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Corrado Mencar Ph.D
University of Bari
Bari, Italy
 

Corrado Mencar is currently an assistant professor in the Department of Informatics at the University of Bari (Italy). He received his MS degree in Informatics in 2000 and a PhD in Informatics in 2005, both at the University of Bari. After receiving his master’s degree, he worked as a software analyst and designer for some Italian software firms. In 2005, he joined the University of Bari as an assistant professor, researching computational intelligence and related fields. His current research interests include fuzzy logic and fuzzy systems, granular computing, computational web intelligence, intelligent data analysis and genetic algorithms. The most important achievements in his research are related to the interpretability of fuzzy systems, that is, techniques for endowing fuzzy systems with empirically acquired knowledge that can be communicated to users in a way that is easy to read and understand.

He has been involved with several research projects and has written more than 60 peer-reviewed international papers. He also acts as a reviewer for several international journals, is member of the program committees of several conferences, and is an associate editor for the International Journal on Artificial Intelligence. Mencar has taught several undergraduate and graduate courses on topics related to his research, as well as courses on programming fundamentals, computer architectures and operating systems. He supervises of a number of PhD students and is the scientific supervisor of the department library.

In addition to his research interests, he is passionate about complex dynamical systems, including biological, social and natural systems. He is an avid reader of books in the field, and is a fan of Richard Dawkins, Douglas Hofstadter and Fritjof Capra.


     

Foundational Python for data science
Behrman K., Addison-Wesley Professional, Boston, MA, 2021. 256 pp.  Type: Book (978-1-366243-59-1)

The collection of books on data science is becoming so large that it is itself an interesting subject for data science analysis [1,2]. This is amply justified by the galloping success of data science among students, researchers, and practitioners ...

 

 Discrete fuzzy measures: computational aspects
Beliakov G., James S., Wu J., Springer International Publishing, New York, NY, 2020. 245 pp.  Type: Book (978-3-030153-04-5)

Decision-making is a problem-solving activity aimed at reckoning a choice by taking into account a possibly large number of constraints, preferences, beliefs, and costs, among other things. It is a complex discipline that requires soph...

 

Cause Effect Pairs in Machine Learning
Guyon I., Statnikov A., Bakir Batu B., Springer, New York, NY, 2020. 372 pp.  Type: Book (978-3-030218-09-6)

From the earliest courses in statistics we are taught that correlation does not imply causation. However, apart from some special cases, it is also generally true that causation implies correlation (or dependency). While the first sent...

 

Fuzzy collaborative forecasting and clustering: methodology, system architecture, and applications
Chen T., Honda K., Springer International Publishing, New York, NY, 2019. 100 pp.  Type: Book (978-3-030225-73-5)

Collaborative machine learning (ML)--sometimes known as federated ML--has been gaining momentum in the last few years for several in-demand reasons, including privacy-preserving data analysis, sharing complex computat...

 

Assessing and improving prediction and classification: theory and algorithms in C++
Masters T., Apress, New York, NY, 2018. 517 pp.  Type: Book (978-1-484233-35-1)

There is an increased interest in machine learning (ML) in both academy and industry. One consequence is a greater demand for textbooks and other educational materials that explain the different facets of ML to a heterogeneous readersh...

 
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