RESEARCH

Research Interests

• Distributed systems
• Cybersecurity
• Artificial Intelligence

I work on the design and optimization of distributed systems, their security and resilience, and the application of artificial intelligence to enhance system performance, threat detection, and decision-making. My work bridges theoretical foundations with practical solutions for real-world computing environments.

For those of you wondering what distributed systems are?

Behind every seamless digital experience, whether on the web or mobile, lies a world most people never see. When you send a message, watch a video, or request a ride, you are not talking to a single machine. You are interacting with an entire ecosystem. Dozens, hundreds, sometimes thousands of computers spread across the globe collaborate in real time to make that action work.

This is the essence of distributed systems: many independent machines behaving as one.

They coordinate, recover from failures, defend against cyber threats, balance overwhelming traffic, and make split-second decisions, all while giving us the illusion of simplicity and effortlessness. Distributed systems are not just a concept. They are the invisible machinery holding our digital world together.

Current Research Projects

• Leveraging AI for Cybersecurity: Threat Intelligence and Threat Hunting

Journal Reviews | Web of Science

• ACM Computing Surveys, ISSN 1557-7341, ACM
• IEEE Transactions on Vehicular Technology, ISSN 1939-9359, IEEE
• IEEE Access, ISSN 2169-3536, IEEE
• Journal of Parallel and Distributed Computing, ISSN 0743-7315, Elsevier
• Expert Systems with Applications, ISSN 0957-4174, Elsevier
• Computing, ISSN 1436-5057, Springer
• Peer-to-Peer Networking and Applications, ISSN 1936-6450, Springer
• Wireless Personal Communications, ISSN 1572-834X, Springer
• Sensors, ISSN 1424-8220, MDPI

Technical Program Committees

• Healthcom '25 (IEEE International Conference on E-health Networking, Application & Services). Oct 21–23, 2025, Abu Dhabi, United Arab Emirates. 

• IC3IT '24 (1st International Conference on Innovative and Intelligent Information Technologies). Dec 3-5, 2024 Batna, Algeria.

• MISC '22 (7th International Symposium on Modelling and Implementation of Complex Systems). Oct 30-31, 2022, Mostaganem, Algeria.
• ACM Q2SWinet '21 (17th ACM International Symposium on QoS and Security for Wireless Mobile Networks). Nov 22-26, 2021, Alicante, Spain.
• ACM Q2SWinet '20 (16th ACM International Symposium on QoS and Security for Wireless Mobile Networks). Nov 16-20, 2020, Alicante, Spain.
• MISC '20 (6th International Symposium on Modelling and Implementation of Complex Systems). Oct 24-26, 2020, Batna, Algeria.
• ACM Q2SWinet '19 (15th ACM International Symposium on QoS and Security for Wireless Mobile Networks). Nov 25-29, 2019, Miami Beach, USA.
• ACM Q2SWinet '18 (14th ACM International Symposium on QoS and Security for Wireless Mobile Networks). Oct 28-Nov 2, 2018, Montreal, Canada.

Some Previous Research

• A Lightweight AI System for Real-Time Elderly Fall Detection.
• Distributed Systems and Big Data: Adaptive Resource Allocation for Streaming Applications in Big Data Infrastructures.
• A novel general-purpose big data platform for smart cities. This project focused on the main architectural challenges and solutions that must be considered to ease the continuous design, development, deployment, and operations of cloud-native services for smart cities. The employed technologies included OpenStack, OpenShift (Docker/K8s, Helm), Kafka, MongoDB, Neo4J, Spark, and other DevOps and machine learning tools.
• Big data architecture for connected vehicles (based on the experience and feedback of Stellantis). This work is a collaboration between academia and industry. Technical support has been provided by senior data architects at Stellantis.
• Optimized usage of MQTT in the context of connected vehicles (MQTT-CV).
• Combining deep learning and IoT technologies to achieve efficient in-city vehicle parking.
• Lightweight deep learning: classical optimized vs. new lightweight architectures.
• Ensuring long-lifetime coverage with circumferential WMSNs.
• Boundary traversal in WSNs.
• Sequential anti-void processing of spatial-window queries in WSNs.  
• Efficient in-network data aggregation from large-scale WSNs.
• Efficient distributed graph traversal. The proposed novel algorithms (namely, Peeling Algorithm, Spreading Aggregation, and Geometric Serial Search) approximate the optimal number of hops in most of the cases (they require n - 1 communications to traverse a network of n nodes). The key idea consists of using a single packet that can jump from node to node and traverse/query any connected network.
• Load-balancing and cluster-based data communication in WSNs.
• Algorithm-architecture adequation.