Victoria Granja is a Postdoctoral Associate at Rice University, specializing in Physics-Informed Neural Networks (PINNs) with applications in tribology and mechanical system optimization. She earned her Ph.D. in Mechanical Engineering from Rice in May 2024, where her research focused on leveraging machine learning to enhance the control and prediction of lubricated tribosystem performance through a synergistic combination of experiments and data-driven models. Originally from Ecuador, she completed her B.S. and M.S. in Mechanical Engineering at Escuela Politécnica Nacional, graduating with the highest honors. Her academic excellence earned her the prestigious Fulbright Fellowship, which supported her doctoral studies in the United States.

During her time at Rice, Victoria held multiple leadership roles, serving as Vice President of Student Advocacy for the Graduate Student Association, a representative of the Mechanical Engineering Association, and a board member of the Latin American Graduate Student Association. Her contributions to research and leadership have been recognized with numerous honors, including the Superior Engineering Student Award (2024), selection for the MIDAS Future Leaders Summit (2023), the Ken Kennedy Institute Graduate Fellowship (2022), the NSF Fellowship (2021) for her participation in the Mechanistic Machine Learning and Digital Twins Conference, and the AMPT Resiliency Award (2020).

Victoria combines expertise in mechanical design, experimental execution, and data-driven modeling to develop innovative solutions in tribology and system optimization. With a strong background in artificial intelligence and advanced engineering, she is committed to bridging the gap between fundamental research and real-world applications, leveraging data-driven approaches to solve complex engineering challenges. She believes that knowledge is most meaningful when applied for the greater good and strives to contribute to technological advancements that improve society and drive innovation for a more sustainable and efficient future.

Victoria is happy to connect on any topic