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Leszek Sliwko
University of Westminster
London, New York
 

Leszek Sliwko is an experienced information technology (IT) professional with over two decades of expertise in Java/Scala development and cloud/cluster systems architecture. He has a strong understanding of the software development process and a proven ability to deliver effective solutions across various industries. He has worked in sectors such as the United Kingdom (UK) government, investment banking, financial consultancy, and telecommunications. In roles such as team lead, technical architect, and principal software developer, Leszek has built a strong track record in team supervision and management.

Leszek is a skilled communicator who works effectively with both technical and business teams. Many of his projects have involved stakeholder management and collaboration with high-profile organizations, including the United Nations High Commissioner for Refugees (UNHCR) and the UK Cabinet Office. In his leadership roles, he has also conducted training sessions for junior developers, focusing on functional programming and DevOps tools.

Leszek holds a PhD in parallel and distributed computing from the University of Westminster, London, awarded for his innovative work on developing an AI-driven load balancer for cloud systems. He is a respected speaker, having presented at international events such as IEEE conferences, machine intelligence research lab lectures, and popular seminars like Scala in the City, The Forge Tech Talks, JVM Roundabout, and Scala Central. He is keen on experimenting with the latest technologies, particularly those related to high-performance computing and artificial intelligence (AI).

Leszek actively reviews for several scientific journals, and his current research focuses on applying machine learning solutions for large-scale distributed workload orchestration.


     

 Sequential-hierarchical attention network: exploring the hierarchical intention feature in POI recommendation
Ma Y., Gan M. World Wide Web 27(6): 67-67, 2024.  Type: Article

A point-of-interest (POI) recommender system has become an important and powerful tool for travelers. Such systems “model the impact of external factors on user behavior, such as time [and] geographical location, to predict future check-ins....

 

Towards combining commonsense reasoning and knowledge acquisition to guide deep learning
Sridharan M., Mota T. Autonomous Agents and Multi-Agent Systems 37(1): 2023.  Type: Article

In artificial intelligence (AI), commonsense reasoning refers to the ability to make assumptions about the characteristics and nature of everyday situations, similar to how humans perceive and interpret them. For example, it involves evaluating ph...

 

 Deep learning in medical image super resolution: a review
Yang H., Wang Z., Liu X., Li C., Xin J., Wang Z. Applied Intelligence 53(18): 20891-20916, 2023.  Type: Article

Medical image super-resolution (SR) reconstruction is an active area of research, with the potential to make medical imaging safer and more accessible by enhancing the quality of images produced with low-cost equipment or reduced radiation doses. ...

 
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