Javad Ghaderi

Leveraging tools from algorithms, optimization, and stochastic processes, his work is focused on the analysis and optimization of communication networks, data centers, and large-scale machine learning systems.

Of particular interest to Prof. Ghaderi are the resource optimization problems that arise in emerging large-scale networking, computing, and machine learning systems. With the ever-increasing demand for faster data communication and processing, efficient allocation of distributed network and compute resources is imperative to optimize performance and meet the growing demand for speed and efficiency in contemporary applications.

Prof. Ghaderi received his BSc from the University of Tehran, Iran, in 2006, his MSc from the University of Waterloo, Canada, in 2008, and his PhD from the University of Illinois at Urbana-Champaign (UIUC), in 2013, all in Electrical and Computer Engineering. He spent a one-year Simons Postdoctoral Fellowship at the University of Texas at Austin before joining Columbia in 2014. Prof. Ghaderi's research has received Best Paper awards from several major conferences, such as IEEE International Conference on Computer Communications (INFOCOM), IFIP International Symposium on Computer Performance, Modeling, Measurements and Evaluation (Performance), and ACM Conference on emerging Networking EXperiments and Technologies (CoNEXT). He is also a recipient of NSF CAREER Award and Best Student Paper Finalist award at the American Control Conference (ACC).

Research Areas

• Artificial Intelligence (AI) and Machine Learning (ML)
• Networked and Distributed Systems
• Wireless, Embedded & Sensor Systems
• Communications
• Networking
• Stochastic Processes
• Algorithms
• Optimization