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Piotr A Cholda
AGH University of Science and Technology
Krakow, Poland

Piotr Cholda specializes in the design of computer and communications networks. At the beginning of his career, his research focused on reliability modeling and the optimization of resilient multilayer long-haul networks (like the ones based on generalized multiprotocol label switching (GMPLS); he later moved toward softer problems, like the effective provisioning of services to network clients. His interests extend to problems embracing so-called quality of recovery (QoR), resilience-based differentiation, and quality of service (QoS)/QoR for peer-to-peer networking. Recently, Piotr has focused on risk-based communications networking, which he perceives as a very promising research field. In this area, the interface between business needs and threats from one side and the resilience technology from the other can be used to obtain a practical equilibrium where a balance between client needs and technological possibilities can be found.

Piotr graduated from AGH University of Science and Technology (Krakow, Poland) with an MS in networking in 2001. He obtained a doctorate in telecommunications in 2006 from the same university. He then joined the Department of Telecommunications there, and is now an assistant professor.

Piotr is the co-author of 36 refereed technical papers (11 of which are published in journals) and two conference tutorials. He has worked on network recovery problems in the following European projects: IP Nobel/Nobel II, NoE EuroNGI/EuroFGI, STREP SmoothIT, and the NoE Euro-NF EU Project. Piotr was a technical program committee (TPC) co-chair of NGI 2008 and NGI 2012, a TPC co-chair of the Communications QoS, Reliability and Modelling Symposium at ICC 2011, and a TPC co-chair of DRCN 2011. Now, he serves as a TPC co-chair for NOMS 2014.

Aside for preparing reviews for Computing Reviews, Piotr serves as an editor of the book review column in IEEE Communications Magazine. He is a member of the ACM and IEEE.


Practical explainable AI using Python: artificial intelligence model explanations using Python-based libraries, extensions, and frameworks
Mishra P., Apress, New York, NY, 2022. 364 pp.  Type: Book (978-1-484271-57-5)

In recent years, the overwhelming successes provided by artificial intelligence (AI) and machine learning (ML) methods have been stunning. All computer scientists know about very efficient picture tagging with convolutional neural networks (CNNs) ...


Behavioral Cybersecurity: Applications of Personality Psychology and Computer Science
Patterson W., Winston-Proctor C., CRC Press, USA, 2019. 261 pp.  Type: Book (978-1-138617-78-0)

It is a well-known fact that the weakest element of all cryptographic systems is a human being. No matter how smart mathematical methods are embedded to protect our network and computer infrastructures, nor how precisely we design the ...


 Foundations of deep reinforcement learning: theory and practice in Python
Graesser L., Loon Keng W., Pearson, Boston, MA, 2019. 416 pp.  Type: Book (978-0-135172-38-4)

Even for specialists well acquainted with more classical topics in machine learning, for example, plain supervised or unsupervised tasks (regression, classification, clustering, and the like), reinforcement learning (RL) can be quite c...


 Bringing Bayesian models to life
Hooten M., Hefley T., CRC Press, Boca Raton, FL, 2019. 573 pp.  Type: Book (978-0-367198-48-0)

We are used to classical statistics, yet in many important contemporary applications, such as the estimation of parameters in machine learning, a second branch of statistics based on Bayesian methods is very attractive. Therefore, a bo...


Abstract algebra with applications
Terras A., Cambridge University Press, New York, NY, 2019. 328 pp.  Type: Book (978-1-107164-07-9)

Any experienced teacher of a classical field of mathematics who wishes to publish a new textbook in such an area has to figure out how to present a topic with a long tradition to a new generation of readers. One approach is to present ...


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