Ali Ganji
About Ali Ganji
Ali Ganji is a Machine Learning Scientist III at Expedia Group with a background in industrial engineering and extensive experience in research and data science.
Title and Current Position
Ali Ganji holds the position of Machine Learning Scientist III at Expedia Group. Based in Seattle, Washington, United States, he has been with the company since 2022. In his role, he has led the development and deployment of a model to predict a different Customer Lifetime Value metric.
Previous Work Experience
Before joining Expedia Group, Ali Ganji worked at General Motors as a Researcher in the United States, from 2021 to 2022. He also served as an Applied Scientist Intern at Zillow in 2020, where he quantified the uncertainty of home valuation errors using machine learning. Additionally, he was a Data Scientist Intern at SAS in 2019, working on demand forecasting for hotels using machine learning models in Greater Minneapolis-St. Paul Area. His experience also includes roles at Arizona State University as a Research Assistant (2016-2021) and Teaching Assistant (2015-2016).
Educational Background
Ali Ganji completed his Doctor of Philosophy (Ph.D.) in Industrial Engineering from Arizona State University between 2015 and 2021. Prior to that, he earned a Master’s Degree in Industrial Engineering from Sharif University of Technology (2008-2011) and a Bachelor of Science (BSc) in Industrial Engineering from Azad University (IAU) (2004-2008).
Internships and Research Projects
During his internships, Ali Ganji developed a minimum viable product for predicting hotel bookings at SAS and quantified home valuation errors at Zillow Group. His research experience includes conducting projects funded by federal agencies such as the National Science Foundation, Department of Energy, and Department of Homeland Security. His work has been published in prestigious journals, including Transportation Research Part E and Journal of Disaster Risk Reduction.
Ph.D. Research and Application Areas
Ali Ganji's Ph.D. research at Arizona State University encompassed a wide range of applications including disaster preparedness and response, energy systems, and cyber-physical systems. His research contributed significantly to these fields, and his efforts were supported by funding from reputable federal agencies.