Ali Ghodsi

Ali Ghodsi is an Adjunct Associate Professor in the Department of Computer Science at the University of California, Berkeley. His research interests include Database Management Systems (DBMS) and Operating Systems & Networking (OSNT). Ghodsi received his PhD in 2006 from KTH/Royal Institute of Technology in the area of Distributed Computing. His work spans distributed systems, cloud computing, big data computing, and networking. He holds an MBA in Logistics and Marketing from Mid-Sweden University and an MSc in Computer Engineering from the same institution. He is affiliated with the EECS department at UC Berkeley and teaches courses such as CS 294-194: Research to Startup.

Ali Ghodsi is a researcher at UC Berkeley with expertise in Big Data, Distributed Computing, Data Management, and Networking. His work focuses on developing scalable systems for data processing and storage, including Apache Spark, Spark SQL, and Delta Lake. Ghodsi has contributed to projects such as Mesos, Tachyon, and Lakehouse, which aim to improve resource sharing, data consistency, and performance in distributed environments. His research also explores information-centric networking, causal consistency, and the integration of machine learning with data systems. Ghodsi's publications highlight the challenges and innovations in building reliable, high-performance data platforms for modern computing.