Gregory Ganger
Office
2208 Mehrabian Collaborative Innovation Center
ganger@ece.cmu.edu
Phone
(412) 268-1297
Department
CIT - Electrical and Computer Engineering
Computer Science Department: Affiliated
Administrative Support
Research Areas
Research Interests
Data-Intensive and Cloud Computing
Distributed Systems
Advisees
CSD Courses Taught
15746 - Fall, 2025
Research Statement
I have broad research interests in computer systems, including cloud computing, storage/file systems, operating systems and distributed systems. I am involved in several ongoing projects in such areas as systems for large-scale ML, cloud/cluster resource scheduling, and exploitation of new storage/NVM technologies.
Big-learning systems for Big Data
Modern data analytics often relies on statistical machine learning (ML) to parameterize models that fit observation data, for use in making predictions, correlating causes with effects, etc. Growth in data and desired model precision dictate parallel execution of ML algorithms on clusters, with the corresponding work distribution, synchronization, and data consistency challenges. The big-learning group is exploring powerful new approaches for efficient, scalable, and robust big-learning on Big Data.
Cloud Computing
We are exploring software systems challenges in efficiently supporting and exploiting cloud computing, such as resource allocation/scheduling and exploiting elasticity for stateful services (e.g., storage) and long-running computations (e.g., large-scale ML).
Parallel Data Lab (PDL)
As a faculty member of the Parallel Data Lab, I lead and collaborate on a number of storage-related projects in areas such as storage system architecture, file systems, and Big Data systems. For example, in addition to the activities discussed above, we are exploring how system software should change to accommodate new storage technologies like non-volatile RAM (e.g., PCM) and best exploit Flash.