I obtained my Ph.D. degree from the University of Toronto under the supervision of Professor Ashish Khisti. In my thesis, I investigated fundamental limits and applications of streaming codes. Traditionally, information theory and coding theory handle the transmission of a single, usually large, message that needs to be transmitted from sender to receiver. Streaming codes, on the other hand, consider a setting of a sequence of messages, which are decoded with a limited latency, usually focused on packet-erasure channel models. They can be seen as a particularly interesting type of convolutional codes.

I am generally interested in information theory, multi-user communications and channel coding theory. Recently, I have taken interest in Machine Learning, and in particular Reinforcement Learning, as its strong theoretical foundation in Markov Decision Processes, and its connection to how humans learn, is captivating.

I really enjoy teaching and mentoring students and I believe scientific development would greatly benefit from a clearer and more accessible communication of knowledge.

Research Interests

• Information Theory
• Multi-user Communications
• Streaming Codes
• Machine Learning applied to Communications

Selected Publications and Preprints

For a complete list, please check my publications page or my Google Scholar profile.

• Deep Reinforcement Learning for Latency-Sensitive Communication With Adaptive Redundant Retransmissions
  Gustavo Kasper Facenda, Ashish Khisti, Wai-Tian Tan and John Apostolopoulos
  IEEE Transactions on Communications, 2023. See on IEEExplore.

• Adaptive Relaying for Streaming Erasure Codes in a Three Node Relay Network
  Gustavo Kasper Facenda, Nikhil Krishnan, Elad Domanovitz, Ashish Khisti, Wai-Tian Tan and John Apostolopoulos
  IEEE Transactions on Information Theory, 2023. See on IEEExplore.

• Streaming Erasure Codes over Multi-Access Relayed Networks
  Gustavo Kasper Facenda, Elad Domanovitz, Ashish Khisti, Wai-Tian Tan and John Apostolopoulos
  IEEE Transactions on Information Theory, 2022. See on IEEExplore.
  

• Efficient Scheduling for the Massive Random Access Gaussian Channel
  Gustavo Kasper Facenda and Danilo Silva
  IEEE Transactions on Wireless Communications, 2020. See on IEEExplore