Plenary Talk/Keynote speakers
Dr. Paul Hofmann
PhD, Vice President Research at SAP Labs, Palo Alto, US
Dr. Paul Hofmann is Vice President Research at SAP Labs at Palo Alto. Before joining the team of the Chief Scientist Paul worked for the SAP Corporate Venturing Group. Paul joined SAP 2001 as Director Global Strategic Supply Chain Management Initiative EMEA. His pre-sales team designed and rolled out the SCM Value Based Selling Approach for EMEA and supported many crucial Supply Chain sales for SAP in EMEA. Prior to joining SAP, he was Senior Plant Manager at BASF’s Global Catalysts Business Unit in Ludwigshafen, Germany. After joining BASF 1989 Paul headed the development of object-oriented production planning and scheduling software for BASF's plants in the IT division of BASF. He designed a Computer Integrated Manufacturing System for BASF. He led the team that implemented the OO design in C++ and Small Talk; one of the first big object oriented software projects in German industry. Paul led the implementation of SAP R/3 for BASF Intermediary Division. Paul was Researcher and Assistant Professor at top German and US Universities, like Northwestern University in Evanston/Chicago, Illinois, USA and at Technical University in Munich, Germany. Paul was visiting scientist at Civil and Environmental Engineering Department at MIT, Cambridge, MA 2009. At Northwestern he did molecular simulations to explain molecular beam reactions. He used the Cray supercomputers extensively for this work and collaborated with Sir John Pople (Nobel Prize Laureate). At Munich Paul used Associative Memory Systems -AMS- (Neuronal Networks) to predict chemical reactions in mass spectrographs. Paul studied Chemistry and Physics at the University of Vienna, Austria. He received a Bachelor in biotechnology and a master’s degree in Chemistry from the University of Vienna. He did his Ph.D.in Physics at the Darmstadt University of Technology, Germany. At Darmstadt he wrote SW for the design of molecules (drugs) using computer graphics. He was part of the MOLCAD team that developed SW for Silicon Graphics. His thesis is on non-linear quantum dynamics and chaos theory. He is the author of numerous publications and books, including a book on SCM and environmental information systems as well as Performance Management and Productivity of Supply Chains.
Topic: The Big Five IT Megatrends
Abstract: Mobile, Big Data - exponential data growth - and social media are the disruptive IT trends of the early 21st century. Ubiquitous mobile computing is the first technology that changes the industrial world as well as the developing countries. Actually, some developing countries are leap frogging us with regard to banking. Over 10 M people or 50% of the adult population in Kenya do branch less banking. 12% of Kenyans are sending money from phone to phone. Have you ever returned money to a friend via your phone? Facebook moves about 2 B dollars of virtual game money. The information economy will be brick and mortar less. Added value will be created transforming the zettabytes we create into useful information. Mixed human-machine approaches will help us to make sense of those billions of Terabytes. We will have to automate information gathering using for example machine learning and neuronal algorithms like Siri does for understanding what we say. Even machines will talk to each other in the future Internet of Things.
Our social interactions will widely profit from being always connected and supported by those smart sense making algorithms. Social media digitize our relationships, interests and timelines to make our life easier. We will use personalized catalogues and products, as well as an incredible game like experience for collaborating at work and with friends.
The oil of the information economy is the ubiquitous compute power of the cloud. The fifth mega trend -consumerization- may be troublesome for many CIOs and enterprise software providers. The digital natives will not leave their smart phones and touch pads at home to use corporate IT approved devices and software at work. The enterprise and consumer players will clash on the mobile phone.
Dr. Paul Maglio
Paul P. Maglio is a research scientist and manager at IBM Research - Almaden in San Jose, California. He holds a bachelor's degree in computer science and engineering from MIT and an M.S. and a Ph.D. in cognitive science from the University of California at San Diego. He is also an Associate Adjunct Professor of Cognitive and Information Sciences at the University of California, Merced. Since joining IBM Research, Dr Maglio has worked on programmable Web intermediaries, attentive user interfaces, multimodal human-computer interaction, human aspects of autonomic computing, and service science. He is currently working on a system to compose loosely coupled heterogeneous models and simulations to inform health and health policy decisions. One of the founders of the field of service science, Dr Maglio serves on the editorial boards of the Journal of Service Research (Sage), Service Science (INFORMS), and is lead editor of the Handbook of Service Science (Springer). He has chaired or co-chaired many conferences related to service science, including the The Art and Science of Service (2011), the International Conference on Service-Oriented Computing (2010), Frontiers in Service (2007), the Sixteenth International Conference on Management of Technology (2007), the First ACM Symposium on Computer-Human Interaction for Managing Information Technology (2007), and the Service Science, Management, Engineering Minitrack at the Hawaii International Conference on Systems Science (2008-2012). Dr Maglio has published more than 100 scientific papers in various areas of computer science, cognitive science, and service science, and is an ACM Distinguished Scientist. At UC Merced, he has taught service science since 2007.
Topic: Modeling Complex Service Systems: Trying to Understand People, Interactions, and Emergence
Abstract: One key challenge in developing a new science of service is in finding appropriate methods for modeling service systems, arrangements of people, technology, organizations, and shared information connected by value propositions. A service system incorporates multiple interacting entities, such as firms and customers, working together to create mutual value by sharing resources -- including capabilities and competences -- and taking joint action. Service systems may be as simple two individuals interacting or as complex as hundreds of firms organized to deliver
complicated goods and services. Consider an example, human health. Health results from complex interactions among many distinct human, environment, and social systems, such as cultural, educational, political, and economic conditions, as well as policies, practices, costs, and pricing in industries as diverse as advertising, transportation, agriculture, and others. The health system is a complex service system. Interventions aimed at improving population health by affecting one system may have unanticipated consequences in another. Chronic conditions such as obesity
resist medical, behavioral, and policy interventions that touch a single system, for instance solely at the level of biology, psychology, community, built environment, economic investment, or public policy. We do not always think through the interactions among systems. It is difficult to do. It requires cross-domain thinking and systems thinking. It also requires careful collaboration among experts in different domains to explore complex interdependencies among the operation of the real-world systems each expert knows best. How can we model something so complex as
the service system around health, taking account of all relevant interactions among all relevant parts?
To try to answer this question, we have developed Splash (Smarter Planet Platform for Analysis and Simulation of Health), a novel computational framework for integrating independent data, models, and simulations to create comprehensive system models for understanding individual and population health at multiple scales and for multiple purposes. By supporting collaboration among those with data, models, and problems with a platform capable of integrating disparate data, models, and simulations, each representing parts of the overall system, Splash enables
interoperability and reuse of models and data that were created independently by different individuals or different organizations. Resulting composite models can be used to do predictive analytics, enabling “what-if” analyses that cut across disciplines. Splash makes it possible for domain experts from different areas to collaborate effectively and efficiently to exploit their combined knowledge. Models and data in Splash are loosely coupled via data exchange: every component model in a composite model expects input data and generates output data,
which may be transformed before being used by another downstream model. As a computational platform, Splash supports system-level, model-based collaboration among multiple domain scientists. It aims to raise the collaborative capabilities of experts in different domains working on related problems, each using different data, methods, and technologies. For service science, Splash represents a promising approach to modeling complex service systems through principled composition of domain-specific data, models, and simulations.