Project: Network Algorithms and Distributed Optimization

We design and analyze approximation algorithms for NP-hard network optimization problems. These algorithms demonstrate the power of randomness for overcoming provably difficult tasks. Our theoretical results are supported by simulations to showcase their practicality. Recently, we have been investigating the application of reinforcement learning techniques to network optimization problems that include local restrictions.

Publications (2019 – Present)

Please find publications from prior to 2019 here.

Refereed Journal Papers

  • Coming soon!

Refereed Conference Proceedings

Other Publications

  • Coming soon!


Invited Talks

  • Coming soon!

Conference Talks

Poster Presentations

  • Coming soon!

Other Presentations

  • Coming soon!


Current Team

Andréa W. Richa

PI / President’s Professor, Arizona State University[Website]

Jamison Weber

PhD Student, Arizona State University[Website]

Anya Chaturvedi

Factory Automation Engineer, Intel[Website]

Stefan Schmid

Professor, University of Vienna


Matthias Rost

Professor, TU Berlin | Software Engineer, Observe


Chandra Chekuri

Professor, University of Illinois at Urbana-Champaign


Dhanush Giriyan

Computer Science Undergraduate, Arizona State University

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Past Members and Collaborators

Mengxue Liu

PhD, Arizona State University 2018[LinkedIn]