Prof. Lawrence O. Hall
University of South Florida

Title: Building Prognostic Models for Cancer from Medical Images

Medical imaging provides a noninvasive way of viewing cancerous or precancerous anomalies. The anomalies could be lung polyps or tumors, for instance. The extraction of useful features and building of learned models from CT scans of lungs and magnetic resonance images of brains will be discussed. Experiments will be shown that indicate it is possible to predict disease prognosis. The challenges of using only images for prediction will be discussed, as well as the combination of clinical and genetic information to improve prognosis prediction.

Short Biography

Lawrence O. Hall is a Distinguished University Professor and the Chair of the Department of Computer Science and Engineering at University of South Florida. He received his Ph.D. in Computer Science from the Florida State University in 1986 and a B.S. in Applied Mathematics from the Florida Institute of Technology in 1980. He is a fellow of the IEEE. He is a fellow of the AAAS and IAPR. He received the Norbert Wiener award in 2012 from the IEEE SMC Society. His research interests lie in distributed machine learning, extreme data mining, bioinformatics, pattern recognition and integrating AI into image processing. The exploitation of imprecision with the use of fuzzy logic in pattern recognition, AI and learning is a research theme. He has authored or co-authored over 70 publications in journals, as well as many conference papers and book chapters. Some recent publications appear in the IEEE Transactions on Pattern Analysis and Machine Intelligence, Neural Computation, Information Fusion, Journal of Machine Learning research, IEEE Transactions on Systems, Man, and Cybernetics, Pattern Recognition, the International Conference on Pattern Recognition, the Multiple Classifier Systems Workshop, and the FUZZ-IEEE conference ().
He received the IEEE SMC Society Outstanding contribution award in 2008. He received an Outstanding Research achievement award from the Univ. of South Florida in 2004. A past president of NAFIPS. The former vice president for membership of the SMC society. He was the President of the IEEE Systems, Man and Cybernetics society for 2006-7. He was the Editor-In-Chief of the IEEE Transactions on Systems, Man and Cybernetics, Part B, 2002-05. He is the Vice President for Publications of the IEEE Biometrics Council. Also, associate editor for IEEE Transactions on Fuzzy Systems, International Journal of Intelligent Data Analysis, the International Journal of Pattern Recognition and Artificial Intelligence and International Journal of Approximate Reasoning.

Prof. Radu Grosu
Vienna University of Technology

Title:Cyber-Physical and Biological Systems: The Next Challenge

Recent technological breakthroughs in data acquisition and data communication have revolutionized the way in which we understand and shape our own world. These breakthroughs however, have also lead to one of the greatest challenges of this century: Predicting the emergent behaviors of future cyber-physical systems, in which the physical world is getting merged with the cyber world. In this quest we can learn a great deal from biological cyber-physical systems, such as genetic-regulatory networks and the human heart. This talk discusses the opportunities and research challenges faced in the modeling, analysis and control of the human heart. Consisting of more than 4 billion communication nodes, interconnected through a very sophisticated communication structure, this ultimate cyber-physical system achieves with an astonishing reliability, the electric synchronization and the mechanical contraction of all of its nodes, in order to pump blood, during what is commonly known as a heart beat. However, even this cyber-physical system, engineered by billion years of evolution is fallible, and predicting its failure is a great challenge for our society.

Short Biography

Radu Grosu is a Professor and Head of the Cyber-Physical-Systems Group at the Faculty of Informatics of the Vienna University of Technology, and a Research Professor at the Computer Science Department of the State University of New York at Stony Brook. His research interests include modeling, analysis and control of cyber-physical and biological systems and his application focus includes green operating systems, mobile ad-hoc networks, automotive systems, the Mars rover, cardiac-cell networks and genetic regulatory networks. Grosu is the recipient of the National Science Foundation Career Award, the State University of New York Research Foundation Promising Inventor Award, the ACM Service Award, and a member of the International Federation of Information Processing WG 2.2. Before receiving his appointment at the Vienna University of Technology, Grosu was an Associate Professor in the Computer Science Department of the State University of New York at Stony Brook, where he co- directed the Concurrent-Systems laboratory and co-founded the Systems-Biology laboratory. Grosu earned his Dr.rer.nat. in Computer Science from the Technical University of München, and was a Research Associate in the Computer Science Department of the University of Pennsylvania.

Prof. Dr. Robert Riener

Title:Predict, Assist and Assess Human Movements

Mechatronic systems and their clinical applications play an increasingly important role in neuroscience and neurorehabilitation. Novel technical systems are being developed or are already in regular clinical use within the different therapeutic phases ranging from diagnostic neuroimaging via neurosurgical technologies to therapeutic treatments in the acute, subacute, and chronic stage of neurorehabilitation. This talk will focus on different interaction technologies that will allow future rehabilitation robotic systems i) to detect motion intention supporting the patient in an intuitive way during the therapy, ii) to assist the patient as needed during the performed movement, and iii) to quantitatively assess the motor function during and after the therapy session.
One way to engage the human subject in the movement task is to let the assisting robotic system estimate the user movement intention and support the user continuously during his or her freely chosen task rather than imposing the user with a predefined robotic action. We developed a method for predicting targets of human reaching motions using different sensing technologies such as electroencephalography, electrooculography, camera-based eye tracking, electromyography, hand position and an estimate of the user's personal preferences. Supervised machine learning was used to make predictions at different points in time (before and during the motion) with each individual sensor and with combinations of sensors.
Furthermore, during the movement therapy, audiovisual displays and rendering methods are used to present a virtual environment and let the patient perform games, virtual functional tasks or virtual activities of daily living. The human is integrated into the robotic system not only from a biomechanical view but also with regard to psycho-physiological aspects. Psycho-physiological integration involves recording and controlling the patient's physiological reactions so that the patient receives appropriate stimuli and is challenged in a moderate but engaging way without causing undue stress or harm.
Last but not least, assessment routines integrated into the robotic training can enhance the diagnosis and quantify the therapy progress, identify the impairment level and adapt the therapy to optimize the therapy outcome, eventually contributing to an optimization of the rehabilitation. Different robot-assisted assessment routines will be presented that have been implemented into different training devices allowing objective and quantitative evaluation of biomechanical functions in patients with neurological deficits, e.g. after spinal cord injury or stroke.
This talk will present several virtual reality display methods and psychophysiological recording and assessment strategies that have been implemented and tested on different rehabilitation devices such as the actuated gait orthosis Lokomat and the arm therapy device ARMin.

Short Biography

Robert Riener is full professor for Sensory-Motor Systems at the Department of Health Sciences and Technology, ETH Zurich, and professor of medicine at the University Clinic Balgrist, University of Zurich. Riener has published more than 400 peer-reviewed journal and conference articles, most of them as first or last author, 2 monographs, 19 book chapters and he has filed 20 patents. He has received more than 15 personal distinctions and awards including the Swiss Technology Award in 2006, the IEEE TNSRE Best Paper Award 2010, and the euRobotics Technology Transfer Awards 2011 and 2012.
Riener's research focuses on the investigation of the sensory-motor actions in and interactions between humans and machines. This includes the study of human sensory-motor control, the design of novel user-cooperative robotic devices and virtual reality technologies, and the investigation of human movement and psychophysiological engagement. Main application areas are in the fields of rehabilitation, medical education and sports.

Kenwood H. Hall
Vice President of Architecture and Systems Advanced Technology, Rockwell Automation

Title: Challenges in the Industrial Control Area

An overview of Rockwell Automation's 18 year history with Autonomous Distributed Systems including lessons learned, new areas of research and future plans. The increasing complexity of industrial automation systems balanced with the ability to maintain high levels of production in a high mix production environment has lead Rockwell Automation to investigate the use of Autonomous Distributed Systems. This research has lead to additional topics of investigation in very accurate software based industrial system simulation and how to trouble shoot a distributed industrial system. The years of experience in Distributed Systems is being applied to the data collection and analysis of cloud based big data research for optimization and diagnostics of large complex systems.

Short Biography

Ken is a Cleveland Native and a graduate of Cleveland State University’s Fenn College of Engineering. Ken has worked in engineering and engineering management in the Cleveland area for a number of companies including Keithley Instruments, Picker X ray, Firestone and Allen-Bradley which is now Rockwell Automation. Ken has led the development of many of Rockwell Automations large controller systems including the new LOGIX family of integrated controllers. Ken is one of the founding members of the OhioICE consortium and a former member of the board for the new third frontier Wright center for Sensor Systems Engineering. Board member for the Cleveland Engineering Society and has been issued 88 Patents with 79 pending applications. Ken’s current responsibilities are focused on the investigation and application of advanced technologies for industrial automation.