Continuing Education

The Sub-Committee on Continuing Education of the IEEE Computational Intelligence Society (CIS) aims at providing members, designers and researchers in the industrial sector with assistance and support for using tools of computational intelligence and their applications to various industrial sectors. There are two potential missions here. The first is to make industry aware of the unique capabilities and appropriate applications of computational intelligence techniques, the second are modules used to train industrial researchers in particular niche.

Current/Ongoing Projects

• The Sub-Committee has embarked on an ambitious project, involving the creation of a wiki document in the form of an online Handbook on Computational Intelligence for Industrial Applications. At this stage a few pages have been filled by members of the committee. We plan to make it a full fledged wiki document, where contributors log on into the system and provide content to various sections of the Handbook. The link of the Handbook (which is under continuous construction/update) is: http://ciscedu.org/continuing-education
• An edited volume or volumes on the teaching of computational intelligence.
• Indexing existing videos on computational intelligence as a web resource. This is supposed to tie into the existing tutorials repository and extend it.
• Writing training modules for industrial outreach. There are two potential missions here. The first is to make industry aware of the unique capabilities and appropriate applications of computational intelligence techniques, the second are modules that train industrial researchers in particular techniques.

Existing Resources

The committee puts at the disposal of its members a large repository or archived material, including lectures, tutorials, webinars, and courses. Most of these resources are part of the IEEE CIS Video Collection available to members at large. The Committee will target among this knowledge base, pertinent material that can be used by members of the industrial sectors.

Selected Material by Topic

Lectures/Plenary Talks:

• Neural Networks: Past, Present and Future (S. Grossberg)
• Pattern Recognition (J. Bezdek)
• Fuzzy Reinforcement Learning (H. Berenji)
• Model Based Fuzzy Logic Control (G. Feng and Z. Zeng)
• Overview on Fuzzy Set Systems (M. Berthold)

Courses:

• Introduction to Fuzzy Systems (R. Kruse)
• Introduction to Neural Networks (F. Karray)
• Introduction to Bayesian Networks (R. Kruse)
• Genetic Programming with Applications (R. Poli)

Tutorials/Webinars:

• Computational Finance & Economics (E. Tsang)
• Tutorial on Evolutionary Computation in Bioinformatics (G. Fogel and K. Wiese)
• Particle Swarm Optimization (R. Eberhart)
• Lectures on Neural Network (B. Widrow)
• Support Vector Machines and Kernel Based Learning(J. Suykens)
• A Gentle Introduction to Evolutionary Computation (X. Yao)
• Fuzzy Type 2 Systems (J. Mendel)

Contact

For further information on the committee or if you wish to take part in its various activities, please email the Sub-Committee Chair, Dipti Srinivasan, or any other members of the Committee.