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Keynote Speakers

KEYNOTE SPEAKERS LIST

Kevin Warwick, University of Reading, United Kingdom
          Title: The Disappearing Human-Machine Divide

Leslie Smith, University of Stirling, United Kingdom
          Title: To be announced

Juan J. Merelo, Universidad de Granada, Spain
          Title: The Art of Programming Evolutionary Algorithms

Eyke Hüllermeier, Philipps University of Marburg, Germany
          Title: Learning from Imprecise and Fuzzy Data: on the Notion of Data Disambiguation

Belur V. Dasarathy, Information Fusion, United States
          Title: Information Fusion - An Appealing Avenue for Robust Knowledge Discovery in Multi-Source Enviroments

 

Keynote Lecture 1
The Disappearing Human-Machine Divide
Kevin Warwick
University of Reading
United Kingdom


Brief Bio
Kevin Warwick is Professor of Cybernetics at the University of Reading, England, where he carries out research in artificial intelligence, control, robotics and biomedical engineering. He took his first degree at Aston University, followed by a PhD and research post at Imperial College London. He subsequently held positions at Oxford, Newcastle and Warwick Universities before being offered the Chair at Reading. He is a Chartered Engineer (CEng.) and is a Fellow of The Institution of Engineering & Technology (FIET). Kevin Warwick is the youngest person ever to become a Fellow of the City & Guilds of London Institute (FCGI). He is the author or co-author of more than 500 research papers and has written or edited 27 books (three for general readership), as well as numerous magazine and newspaper articles on scientific and general subjects. 

Kevin has been awarded higher doctorates (DSc) both by Imperial College and the Czech Academy of Sciences, Prague and has received Honorary Doctorates from 6 Universities. He has appeared in the Guiness Book of Records for his research on several occasions and is perhaps best known for his implant self-experimentation, linking his own nervous system with a computer network. 

Kevin instigated a series of pioneering experiments involving the neuro-surgical implantation of a device (Utah Array/BrainGate) into the median nerves of his left arm in order to link his nervous system directly to a computer to assess the latest technology for use with the disabled. The development of the implant technology was carried out by a team of researchers headed by Dr Mark Gasson who, along with Kevin, used it to perform the ground-breaking research. Kevin was successful with the first extra-sensory (ultrasonic) input for a human and with the first purely electronic communication experiment between the nervous systems of two humans. His research has been discussed by the US White House Presidential Council on BioEthics.

The Institute of Physics selected Kevin as one of only 7 eminent scientists to illustrate the ethical impact their scientific work can have: the others being Galileo, Einstein, Curie, Nobel, Oppenheimer and Rotblat.


Abstract

In this presentation Kevin will look at:
1. The latest results with implant technology (linking human brains with computers),  
2. Culturing biological neurons and putting them in a robot body (robots with biological brains) and 
3. Practical Turing Test results (can you tell the difference between a human and a machine from interactive communication?). New experimental data will be presented in each of these areas and participants will be able to see for themselves if they can tell the difference, in a Turing sense, between human and machine dialogue. A brief look will be taken at the future and what all this might mean.

 

Keynote Lecture 2
To be announced
Leslie Smith
University of Stirling
United Kingdom


Brief Bio
Available soon.


Abstract
Available soon.

 

Keynote Lecture 3
The Art of Programming Evolutionary Algorithms
Juan J. Merelo
Universidad de Granada
Spain


Brief Bio
JJ Merelo is professor at the University of Granada (Spain), where he leads the Free Software Office (http://osl.ugr.es). He arrived to evolutionary computation from artificial life, and currently is interested in complex systems (and networks), distributed evolutionary algorithms and web computing. He obtained a MSc and PhD in Physics from the same university, and also regularly publishes novels (which are also available under a free licence).


Abstract
This talk gives an holistic view of coding in science (specially in evolutionary algorithms) from idea to publication, introducing several best practices that can be used at every step of the process. It describes how scientific programming should be language-agnostic and talks about design patterns and workflows that can be used to make the process of publishing papers based on the code you write (inspired by the idea you originally had) much less painful. The set of best practices, gleaned from experience, can be applied to pretty much everybody that is in the business of scientific programming, but specially to those that work in the area of evolutionary algorithms at large.

 

Keynote Lecture 4
Learning from Imprecise and Fuzzy Data: on the Notion of Data Disambiguation
Eyke Hüllermeier
Philipps University of Marburg
Germany


Brief Bio
Eyke Hüllermeier is with the Department of Mathematics and Computer Science at Marburg University (Germany), where he holds an appointment as a full professor and heads the Computational Intelligence Group. He holds MSc degrees in mathematics and business computing, a PhD in computer science, and a Habilitation degree, all from the University of Paderborn (Germany). Prior to his current appointment, he held positions at the Universities of Dortmund, Toulouse and Magdeburg.
His research interests are focused on methodological foundations of Artificial Intelligence and intelligent systems design, especially on machine learning and data mining as well as modeling and reasoning with uncertain knowledge. Besides, he is very interested in the application of AI methods in other fields, including the life sciences, engineering and economics. He has published around 200 research papers on these topics in top-tier journals and major international conferences, and several of his contributions have been recognized with scientific awards.
Professor Hüllermeier is Co-Editor-in-Chief of Fuzzy Sets and Systems, one of the leading journals in the field of Computational Intelligence, and serves on the editorial board of several other journals, including Machine Learning, IEEE Transactions on Fuzzy Systems, International Journal on Approximate Reasoning, and Advances in Data Analysis and Classification. Moreover, he is a regular member of the program committee of major international conferences in the fields of Computational and Artificial Intelligence. He is a coordinator of the EUSFLAT working group on Machine Learning and Data Mining and the head of the IEEE CIS Task Force on Machine Learning.
Professor Hüllermeier was the General Chair of IPMU–2010, 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (Dortmund, Germany). Last year, he was a PC Co-Chair of SUM–2012, the 6th International Conference on Scalable Uncertainty Management (Marburg, Germany), and this year, he is a PC Co-Chair of DS–2013, the 16th International Conference on Discovery Science (to be held in Singapore). Next year, he will be PC Co-Chair of ECML/PDKK, the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.


Abstract
Methods for analyzing or learning from "fuzzy data" have attracted considerable attention in recent years. In many cases, however, existing methods (for precise, non-fuzzy data) are extended to the fuzzy case in an ad-hoc manner, and without carefully considering the interpretation of a fuzzy set when being used for modeling data. Distinguishing between an ontic and an epistemic interpretation of fuzzy set-valued data, and focusing on the latter, it will be argued that a "fuzzification" of learning algorithms based on an application of the generic extension principle is not appropriate. In fact, the extension principle fails to properly exploit the inductive bias underlying typical machine learning methods, although this bias, at least in principle, offers a means for "disambiguating" the fuzzy data. Alternatively, a novel method is proposed which is based on the generalization of loss functions in empirical risk minimization, and which performs model identification and data disambiguation simultaneously.

 

Keynote Lecture 5
Information Fusion - An Appealing Avenue for Robust Knowledge Discovery in Multi-Source Enviroments
Belur V. Dasarathy
Information Fusion
United States


Brief Bio
Dr. Belur V. Dasarathy, an IEEE Fellow, is an independent consultant offering services to commercial and government clients in the design and development of automated intelligent decision systems arising in a variety of applications. His expertise includes guidance, teaching, research and development (R&D) and R&D management in the areas of intelligent decision systems, learning systems, multi-sensor multi-source information fusion, knowledge discovery through pattern recognition and data mining, image analysis and other related topics. His prior professional full-time affiliations have included Dynetics, Inc., Intergraph Corp., Computer Sciences Corp., Indian Institute of Science, Southern Methodist University, as well as adjunct positions at University of Alabama in Huntsville.
He is the founding Editor-in-chief of the International Journal on Information Fusion published by Elsevier Science, the very first journal dedicated to this evolving field. He has offered short courses in the information fusion arena under SPIE and other conference sponsorships as well as under individual company/ University/ Organization sponsored on-site programs.
Dr. Dasarathy has over 180 open literature publications with him as primary author in majority of these publications. He is the author of three IEEE Computer Society Press books: Decision Fusion, Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques, and Image Data Compression: Block Truncation Coding. He has also contributed chapters/sections to other books, including one in the handbook on Data Mining and Knowledge Discovery (Oxford University Press, 2002). His publications have been cited in the literature in over 400 studies.
He has been an invited speaker at many national and international conferences over the past decade such as 2nd Intl Conference on Sensor Networks (SENSORNETS 2013), Spain;3rd International Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2013), Spain; 6th International Symposium on Intelligent Distributed Computing 2012, Italy; 16th Annual KES Conference, 2012 Spain; IDGA 9th Annual Image Fusion Summit, 2010, USA; 2008 International Conference on Aerospace Science and Technology, India; 2008 Indo-US Workshop on Regional Air Transportation, India; 2nd International Conference on Information  Security and  Assurance, 2008, Korea; Future Generation Communication and Networking, 2007 Korea; 2006 IDGA Conference on Night Vision Systems, Washington, DC; 2006 IEEE Intl Conf on Multisensor Fusion and Integration for Intelligent Systems, Germany; 2006 Biologically Inspired Information Fusion, UK; ISSNIP ’04 Australia; International Conference on Human-Machine Interface 2004, India; IEEE International Conference on Computational Cybernetics ICCC’04 Austria; The 11th International Conference on Advanced Robotics, ICAR Portugal; International Workshop on Information Fusion 2002, China; IX Spanish Symposium on Pattern Recognition and Image Processing 2001, Spain; IEEE International Conference on Industrial Technology, ICIT 2000, India; International Conference on Applications of Pattern Recognition 1998, England.
Dr. Dasarathy was honored as the IEEE Huntsville Section Outstanding Engineer 1996, IEEE Region 3 Outstanding Engineer for 1997 and a recipient of the IEEE Third Millennium Medal. He was one of the founding members of the board of directors of the International Society on Information Fusion (ISIF) and served on it for three years. He was the guest editor of Optical Engineering for three special sections on Sensor Fusion. From 1997 to 2009, he has been the organizer & chairman of two annual SPIE Conferences on multi-sensor, multi-source information fusion and data mining, intrusion detection & network security. He was the publicity chair for the International conferences on Information Fusion - Fusion 1998, Fusion 1999, Fusion 2001, a member of the executive committee of Fusion 2000, and is a member of the International Program committee for Fusion 2003. He has organized and chaired special sessions on Information Fusion and Data Mining at other conferences including IEEE Decision and Control 1998, International Joint Conference on Neural Networks 1999, IGARSS 2000, IECON-2000. He has been a member of the Scientific Committee for the annual workshop on Multiple Classifier Systems since 2000 including the one to be held in 2003. He was also the technical vice-chair for Autotestcon 2002.
His biographical citations include: International Who's Who in Information Technology, 1999; "The Official Registry of the Who' Who of American Business Leaders," 1991; ; "Who's Who in the South and Southwest," 22nd Edition, 1991; Who's Who in Technology Today," Dick Publishing 5th Edition, "Personalities of the South," American Biographical Institute, 1986; "WHO' WHO" in Computer Graphics," Marquis, 1984, etc.


Abstract
Available soon.