- Elasticity for data stream processing applications.
- Modelling distributed system behaviours.
- Mono- and multi-objective optimisation problems.
- (Near) Real-time solutions for big data analytics.
- Machine Learning (ML) and Reinforcement Learning (RL).
- Cloud, Edge and Fog computing.
- Internet of Things (IoT) issues.
- Here you can find my research statement.
- 2019 - present: Postdoctoral Fellow in the Departament of Computer Science.
- Leader: Professor Eyal de Lara.
- Hosting team: Computer Systems and Networks Group in Department of Computer Science at the University of Toronto.
- Description: Distributed Stream Processing (DSP) applications are increasingly used in new pervasive services that process enormous amounts of data in a seamless and near real-time fashion. Edge computing has emerged as a means to minimise the time to handle events by enabling processing (i.e., operators) to be offloaded from the Cloud to the edges of the Internet, where the data is often generated. Deciding where to execute such operations (i.e., edge or cloud) during application deployment or at runtime is not a trivial problem. One of my goals is to improve performance metrics by introducing mechanisms for deploying DSP applications across Cloud and edge resources. I also participate in the research projects of Professor Eyal de Lara.
- 2016 - 2019: Ph.D. in Computer Science.
- Title: Algorithms for big data analytics. Thesis here
- Advisors: Marcos Dias de Assunção and Laurent Lefèvre.
- Hosting team: AVALON-Team in LIP at ENS-Lyon.
- Defense: September 2019.
- Approach: I worked on the subject “Algorithms for Elastic Big-Data Stream Analytics” where I developed QoS-aware mechanisms for (re)configuring data stream processing applications across edge and cloud resources. During my investigation, I introduced models and solutions for placing (near)real-time applications on heterogeneous infrastructures addressing single and multiple performance metrics. The techniques and methods covered by the research include: queueing theory, Markov Decision Process (MDP), Reinforcement Learning (RL), series-parallel graphs, Monte-Carlo Tree Search (MCTS), Temporal Difference Tree Search (TDTS), Q-learning and greedy algorithms.
- 2012 - 2014: M.Sc. in Computer Science.
Other paper reviews
- Review for CCGrid 2017, IEEE Globecom 2017, and IEEE Globecom 2018.
- September 23, 2019: Ph.D. defense [talk] entitled “Quality of Service Aware Mechanisms for (Re)Configuring Data Stream Processing Applications on Highly Distributed Infrastructure”.
- August 30, 2019: I was invited to be a PC member of ICPP 2020.
- August 21-23, 2019: I visited the University of Toronto and I also gave a talk [talk].
- August 7, 2019: A paper titled “Monte-Carlo Tree Search and Reinforcement Learning for Reconfiguring Data Stream Processing on Edge Computing” was accepted at The International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2019).
- August 5, 2019: I attended the 48th International Conference on Parallel Processing and I gave a [talk].
- May 21, 2019: A paper entitled “Multi-Objective Reinforcement Learning for Reconfiguring Data Stream Analytics on Edge Computing” was accepted at 48th International Conference on Parallel Processing (ICPP).
- May 17, 2019: I attended the 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing held in Larnaca, Cyprus and I gave a [talk].
- February 16, 2019: A paper entitled “Distributed Operator Placement for IoT Data Analytics Across Edge and Cloud Resources” was accepted at IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing (CCGrid 2019).
- November 12-15, 2018: I attended the 16th International Conference on Service Oriented Computing held in Hangzhou, Zhejiang, China and I gave a [talk].
- July 23, 2018: A paper entitled “Latency-Aware Placement of Data Stream Analytics on Edge Computing” was accepted at International Conference on Service Oriented Computing (ICSOC).
- July 10, 2018: I attended the USENIX Workshop on Hot Topics in Edge Computing held in Boston, MA, USA.
- June 23, 2018: A poster entitled “Latency-Aware Strategies for Placing Data Stream Analytics onto Edge Computing” was accepted at USENIX Workshop on Hot Topics in Edge Computing (HotEdge ‘18).
- June 28-30, 2017: I attended the COMPAS held in Sophia-Antipolis, France and I gave a [talk].
- April 29, 2017: A paper was accepted in the Conférence d’informatique en Parallélisme, Architecture et Système(COMPAS).
- October 7, 2017: A paper titled “Resource Elasticity for Distributed Data Stream Processing: A Survey and Future Directions” was accepted at Journal of Network and Computer Applications.
- July 27-30, 2015: I attended the 21st International Conference on Parallel, and Distributed Processing Techniques and Applications held in Las Vegas, Nevada, US and I gave a [talk]
- April 30, 2015: A paper entitled “BSPonP2P: Towards Running Bulk-Synchronous Parallel Applications on P2P Desktop Grids” was accepted at International Conference on Parallel and Distributed Processing Techniques and Applications.