energy enthusiast. He specializes in statistical analysis, machine learning, and deep learning techniques for forecasting wind speed and solar power generation. With a focus on solar, wind, micro-hydro, and green hydrogen technologies; he works in resource assessment, energy modeling, and data analysis domains within renewable energy.

Having gained practical industry experience as a data/machine learning student analyst at the Electric Power Research Institute (EPRI) and as a Mechanical Engineer Intern at the National Renewable Energy Laboratory (NREL), Ashish brings valuable expertise to the table. His passion for addressing the global energy crisis, combined with his mechanical engineering background, drives his commitment to the renewable energy industry.

Ashish believes in maintaining a healthy work-life balance and enjoys outdoor pursuits such as hiking and soccer. With a diverse skill set and a passion for making a positive impact, Ashish is poised to contribute significantly to the renewable energy sector.



  • 2024 (Expected): Doctor of Philosophy - PhD, Wind Science & Engineering, Texas Tech University, Lubbock, TX
  • 2023: Graduate Certificate in Renewable Energy, Texas Tech University, Lubbock, TX
  • 2020: Bachelor of Engineering in Mechanical Engineering, Punjab, India
  • 2015: High School Diploma, Liverpool International College, Kathmandu, Nepal


Professional Experience

  • Graduate-II Mechanical Engineer at National Renewable Energy Laboratory (NREL), Denver, CO.
  • Machine Learning Analyst at Electric Power Research Institute (EPRI), Palo Alto, CA.
  • Research Assistant at Texas Tech University Lubbock, TX.
  • Instructor at Madan Bhandari Memorial Engineering College, Pokhara University, Nepal
  • Research Assistant Intern at Kathmandu University,Turbine Testing Lab, Kathmandu Nepal
  • Research Intern at Vortex Energy Solution Pvt. Ltd, Bhaktapur, Nepal

Awards and Honors

  • Graduate Research Assistantship Award from National Wind Institute($24,000 per year)
  • Repowering Schools & NREL: Wind Energy Seed Funding($6,000)
  • Repowering Schools: Travel Fund ($1000)
  • Best Poster Award in DOE's Hydropower Collegiate Competition.
  • Clean Energy Editor's Choice Award for the Paper “Wind Energy as Source of Green Hydrogen Production in the USA”:($1,000)

Research Articles

Google Scholar Link

  • Sedai, A., Gautam, S., Dhakal, R., Thapa, BS., Pol, S., Moussa, H., Wind Energy as a source of green hydrogen production in the United States. Clean energy, Oxford Academic.
  • Sedai, A.; Dhakal, R.; Gautam, S.; Dhamala, A.; Bilbao, A.; Wang, Q.; Wigington, A.; Pol, S. Performance Analysis of Statistical, Machine Learning and Deep Learning Models in Long-Term Forecasting of Solar Power Production. Forecasting 2023, 5, 256-284. https://doi.org/10.3390/forecast5010014
  • Sedai, A., Singh, G., Dhakal, R., Khatiwada, A., Khanal, K., Kumal, B., & Mishra, A. K. (2021, November) Technical and economic feasibility of a fully solar-powered Airport in Nepal. In 2021 IEEE International Conference on Intelligent Systems, Smart and Green Technologies (ICISSGT) (pp. 122-127). IEEE.
  • Dhakal, R., Sedai, A., Paneru, S., Yosofvand, M., & Moussa, H. (2021). Towards a Net Zero Building Using Photovoltaic Panels: A Case Study in an Educational Building. International Journal of Renewable Energy Research (IJRER), 11(2), 879889.
  • Sedai, A., Thapa, BS., Thapa, B., Kapali, A., Quain, Z., Guo, Z., Application of reverse engineering method to model eroded Francis's runner. Journal of Physics: Conference Series (CRHT), 2020
  • Sedai, A., Singh, G., Dhakal, R., Kumal, B., Ghimire, N., and Yadav, B., Technical and Economic Analysis of Site Implementations of Gravitational Water Vortex Power Plant, 2021 IEEE International Conference on Intelligent Systems, Smart and Green Technologies (ICISSGT), 2021, pp. 128-133.
  • Sedai, A., Yadav, B., Khatiwada, A., kumal, B., Dhakal, R., Performance analysis of gravitational water vortex power plant. CRHT-X conference Kathmandu University.
  • Dhakal, R., Sedai, A., Moussa, H., Pol, S., A Novel Hybrid Method for Short-Term Wind Speed Prediction Based on Wind Probability Distribution Function and Machine Learning Models, Applied Sciences, MDPI.
  • Dhakal, R., Sedai, A., Prasai, S., Pol, S., Moussa, H., Deep Learning Model with Probability Density Function and Feature Engineering for Short Term Wind Speed Prediction. (Presenting at IEEE conference Oct 2022, Utah)

Renewable Energy