麻豆传媒

Dr Tomasz Szydlo is a Senior Lecturer in the School of Computing at 麻豆传媒, UK. He has joined the NUSE group, where he explores the IoT and TinyML research areas. Up till then, he held the position of associated professor in the , which is part of the at the . In 2005, he cooperated with the Machine Learning and Inference Laboratory at George Mason University, working on the conversion of rules into decision trees. In 2008, he was an intern at IBM Hursley, UK, where he worked on integrating the MQTT protocol with service-oriented device architectures. Since that time, he has participated in several EU and national research projects. In 2010, he defended his PhD at the AGH-UST, which focused on QoS-driven semantics-based SOA applications composition and execution. Then, he obtained a habilitation degree in computer science in 2019 for work on methods and mechanisms for Internet of Things systems characterized by variable operation policies and restrictions.

My current research interests cover two intersecting aspects - organization of data processing on cloud-edge-device continuum and computer systems sustainability:

• We live in times when the Internet of Things systems, including smart homes, smart cities, and the fourth industrial revolution based on cyber-physical systems, are not unusual. Millions of devices and machines are sources of sensor data streams that require continuous analysis on the fly and, later, in-depth analysis using big data processing. The 5G technology, edge computing, and computational clouds are enablers for this kind of applications. The research problem is how to organize computation and distribute it on the available infrastructure to provide the desired data processing quality and how to process the collected data efficiently.
• Unfortunately, developing computing infrastructure for modern computing systems' needs is not without significance for the environment because it requires a lot of energy and thus has a large carbon footprint. Several solutions, such as energy-efficient processors and architectures, are introduced to reduce energy consumption. The promising approach is to power these devices with renewable energy sources, such as photovoltaic panels that absorb solar radiation and generate electricity. Nevertheless, the optimal use of renewable energy sources requires intelligence in resource management. The research problem is how to manage stream processing and data-at-rest in such a way as to take into account the dynamics of changes in renewable energy-supplying computing centres both in the cloud and on edge.
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I believe these issues are crucial in developing computer systems for future generations. In my work, I try to build prototypes of computer systems using new technologies, including virtualization, cloud computing, Internet of Things devices and machine learning, so that it is possible to manage the data processing and, at the same time, operate sustainably.

Research topics: Mobile systems, Computer networks, Internet Of Things, Machine Learning, TinyML, Sustainable computing