Dr. Monica Borunda | Forecast of Electric Energy Demand | Best Researcher Award

Professor at CENIDET, Mexico

Mónica Borunda Pacheco is a distinguished researcher and academic in the fields of renewable energy, artificial intelligence applications in energy management, and high-energy physics. With a career that spans over two decades, she has made significant contributions to both theoretical and applied research domains. Transitioning seamlessly from string theory and cosmology to innovative renewable energy technologies, her professional journey reflects a unique blend of deep theoretical insight and practical technological advancement. As a passionate educator and project leader, she continuously pushes the boundaries of interdisciplinary research, fostering advancements that address pressing global challenges.

Profile

Orcid

Education

Mónica’s educational background is exemplary, beginning with a Bachelor of Science in Physics from the National Autonomous University of Mexico (UNAM), where she earned the prestigious “Gabino Barreda” medal for academic excellence. She pursued a Diploma in High Energy Physics at the Abdus Salam International Center for Theoretical Physics (ICTP) in Italy, followed by advanced studies in Physics and Mathematics at the University of California, Davis, and Cornell University. She completed her Ph.D. in High Energy Physics at the International School for Advanced Studies (SISSA) in Trieste, Italy, where her research centered on time-dependent backgrounds in String Theory. Further enhancing her expertise, she specialized in Photovoltaic Power Generation through a program by the Japan International Cooperation Agency (JICA).

Experience

Throughout her extensive career, Mónica has held research and academic positions at prominent institutions worldwide. She contributed to theoretical physics research at the University of Neuchâtel, ICTP, and Universidad de Granada, focusing on gravity, cosmology, and thermodynamics. Later, she transitioned to applied energy research at institutions like the National Institute of Electricity and Clean Energy (INEEL) and Monash University, concentrating on renewable energy projects involving solar and wind technologies. Her professional endeavors also include project management roles in international energy firms in Qatar and Spain, where she led projects on solar thermal energy and photovoltaic system optimization. Simultaneously, she has been active in teaching advanced courses in physics, renewable energy, and artificial intelligence at UNAM and other educational institutions.

Research Interest

Mónica’s research interests are notably interdisciplinary, encompassing renewable energy, artificial intelligence, and energy management. She focuses on the application of machine learning techniques to optimize energy generation and forecasting in solar and wind systems. Her work seeks to enhance the efficiency, reliability, and integration of renewable energy into existing power grids. She is particularly interested in modeling and simulating energy systems to predict performance and identify optimization strategies using advanced computational tools. Her previous background in theoretical physics continues to inform her rigorous methodological approach, ensuring robustness in her applied research.

Award

Mónica’s outstanding contributions have been recognized through numerous prestigious awards and fellowships. She was honored with the Australian-APEC Women in Research Fellowship in 2017 and received the Japanese Government Fellowship in 2015. Her research excellence has also been acknowledged through grants such as the Torres Quevedo Grant and the Juan de la Cierva Fellowship from the Spanish Ministry of Science and Innovation. Earlier in her career, she secured fellowships from organizations such as the Swiss National Science Foundation, SISSA, and ICTP. Her academic excellence during her undergraduate studies was crowned with the Gabino Barreda Medal.

Publication

Mónica Borunda Pacheco has published extensively, with her research articles widely cited by the scientific community. A few notable publications include:

• “An intelligent method for day-ahead regional load demand forecasting via Machine-Learning analysis of energy consumption patterns across daily, weekly and annual scales,” Applied Sciences, 2025, cited for its innovative approach to energy forecasting.

• “Experimental study on biodiesel production in a continuous tubular reactor with a static mixer,” Processes, 2024, contributing significantly to renewable fuels research.

• “ANFIS-PSO based optimization for THD reduction in cascaded multilevel inverter UPS systems,” Electronics, 2024, known for its impact on power electronics systems.

• “Intelligent control of an experimental small-scale wind turbine,” Energies, 2024, advancing smart renewable energy technologies.

• “Spatial intelligent estimation of energy consumption,” Advances in Computational Intelligence, Springer, 2024, providing new insights into energy consumption analytics.

• “Enhancing long-term wind power forecasting by using an intelligent statistical treatment for wind resource data,” Energies, 2023, improving predictive models in renewable energy.

• “Load demand forecasting using a long-short term memory neural network,” Advances in Computational Intelligence, Springer, 2023, reflecting her expertise in AI-based energy management.

Conclusion

Mónica Borunda Pacheco’s career exemplifies a rare synthesis of deep theoretical knowledge and forward-looking applied research. Her pioneering work at the intersection of artificial intelligence and renewable energy continues to inspire new directions for sustainable development. Through her teaching, research, and leadership, she is not only advancing scientific understanding but also fostering the next generation of researchers and engineers dedicated to solving global energy challenges. Her work stands as a testament to the profound impact that interdisciplinary approaches can have in shaping a more sustainable future.