Omid Isfahani Alamdari

My research activity is mainly oriented towards mobility data analytics, focusing on big data and data-intensive techniques to manage and process massive amounts of trajectory data. I developed specific memory-based trajectory data analysis techniques using Apache Spark to process data in a distributed manner with indexing techniques based on reduced representations of trajectories.

I am currently engaged in two ongoing research projects based mainly on the historical user data. The first focuses on sustainable mobility solutions, particularly in the areas of carpooling and electric vehicles, by analyzing individual mobility networks. The second project involves developing event prediction techniques that aim to provide explainable decisions by combining user history with real-time events.

Alongside my research and industry work, I’ve also taught computer science and data analytics courses, helping students connect theory with real-world applications. I’m excited about contributing to both academic and industrial projects and fostering student success through hands-on learning.