Plenary Talks

FUZZ-IEEE has a long tradition of inviting illustrious speakers, which have strongly contributed with their research to the area of fuzzy logic theory and applications. Also for the 2017 edition, plenary talks are chosen with an eye to highlighting state-of-the-art hot topics in fuzzy logic area, providing retrospectives of technology advances, and highlighting the high applicability of fuzzy sets to different and heterogenous application domains. The FUZZ-IEEE 2017 Program Committee is pleased to announce that the following plenary presentations (in alphabetical order with respect to the last name of speakers) will be held in the beautiful scenario of Naples.

Derek T. Anderson

Fusion here, there and almost everywhere in computer vision - driving new advances in fuzzy integrals

Computer vision is a well-known area where computational intelligence has made a significant impact. In general, the field is diverse and objectives range from filtering to object detection, image understanding and linguistic summarization/description, to name a few. As simple as it may sound, we have been trying to make a computer “describe what it saw” since the 1960s. In an attempt to achieve this goal, researchers have looked to data/information fusion. However, most classical aggregation strategies are additive and assume independence among inputs. On the other hand, fuzzy measure theory provides a powerful parametric way to specify or learn input interactions (when/if available). More importantly, the fuzzy integral utilizes the fuzzy measure to achieve nonlinear aggregation. In this talk, I will discuss the role of nonlinear aggregation via fuzzy integrals at the levels of signal, spectrum, feature, and decision-level fusion. In particular, I highlight recently established extensions of fuzzy integrals designed to address key challenges in computer vision. These extensions focus on spatial and/or distribution level uncertainty and they are embedded into pattern recognition or automated decision making via multiple kernel learning and/or fuzzy logic. Applications are discussed for multi-sensor humanitarian demining, hyperspectral image analysis and remote sensing.

Oscar Cordon

Using Computational Intelligence to automate Craniofacial Superimposition for Skeleton-based Human Identification

Craniofacial superimposition is a skeleton-based, forensic identification technique that can provide evidence to support that some human skeletal remains belong or not to a missing person. The process aims to overlay a skull with some ante-mortem images of a candidate in order to determine if they correspond to the same person. Although craniofacial superimposition has been in use for over a century, there is not a common methodology accepted worldwide. Instead, each forensic anthropologist applies a specific approach considering her expert knowledge and the available technologies. Hence, there is a strong interest in designing systematic and automatic methods to support the forensic anthropologist to apply craniofacial superimposition, avoiding the use of subjective, error-prone, and time-consuming manual procedures. The use of computational intelligence is a natural way to achieve this aim. In particular, evolutionary algorithms and fuzzy sets can properly be used to automate the procedure while handling the underlying uncertainty. This talk is devoted to present an intelligent system for craniofacial identification developed in collaboration with the University of Granada’s Physical Anthropology Lab within a ten year long research project. Our system is composed of a three-stage procedure involving the automatic reconstruction of 3D models of human skulls using evolutionary algorithms and image registration methods, the obtaining of 3D skull model – 2D face photograph overlays based on evolutionary algorithms and fuzzy sets, and the determination of a degree of support for the assertion that that the skull and the ante-mortem image belong to the same person by a decision support system based on fuzzy aggregations and computer vision techniques. The resulting system is protected by an international patent and is currently under commercialization in Mexico. The results obtained in several real-world cases solved by the Physical Anthropology Lab in cooperation with the Spanish Scientific Police will be reported.

Jonathan M. Garibaldi

Type-2: Beyond the Centroid

Type-2 fuzzy sets and systems, including both interval and general type-2 sets, are now firmly established as tools for the fuzzy researcher that may be deployed on a wide range of applications and in a wide set of contexts. However, in many situations the output of type-2 systems are type-reduced and then defuzzified to an interval centroid, which are then often even simply averaged to obtain a single crisp output. Many successful applications of type-2 have been in control contexts, often focussing on reducing the RMSE. This is not taking full advantage of the extra modelling capabilities inherent in type-2 fuzzy sets. In this talk, I will present some of the current research being carried out within the LUCID group at Nottingham, and wider, into type-2 for modelling human reasoning, including approaches and methodologies which make more use of type-2 capabilities.

Chin-Teng Lin

Computational Intelligence for Brain Computer Interface

Brain-Computer Interface (BCI) enhances the capability of a human brain in communicating and interacting with the environment directly. BCI plays an important role in natural cognition, which concerns the studies of brain and behavior at work for enhancing or restoring cognitive functions. Many people may benefit from BCI, which facilitates continuous monitoring of fluctuations in cognitive states under monotonous conditions in workplace or at home. People who suffer from episodic or progressive cognitive impairments in daily life can also benefit from BCI. In this talk, I will first introduce the current status of BCI and its major obstacles: lack of wearable EEG devices, various forms of noise contamination, user/circadian variability, and lack of suitable adaptive cognitive modeling. I will then introduce some methodologies to overcome these obstacles, including discovering the fundamental physiological changes of human cognitive functions at work and then utilizing these main bio-findings and computational intelligence (CI) techniques to monitor, maintain, or track human cognitive states and operating performance. In the second part of my presentation, I will introduce an innovative BCI-inspired research domain called Cyber-Brain-Physical Systems. Some future research directions in this domain will be explored and discussed, including BCI-embedded wearable computing, BCI-based neuro-prosthesis and assistive devices, wearable cognitive robots, and BCI-empowered training. The potential real-life applications of BCI on various aspects of training/education, healthcare, rehabilitation, and medical treatment will also be introduced and discussed.

Gabriella Pasi

The role of aggregation guided by fuzzy quantifiers in Information Retrieval and in Social Media Analytics

Various processes related to the task of Information Retrieval (IR) can be interpreted as Multi Criteria Decision Making activities. The same applies to some tasks related to the analysis of user generated content in Social Media (like for example the assessement of veracity of online reviews). What is particularly interesting in this interpretation is the role of aggregation operators, which, for a given alternative, reduce the performace-scores of the considered criteria into a global performace-score of the alternative. In fact, depending on the selected aggregation strategy, different behaviors can be modelled for the considered process, corresponding to distinct predictive models. These behaviors can be more intuitively captured by guiding the aggregation by means of fuzzy quantifiers (quantifiers guided aggregation). Formally, this can be achieved by employing fuzzy integrals and quantifier guided OWA aggregation. As an example, in Information Retrieval the assessment of the relevance a document (an alternative) to a query can be seen as the process of evaluating the performance of several relevance dimensions (criteria) like topicality, novelty, recency, etc. In relation to the analysis of user generated content, an example is offered by the assessment of the veracity of an online review (alternative), which is based on several features (criteria). In this lecture the impact of quantifier guided aggregation (and of aggregation in general) will be shown in both contexts of IR and of the assessment of veracity of user generated contents. It will be also shown that this quantifier guided aggregation offers an interesting alternative to the application of machine learning techniques (in particular classifiers).

Kimon P. Valavanis

Navigation and Control of Unmanned Vehicles: A Fuzzy Logic Perspective

When dealing with navigation/control of (semi-) autonomous robotic vehicles in obstacle filled dynamic environments, Fuzzy Logic offers a reliable and viable alternative to conventional controller design and analytic techniques, as it is capable of handling environment uncertainty that is difficult if not impossible to model, as well as system modeling uncertainties without affecting system robustness nor adversely impacting performance.
This talk presents a generalized Fuzzy Logic based hierarchical architecture and framework along with its application specific modifications for aerial, aquatic and terrestrial robotic vehicle sensor-based autonomous navigation and control. For such applications, a mathematical model of the dynamics of the vehicle is not needed during the design process of the motion controller; however, the problem-specific heuristic control knowledge is needed for the inference engine design. From the practical and implementation point of view, it is shown that Fuzzy Logic is the most appropriate modeling tool to represent imprecision and uncertainty of sensor readings, and for hardware implementation of fuzzy controllers in real-time due to low computation time.
Experimental and simulation studies and results validate and support implemented techniques and approaches to ground, aerial and underwater vehicles, followed by a comparative study of classical and soft computing based controllers designed to control small unmanned helicopters.

Gabriella Pasi is Full Professor at the Department of Informatics, Systems and Communication (DISCo) of the University of Milano Bicocca, Milano, Italy. Within DISCo she leads the Information Retrieval Lab. Her main research activities are related to Information Retrieval and Information Filtering. In recent years she has addressed the issues of contextual search and user modelling. She is also conducting research activities related to the analysis of user generated content on social media. She has published more than 200 papers on International Journals and Books, and on the Proceedings of International Conferences. She is involved in several activities for the evaluation of research; in particular, she was appointed as an expert of the Computer Science panel for the Starting Grants (till 2011), and Consolidator Grants (2012) of the Programme Ideas at the European Research Council. Since 2013 she is the President of the European Society for Fuzzy Logic and Technologies (EUSFLAT). She is a member of the Editorial Board of several international journals, and she has delivered several keynote talks/plenary lectures at international conferences related to her research interests. She has participated to the organization of several International events, in both roles of organization and program chair.
Prof. Oscar Cordón is Full Professor at the Department of Computer Science and Artificial Intelligence in the University of Granada (UGR) in Spain. He created and headed the Virtual Learning Centre from 2001 to 2005 and he is currently Vice-Rector for Digital University at the UGR. From April 2006 to December 2015, he was also affiliated to the European Centre for Soft Computing, a private international research center, where he first acted as founding Principal Researcher of the Applications of Fuzzy Logic and Evolutionary Algorithms Research Unit until August 2011 and later as Distinguished Affiliated Researcher until December 2015. Prof. Cordón received the UGR Young Researcher Career Award in 2004, the IEEE CIS Outstanding Early Career Award in its 2011 edition, the first such award conferred, the IFSA Award for Outstanding Applications of Fuzzy Technology also in 2011, and the Spanish National Award on Computer Science ARITMEL by the Spanish Computer Science Scientific Society in 2014. He has published more than 330 peer-reviewed scientific publications, including 91 JCR-SCI-indexed journals and a co-authored book published by World Scientific in 2001 with 1141 citations in Google Scholar. He is included among the 1% most cited researchers in the World (source: Thomson’s Web of Knowledge), with 3206 citations from 2032 different citing articles, h index of 28, in the Web of Knowledge, and 10280 citations, h index of 47, in Google Scholar. He has coordinated 26 research projects and contracts with an overall budget of 6,7M€. He is currently or was Associate Editor of 16 journals, 7 of them indexed in the SCI-JCR. He is also inventor of an international patent under exploitation and has advised 16 PhD dissertations, one of them recognized with the EUSFLAT Best Ph.D. Thesis Award in 2011. He is an IEEE member since 2004 (senior member since 2011) and has enjoyed many different representations for reputed international societies such as the IEEE Computational Intelligence Society: founder and chair of the Genetic Fuzzy Systems Task Force (2004-2007); member of the Fuzzy Systems Technical Committee (2004-2013); member of the Graduate Student Research Grants sub-committee (2009-2011); elected member of the Administrative Committee (AdCom); member of the Outstanding Computational Intelligence Early Career Award sub-committee (2011-2015); member of the Outstanding PhD dissertation Award sub-committee (2016); and member of the Award Committee (2014-2015); among many others, as well as for the EUSFLAT Society: Treasurer (2005-2007) and Executive Board member (2005-07, 2009-2013). He has also been involved in the organization of many different conferences: IPC chair of IEEE EFS2006, GEFS2008 and ESTYLF2008; international co-chair of HIS2008; publicity co-chair of IEEE SCCI2009; finance co-chair of IFSA-EUSFLAT 2009; advisory board member of ISDA'09; evolutionary algorithms IPC area chair of IPMU2010; special session co-chair of 2010 IEEE CEC 2010 (WCCI 2010); Fuzzy image, speech, vision and signal processing IPC area chair of Fuzz-IEEE 2011; special session chair of Fuzz-IEEE 2013; program committe co-chair of IFSA2015, program committe co-chair of IEEE CEC 2015, General Chair of Fuzz-IEEE 2016 (WCCI 2016), and program committe co-chair of IEEE CEC 2017. His current main research interests are in the fields of: fuzzy rule-based systems; genetic fuzzy systems; fuzzy and linguistic modeling; evolutionary algorithms, ant colony optimization and other metaheuristics; soft computing applications to different topics (medical image registration, forensic anthropology, assembly line balancing, information retrieval etc.); visual science maps design and mining; multiobjective graph-based data mining; and agent-based modeling, social networks, and their applications in marketing science.
Derek T. Anderson received his Ph.D. in Electrical and Computer Engineering (ECE) from the University of Missouri in 2010. He is an Assistant Professor in ECE at Mississippi State University (MSU). Prof. Anderson also holds an Intermittent Faculty Appointment with the U.S. Naval Research Laboratory, he is an IEEE Senior Member and Associate Editor for the IEEE Trans. on Fuzzy Systems. His research interests include new frontiers in data/information fusion for pattern recognition and automated decision making in signal/image understanding and computer vision with an emphasis on uncertainty and heterogeneity. Prof. Anderson’s primary research contributions to date include multi-source (meaning sensor, algorithm and human) fusion, Choquet integrals (extensions, embedding’s, learning), signal/image feature learning, multi-kernel learning, cluster validation, hyperspectral image understanding and linguistic summarization of video. He has been funded by the U.S. Air Force Research Laboratory (AFRL), Camgian, U.S. Army and Night Vision and Electronics Sensors Directorate (NVESD), U.S. Army Engineering Research and Development Center (ERDC), Pacific Northwest National Laboratory (PNNL), the National Institute of Justice (NIJ), and DARPA. Prof. Anderson is the also the Co-Director of the Sensor Analysis and Intelligence Laboratory (SAIL) in the Center for Advanced Vehicular Systems (CAVS) at MSU, a multi-disciplinary collaborative research laboratory with sensors ranging from hyperspectral in the visible and near, mid and long infrared to radar, lidar, stereoscopic, and light field cameras. SAIL is focused on fusion and scene/environment understanding in the areas of robotics, autonomous systems and ground/aerial vehicles, and remote sensing from UAVs for agriculture and biological earth observations. Derek has published over 90 articles; book chapters, journal manuscripts and conference proceedings. More details can be found at:
Professor Jonathan M. Garibaldi received the B.Sc (Hons) degree in Physics from Bristol University, UK in 1984, and the M.Sc. degree in Intelligent Systems and the Ph.D. degree in Uncertainty Handling in Immediate Neonatal Assessment from the University of Plymouth, UK in 1990 and 1997, respectively. He is Head of School of Computer Science at the University of Nottingham, UK, leads the Intelligent Modelling and Analysis (IMA) Research Group, and is Director of the Advanced Data Analysis Centre (ADAC). The IMA research group undertakes research into intelligent modelling, utilising data analysis and transformation techniques to enable deeper and clearer understanding of complex problems. His main research interests are modelling uncertainty and variation in human reasoning, and in modelling and interpreting complex data to enable better decision making, particularly in medical domains. He has made many theoretical and practical contributions in fuzzy sets and systems, and in a wide range of generic machine learning techniques in real-world applications. Prof. Garibaldi has published over 200 papers on fuzzy systems and intelligent data analysis, and is taking over as the Editor-in-Chief of IEEE Transactions on Fuzzy Systems from Jan 2017. He has served regularly in the organising committees and programme committees of a range of leading international conferences and workshops, such as FUZZ-IEEE, WCCI, EURO and PPSN.
Dr. Chin-Teng Lin received the B.S. degree from National Chiao-Tung University (NCTU), Taiwan in 1986, and the Master and Ph.D. degree in electrical engineering from Purdue University, USA in 1989 and 1992, respectively. He is currently the Distinguished Professor of Faculty of Engineering and Information Technology, University of Technology Sydney. Dr. Lin also own Honorary Chair Professorship of Electrical and Computer Engineering, NCTU, International Faculty of University of California at San-Diego (UCSD), and Honorary Professorship of University of Nottingham. Dr. Lin was elevated to be an IEEE Fellow for his contributions to biologically inspired information systems in 2005, and was elevated International Fuzzy Systems Association (IFSA) Fellow in 2012. Dr. Lin received the IEEE Fuzzy Systems Pioneer Award in 2017, Outstanding Achievement Award by Asia Pacific Neural Network Assembly in 2013, Outstanding Electrical and Computer Engineer, Purdue University in 2011, and Merit National Science Council Research Fellow Award, Taiwan in 2009. He is elected as the Editor-in-chief of IEEE Transactions on Fuzzy Systems since 2011. He also served on the Board of Governors at IEEE Circuits and Systems (CAS) Society in 2005-2008, IEEE Systems, Man, Cybernetics (SMC) Society in 2003-2005, IEEE Computational Intelligence Society (CIS) in 2008-2010, and Chair of IEEE Taipei Section in 2009-2010. Dr. Lin is the Distinguished Lecturer of IEEE CAS Society from 2003 to 2005, and CIS Society from 2015-2017. He served as the Deputy Editor-in-Chief of IEEE Transactions on Circuits and Systems-II in 2006-2008. Dr. Lin was the Program Chair of IEEE International Conference on Systems, Man, and Cybernetics in 2005 and General Chair of 2011 IEEE International Conference on Fuzzy Systems. Dr. Lin is the coauthor of Neural Fuzzy Systems (Prentice-Hall), and the author of Neural Fuzzy Control Systems with Structure and Parameter Learning (World Scientific). He has published more than 200 journal papers and 80 patents (H-index: 56) in the areas of computational intelligence, fuzzy neural networks, natural cognition, brain-computer interface, intelligent system, multimedia information processing, machine learning, robotics, and intelligent sensing and control, including approximately 104 IEEE journal papers.
Dr. Kimon P. Valavanis received the Diploma in Electrical and Electronic Engineering (Diplôme Ingénieur, 5 years of study) from the National Technical University of Athens, Greece, in 1981, the M.Sc. degree in Electrical Engineering and the PhD degree in Computer and Systems Engineering from Rensselaer Polytechnic Institute (RPI)in 1984 and 1986, respectively. He is currently John Evans Professor and Chair of Electrical and Computer Engineering, University of Denver, and Director of the DU Unmanned Systems Research Institute.
His research interests focus on the areas of Robotics and Automation and Unmanned Systems. He has authored/co-authored and edited 19 books the most recent being: On Integrating Unmanned Aircraft Systems into the National Airspace System: Issues, Challenges, Operational Restrictions, Certification, and Recommendations (with K. Dalamagkidis and L. A. Piegl), 2nd Edition, Springer 2012; Linear and Nonlinear Control of Small Scale Unmanned Rotorcraft (I. A. Raptis, K. P. Valavanis), Springer, 2012, which has also been translated into Chinese; Handbook of Unmanned Aerial Vehicles (UAVs) (editors, K. P. Valavanis, G. J. Vachtsevanos), Springer, 2015, which is the only handbook published worldwide – a five-Volume Handbook that includes all aspects of UAVs, also translated into Chinese – a 2nd Edition is now in progress, to be published by Springer in 2017; Foundations of Circulation Control Based Small-Scale Unmanned Aircraft: A Comprehensive Methodology from Concept to Design and Experimental Testing (K. Kanistras, K. P. Valavanis, M. J. Rutherford), and, Modeling, Navigation and Control of a Small-Scale Flybarless Unmanned Rotorcraft (J. Alvarenga, K. P. Valavanis, M. J. Rutherford). He has also published more 30 book Chapters, 110 transaction/journal papers and more than 200 referred conference papers.
During his Academic career thus far, Dr. Valavanis has graduated 38 PhD students. He is Fellow of the American Association for the Advancement of Science and a Fellow of the U.K Institute of Measurement and Control, a senior Member of IEEE and a Fulbright Scholar (Senior Lecturing & Research Award).