Events (Lectures, Webinars, Summer School)


To disseminate advanced knowledge on hot topics in computational intelligence seminars will be organized and distributed through the web free of charge to our members. Past webinars can also be accessed by members free of charge


Upcoming Webinars

Classification in Action: Neural Networks and Differential Evolution Classifier applied to Intrusion Detection and Cancer Data

Webinar Speaker: Prof. Simone Ludwig

Date and Time: November 11, 2019, 3 pm (GMT) Time Zone Converter

Registration URL:

Abstract: This presentation will talk about two research projects. The first investigates an Intrusion Detection data set applying a neural network ensemble classifier, and the second looks at different cancer data sets applying a differential evolution classifier. The presentation will start with an introduction to neural networks and will then describe the deep neural network ensemble that was applied to Intrusion detection data. The classification task is to differentiate between normal and intrusive behavior in a network. The second project proposes a cost-sensitive version of the centroid-based classification algorithm using differential evolution. Four imbalanced cancer data sets (Breast, Lung, Uterus, and Stomach) are investigated. The experiments investigate the survivability of cancer patients compared to the performance of the current variants. Moreover, the performance of the proposed version is compared with the performance of five cost-sensitive machine-learning algorithms.

Bio: Dr. Simone Ludwig is a Professor of Computer Science at North Dakota State University (NDSU, US) since 2010. Prior to joining NDSU she worked at the University of Saskatchewan (Canada), Concordia University (Canada), Cardiff University (UK) and Brunel University (UK). Dr. Ludwig received her PhD degree and MSc degree with distinction from Brunel University (UK), in 2004 and 2000, respectively. Before starting her academic career she worked several years in the software industry. Her research interests lie in the area of computational intelligence including swarm intelligence, evolutionary computation, neural networks, and fuzzy reasoning. Examples of application areas where computational intelligence methods are applied to are data mining (including big data), image processing, intrusion detection, cryptography, and cloud computing.


Webinars Calendar

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Summer Schools

2019 IEEE CIS Summer School on Computational Optimization and Learning
When: July 30 – Aug 1, 2019
Location: Xiamen, China

2019 IEEE CIS Summer School on Computational Intelligence Techniques for High School Students 
Location: National Cheng Kung University, Tainan, Taiwan 
When: Aug. 1-3, 2019 
Download (Report)

2019 IEEE CIS Summer School on Big Data Analytics and Stream Processing: Tools, Techniques and Application 
Location: Indian Institute of Information Technology Allahabad at Prayagraj, Uttar Pradesh, India 
When: Aug. 10-14, 2019 

2019 IEEE CIS Summer School on Computational Intelligence and Robotics 
Location: Emiliano Zapata, Morelos, Mexico 
When: Oct. 22-26, 2019 

2019 IEEE CIS Summer School on Latin American Computational Intelligence Conference
Location: Guayaquil, Ecuador
When: Nov. 11-15, 2019

2019 IEEE CIS Summer School on Computational Intelligence (XV IEEE Escuela de Verano Latino-Americana en Inteligencia Computacional, EVIC)
Location: Valdivia, Chile
When: Dec. 16-18, 2019

2019 IEEE CIS Summer School on Computational Intelligence for Human and Smart Machine Co-learning
Location: National Kaohsiung Normal University, Kaohsiung, Taiwan
When: Dec. 21-23, 2019