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  <a href="/"><span>Gustavo Kasper Facenda</span>
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  <article class="markdown"><img src="Kasper.jpg" style="border-radius: 15%; float: left; padding-right: 15px" height="200" width="auto">
I am currently a researcher at Huawei Canada.
<p>I obtained my Ph.D. degree from the <a href="https://www.ece.utoronto.ca/" target="_blank">University of Toronto</a> under the supervision of Professor <a href="https://www.ece.utoronto.ca/people/khisti-a/" target="_blank">Ashish Khisti</a>. 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 <i>sequence</i> 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.</p>
<p>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.</p>
<p>I really enjoy teaching and mentoring students and I believe scientific development would greatly benefit from a clearer and more accessible communication of knowledge.</p>
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<!-- <p><blockquote class="book-hint info">
  I am currently interested in internships as a way to close the gap between my mostly theoretical communications background and real world applications and implementations. I am especially interested in companies that could benefit from streaming codes, such as companies that work with cloud computing, video conferencing or cloud gaming. You can find my CV <a href="/cv.pdf" target="_blank">here</a> (last updated: Oct/2022).
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<h1 id="research-interests">Research Interests</h1>
<ul>
    <li>Information Theory</li>
    <li>Multi-user Communications</li>
    <li>Streaming Codes</li>
    <li>Machine Learning applied to Communications</li>
</ul>
<h1 id="selected-publications-and-preprints">Selected Publications and Preprints</h1>
<p>For a complete list, please check my <a href="/papers/">publications</a> page or my <a href="https://scholar.google.com/citations?user=VNXac_8AAAAJ" target="_blank">Google Scholar</a> profile.</p>
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<li>
<p><strong>Deep Reinforcement Learning for Latency-Sensitive Communication With Adaptive Redundant Retransmissions</strong><br>
Gustavo Kasper Facenda, Ashish Khisti, Wai-Tian Tan and John Apostolopoulos<br>
IEEE Transactions on Communications, 2023. See on <a href="https://ieeexplore.ieee.org/abstract/document/10075625" target="_blank">IEEExplore</a>. </p>
</li>
<li>
<p><strong>Adaptive Relaying for Streaming Erasure Codes in a Three Node Relay Network</strong><br>
Gustavo Kasper Facenda, Nikhil Krishnan, Elad Domanovitz, Ashish Khisti, Wai-Tian Tan and John Apostolopoulos<br>
IEEE Transactions on Information Theory, 2023. See on <a href="https://ieeexplore.ieee.org/abstract/document/10064107" target="_blank">IEEExplore</a>. </p>
</li>
<li>
<p><strong>Streaming Erasure Codes over Multi-Access Relayed Networks</strong><br>
Gustavo Kasper Facenda, Elad Domanovitz, Ashish Khisti, Wai-Tian Tan and John Apostolopoulos<br>
IEEE Transactions on Information Theory, 2022. See on <a href="https://ieeexplore.ieee.org/abstract/document/9916294" target="_blank">IEEExplore</a>.<br></p>
</li>
<li>
<p><strong>Efficient Scheduling for the Massive Random Access Gaussian Channel</strong><br>
Gustavo Kasper Facenda and Danilo Silva<br>
IEEE Transactions on Wireless Communications, 2020. See on <a href="https://ieeexplore.ieee.org/abstract/document/9163281" target="_blank">IEEExplore</a></p>
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    <p>The Vector Scholarship in Artificial Intelligence supports the recruitment of top students to AI-related master’s programs in Ontario. Valued at $17,500 for one year of full-time study at an Ontario university, these merit-based entrance awards recognize exceptional candidates pursuing a master’s program recognized by the Vector Institute or who are following an individualized study path that is demonstrably AI-focused.</p>
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