| 2020 | ICASSP | On Distributed Stochastic Gradient Algorithms for Global Optimization. | Brian Swenson, Anirudh Sridhar, H. Vincent Poor |
| 2020 | MOBIHOC | Truthful mobile crowd sensing with interdependent valuations. | Meng Zhang, Brian Swenson, Jianwei Huang, H. Vincent Poor |
| 2019 | ACSSC | Smooth Fictitious Play in N 2 Potential Games. | Brian Swenson, H. Vincent Poor |
| 2018 | ACSSC | Best-Response Dynamics in Continuous Potential Games: Non-Convergence to Saddle Points. | Brian Swenson, Ryan W. Murray, Soummya Kar, H. Vincent Poor |
| 2016 | ACSSC | Computationally efficient learning in large-scale games: Sampled fictitious play revisited. | Brian Swenson, Soummya Kar, Joo Xavier |
| 2016 | IJCNN | On the design of phase locked loop oscillatory neural networks: Mitigation of transmission delay effects. | Rongye Shi, Thomas C. Jackson, Brian Swenson, Soummya Kar, Lawrence T. Pileggi |
| 2015 | ACSSC | On asynchronous implementations of fictitious play for distributed learning. | Brian Swenson, Soummya Kar, Joo Xavier |
| 2014 | ACSSC | Game-theoretic learning in a distributed-information setting: Distributed convergence to mean-centric equilibria. | Brian Swenson, Soummya Kar, Joo Xavier |
| 2014 | CISS | Strong convergence to mixed equilibria in fictitious play. | Brian Swenson, Soummya Kar, Joo Manuel Freitas Xavier |
| 2012 | ACSSC | Distributed learning in large-scale multi-agent games: A modified fictitious play approach. | Brian Swenson, Soummya Kar, Joo Manuel Freitas Xavier |