Krzysztof Walkowiak

Professor

Wroclaw University of Science and Technology

Poland

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Professor Krzysztof Walkowiak is a faculty member at Wroclaw University of Science and Technology in Poland. His research areas include machine learning applications in TinyML systems, optical network optimization, and the planning and dimensioning of 5G networks. He has contributed to various recent articles focusing on robust network architectures and the impact of data compression on energy consumption in microcontroller-based systems.

Articles (18)

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2025

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2025

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2021

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2020

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2020

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2020

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2020

Collaborators (6)

Halina Kwasnicka

Head up to 2020, current full professor

University of Wrocław

POLAND

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Szymon Wojciechowski

Wrocław University of Scince and Technology

POLAND

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Michal Aibin

CANADA

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Suresh Subramaniam

George Washington University

UNITED STATES

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Aleksandra Knapińska

Research and Teaching Assistant

Wrocław University of Scince and Technology

POLAND

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Pawel Ksieniewicz

assistant professor

University of Wrocław

POLAND

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Krzysztof Walkowiak

Research Interests

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Articles (18)

Graph-Based Machine Learning Estimation Methods for Backbone Optical Network Optimization

A Novel One-Versus-All Approach for Multiclass Classification in TinyML Systems

PRODIGY+: a robust progressive upgrade approach for elastic optical networks

Data-Driven Model for Sliced 5G Network Dimensioning and Planning, Featured With Forecast and “what-if” Analysis

Machine Learning Assisted Provisioning of Time-Varying Traffic in Translucent Optical Networks

Certainty-Based Neural Network Architecture Selection Framework for TinyML Systems

Link load prediction in an optical network with restoration mechanisms

Cost-Aware DU Placement and Flow Routing in 5G Packet xHaul Networks

Incremental Recursive Ranking Grouping for Large Scale Global Optimization

Study of the Impact of Data Compression on the Energy Consumption Required for Data Transmission in a Microcontroller-Based System

Long-term Traffic Forecasting in Optical Networks Using Machine Learning

TinyML-Based Concept System Used to Analyze Whether the Face Mask Is Worn Properly in Battery-Operated Conditions

Hybrid Regression Model for Link Dimensioning in Spectrally-Spatially Flexible Optical Networks

Machine Learning Classification and Regression Approaches for Optical Network Traffic Prediction

Monte Carlo Tree Search with Last-Good-Reply Policy for Cognitive Optimization of Cloud-Ready Optical Networks

A performance study of dynamic routing algorithm for SDM translucent optical networks with assistive storage

Fragmentation metrics and fragmentation-aware algorithm for spectrally/spatially flexible optical networks

Splitting the fitness and penalty factor for temporal diversity increase in practical problem solving

Collaborators (6)

Halina Kwasnicka

Szymon Wojciechowski

Michal Aibin

Suresh Subramaniam

Aleksandra Knapińska

Pawel Ksieniewicz

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