David Burth Kurka
I am a Postdoctoral research assistant, currently working on Machine Learning for Communications. Previously, I received a PhD degree from Imperial College London (Intelligent Systems and Networks group), and Eng and MsC degrees from University of Campinas - Brazil.
My current research focus is towards developing machine learning solutions to wireless communication problems. Before that, I investigated different machine learning and artificial intelligence related topics, such as socially inspired computing and multi-agent Systems (PhD), the use of social information for predicting behaviour in social networks and complex systems (master's).
My research interests include Machine Learning, Wireless Communications, Information Theory, Socially Inspired Computing, Multi-Agent Systems, Collective Intelligence, Social Network Analysis and Complex Systems.
You can follow my publications and citations on my Google Scholar page.
Publications
Journals
→ D. Burth Kurka, and D. Gunduz, DeepJSCC-f: Deep Joint Source-Channel Coding of Images with Feedback‌, IEEE Journal on Selected Areas in Information Theory (JSAIT), to appear.
→ E. Bourtsoulatze, D. Burth Kurka, and D. Gunduz, Deep Joint Source-Channel Coding for Wireless Image Transmission, IEEE Transactions on Cognitive Communications and Networking (TCCN), vol. 5, no. 3, pp. 567 - 579, Sep. 2019.
→ D. Burth Kurka, J. V. Pitt, J. Ober, Knowledge Management for Self-Organised Resource Allocation, ACM Transactions on Autonomous and Adaptive Systems (TAAS), vol 14, no. 1, July 2019.
→ D. Burth Kurka, A. Godoy, and F. J. Von Zuben, Online Social Network Analysis: A Survey of Research Applications in Computer Science, 2016.
Conferences
→ D. Burth Kurka, D. Gunduz, Deep Joint Source-Channel Coding of Images with Feedback, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.
→ D. Burth Kurka, D. Gunduz, Joint Source-Channel Coding of Images with (not very) Deep Learning, in 2020 International Zurich Seminar on Information and Communication (IZS 2020), Zurich, Switzerland, Feb. 2020.
→ D. Burth Kurka, D. Gunduz, Successive Refinement of Images with Deep Joint Source-Channel Coding, in IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Cannes, France, Jul. 2019.
→ E. Bourtsoulatze, D. Burth Kurka, D. Gunduz, Deep Joint Source-Channel Coding for Wireless Image Transmission, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, 2019.
→ D. Burth Kurka, J. V. Pitt, P. R. Lewis, A. Patelli, and A. Ekárt, Disobedience as a Mechanism of Change, in 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), Trento, Italy, pp. 1-10, Sep 2018.
→ D. Burth Kurka and J. V. Pitt, The Principled Violation of Policy: Norm Flexibilization in Open Self-Organising Systems, in 2nd eCAS Workshop on Engineering Collective Adaptive Systems, Tucson, Arizona, USA, Sep 2017.
→ D. Burth Kurka and J. V. Pitt, Smart-CPR: Self-Organisation and Self-Governance in the Sharing Economy, in Fifth International Workshop on Self-Adaptive and Self-Organising Socio-Technical Systems (SASO^ST), Tucson, Arizona, USA, Sep 2017.
→ D. Burth Kurka, A. Godoy, and F. J. Von Zuben, Using Retweet Information As a Feature to Classify Messages Contents, in Proceedings of the 26th International Conference on World Wide Web Companion (WWW17), Republic and Canton of Geneva, Switzerland, pp. 1485–1491, Apr 2017.
→ D. Burth Kurka and J. V. Pitt, Distributed Distributive Justice, in 2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), pp. 80–89, Sep 2016.
→ D. Burth Kurka and J. V. Pitt, Voices of Justice: Finding Consensus in the Multitude of Claims, , in 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W), pp. 174–179, Sep 2016.
→ D. Burth Kurka, A. Godoy, and F. J. V. Zuben, Birds of a Feather Tweet Together: Computational Techniques to Understand User Communities in Social Networks, in6th Workshop on Making Sense of Microposts (#Microposts2016), pp. 21–27, Apr 2016.
