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Speaker: Prof. Donald W. Gotterbarn, Ph.D.
Host: Prof. Dr. Lorenz Hilty
Computing systems are adaptable; systems designed for one purpose can be used in an entirely different way. The system designed to precisely control a video game is used to control robotic surgery; but that same system is also used to control destructive military devices. The development of the avionics software for surveillance drones was a boon to search and rescue missions in remote areas but that same software has been adapted for use in the theatre of war. Effective encryption of medical information is important but that encryption can contribute to significant harm if it limits access to patient medical information during an emergency situation. Computing professional’s decisions are frequently complex and the outcomes of those decisions are serious. Because systems are now converging with all elements of society, e.g., the impact that the Internet-of-Things has on people’s lives, the decisions made in the development, deployment, and management of computing systems is very different from our normal everyday decisions. Our “technical” decisions are now deeply integrated into society; they are really ‘socio-technical’ decisions. Many so-called “software failures” are due to incomplete risk analysis; a risk analysis that only addresses technical and management decisions. Socio-technical decisions require special attention. Socio-technical decisions unfortunately are more complex than technical decisions. There are support tools to help us mitigate the complexity of these decisions and more effectively reduce the risks of software development. Using real cases from software development this talk will identify some of the traps we fall into while making computing/ICT decisions and will provide two decision support processes to help mitigate the impact of these broader risks. One methodology uses a quick “back of the envelope” engineering analysis technique to clarify concepts and isolate relevant issues and tradeoffs. This technique helps to identify the critical sub-elements of the situation so we can focus our response. The other methodology goes into the complex relationships providing an ordered list of alternative responses to the situation. The ordered list of potential responses facilitates a stepped response to difficult situations. Using these tools will help reduce the broader risks of computing.
Prof. Dr. Don Gotterbarn, as an academic and software systems developer, has been active over several decades promoting responsible computing from his work on the development of computing codes of ethics, writings, and serving as an expert witness on conformance to professional standards by computer practitioners. He led the development of IEEE-CS/ACM Software Engineering Code of Ethics. He has taught at the National Security Agency, the University of Southern California and is professor emeritus of East Tennessee State University. He has held positions as visiting scientist at Carnegies Mellon University and research fellow at Australian National University. Some of his software projects include several database systems for the U.S. Navy and for the Saudi Arabian Navy, and an interactive crime-reporting database, and certification of software for vote counting machines and missile defense systems. He is currently a visiting professor at the UK Centre for Computing and Professional Responsibility, chair of the ACM Committee on Professional Ethics, an ACM Distinguished National Lecturer, on the Board of Directors of the Institute for the Certification of Computing Professionals, Director of the Software Engineering Ethics Research Institute, member of the BCS ICT Ethics Specialist Group and working on two EU grants: Responsible Innovation and Criminal Intelligence Analysis.s.
Speaker: Prof. Robert J. Kauffmann Ph.D.
Host: Prof. Daning Hu, Ph.D.
Most senior leaders in business know that innovation and implementation capabilities go hand-in-hand to support corporate success and profitability. Nowhere is this more true than in the financial services industry where, even before the words ‘big data’ and ‘data analytics’ became the vogue, steady efforts were underway since the 1980s to work with structured and unstructured data to produce knowledge to run the business profitably. This presentation will share a new perspective on data analytics for business, consumer and social insights that emphasizes an updated philosophy of science for digital data, research questions, new methods, and illustrative findings that relate to the acquisition of financial intelligence. The ‘living analytics’ perspective on financial intelligence is based on: (1) access to societal scale data – ‘digital traces’ of consumer behavior; (2) to enable the study of banking services and people in networked relationships; (3) in progressively real-time environments; (4) with rapid and iterative experimental methods; (5) that enable the discovery of causal relationships. This view of how to create ‘financial intelligence’ is especially applicable to retail banking, where products and services, branches and ATMs, self-service and full-service relationships with customers, and transaction-making and incentives for loyalty need to be managed. Financial institutions are highly interdisciplinary organizations, where finance, operations, technology and marketing meet in every product and service area. And yet, the information resources to study key business problems are not always available due to the lack of reference data standards, critical dependencies across different business domains, and limited human capital with deep data analytics skills.m.
Prof. Dr. Robert J. Kauffman is Professor of IS, Associate Dean (Research), and Deputy Director (Living Analytics Research Centre) at Singapore Management University’s School of Information Systems. He serves as faculty leader for SMU’s Area of Excellence on Analytics for Business, Consumer and Social Insights. He visited the Tuck School of Business at Dartmouth College, was W.P. Carey Chair in Information Systems at Arizona State University, and also was Professor and Chair (Information and Decision Sciences), and Director (MIS Research Center at the University of Minnesota. He was on the faculty of the Stern School, NYU. His Ph.D. is from Carnegie Mellon, and his master’s degree is from Cornell. Rob has written 200+ articles in journals, books and conferences, edited several books, and won awards for his research, and for field contributions in IS and Engineering Management. He serves as the Editor of Electronic Commerce Research and Applications, and co-edits an issue of the Journal of Management Information Systems every year. He chairs the annual ‘Workshop on Analytics for Business, Consumer and Social Insights,’ and on ‘Society, Information, Technology, and Economics’ at HICSS. Some of his publications from the past few years that relate to financial intelligence, data analytics, pricing and business value include: ‘Price Points and Price Rigidity’ in Review of Economics and Statistics (2011); ‘Online and Offline Demand and Price Elasticities: Evidence from the Air Travel Industry’ in Information Systems Research (2012); ‘Firm Strategy and the Internet in American Commercial Banking,’ Journal of Management Information Systems (2013);’ ‘Understanding the Paradigm Shift in Computational Social Science in the Presence of “Big Data.”’ in Decision Support Systems (2014); and ‘Consumer Informedness and Firm Information Strategy’ in Information Systems Research (2014).
Speaker: Rodrigo Agerri, Ph.D.
Host: Prof. Dr. Martin Volk
Polarity lexicons are the most important resources for sentiment analysis. In this talk we will defend two claims: First, that polarity lexicons should be extrinsically evaluated on a Polarity or Sentiment or Opinion task. Second, that such an extrinsic evaluation should ideally be part of the polarity lexicon creation. Traditionally, polarity lexicons, whether manually or automatically created, have been intrinsically evaluated against a gold-standard. To substantiate these two claims, we present the Q-WordNet by Personalized Pageranking Vector (QWN-PPV) method to automatically create polarity lexicons using a WordNet only. QWN-PPV is a simple, robust and unsupervised dictionary-based method. We show that QWN-PPV outperforms other automatically generated lexicons for the four extrinsic evaluations presented here. It also shows competitive and robust results with respect to manually annotated ones. Results suggest that no single lexicon is best for every task and dataset, and that the intrinsic evaluation of polarity lexicons is not a good indicator of good performance on a Sentiment Analysis task. Our method is applicable to create QWN-PPVs for any language, and we demonstrate it for English and Spanish. The QWN-PPV method allows to create quality polarity lexicons whenever no domain-specific annotated corpora are available for a given language.
Dr. Rodrigo Agerri is currently Research Fellow at the IXA NLP Group of the University of the Basque Country in San Sebastian. He obtained a PhD in Computer Science at City University London and has since been working on Natural Language Processing at the University of Birmingham (UK), at the MAVIR consortium at the Universidad Politécnica de Madrid. Furthermore, he had a stint in the industry (Vicomtech-IK4) where he led several industrial projects. He has participated in many leading research projects funded by national and European agencies. Furthermore, he was technical coordinator of the European project SUMAT and got awarded a Torres Quevedo Research Fellowship.
Visible Light Communication (VLC) with Light Emitting Diodes (LEDs) as transmitters and receivers enables low bitrate wireless adhoc networking, which is an interesting new approach for toys and related applications in the entertainment industry. We present recent research achievements at Disney Research, address open challenges, and demonstrate the performance of our software-based VLC physical layer and a VLC medium access control layer that retain the simplicity of the LED-to-LED approach. We also provide an overview of research activities at Disney Research, Zurich.
Dr.-Ing. Stefan Mangold received his degrees in electrical engineering/telecommunications from RWTH Aachen University in Germany. He is now senior research scientist at Disney Research in Zurich, Switzerland. As an Imagineer of The Walt Disney Company, Stefan guides a small team that contributes to Disney Research’s work on wireless communication and mobile computing. His research covers many aspects of wireless communication. Other research interests include smart toys and play patterns, and magical experience designs for the entertainment industry.
Speaker: Prof. Salil Kanhere Ph.D.
Host: Prof. Dr. Burkhard Stiller
With recent advances in embedded systems technologies, it is now possible to engineer highly compact sensor platforms that are particularly well-suited for tracking the individual movement patterns of wildlife. In this talk, I will address two specific research challenges that arise from the stringent resource constraints of these sensing devices, in the context of an application for continental-scale long-term tracking of flying foxes. We first consider the problem of offloading data from the mobile sensors. Our application constraints favour a highly asymmetric solution, with heavily duty-cycled sensor nodes communicating with a network of powered base stations. Individual nodes move freely in the environment, resulting in low-quality radio links and hot-spot arrival patterns with the available data exceeding the radio link capacity. We propose a novel scheduling algorithm, k-Fair Scheduling Optimisation Model (k-FSOM), that maximises the amount of collected data under the constraints of radio link quality and energy, while ensuring a fair access to the radio channel. We show the problem is NP-complete and propose a heuristic to approximate the optimal scheduling solution in polynomial time. We use empirical link quality data to evaluate the k-FSOM heuristic in a realistic setting and compare its performance to other heuristics. We show that k-FSOM heuristic achieves high data reception rates, under different fairness and node lifetime constraints. The memory and energy constraints also underscore the need for lightweight online trajectory compression albeit without seriously affecting the accuracy of the mobility data. We present a novel online Polygon Based Approximation (PBA) algorithm that uses regular polygons, the size of which is determined by the allowed spatial error, as the smallest spatial unit for approximating the raw GPS samples. PBA only stores the first GPS sample as a reference. Each subsequent point is approximated to the centre of the polygon containing the point. Furthermore, a coding scheme is proposed that encodes the relative position (distance and direction) of each polygon with respect to the preceding polygon in the trajectory. The resulting trajectory is thus a series of bit codes, that have pair-wise dependencies that originate at the reference point. It is thus possible to easily reconstruct an approximation of the original trajectory by decoding the chain of codes starting with the first reference point. Encoding a single GPS sample is an O(1) operation, with an overall complexity of O(n). Moreover, PBA only requires the storage of two raw GPS samples in memory at any given time. The low complexity and small memory footprint of PBA make it particularly attractive for low-power sensor nodes. PBA is evaluated using GPS traces that capture the actual mobility of flying foxes in the wild. Our results demonstrate that PBA can achieve up to nine-fold memory savings as compared to one of the most widely used trajectory compression scheme.
Prof. Dr. Salil Kanhere received his M.S. and Ph.D. degrees, both in Electrical Engineering from Drexel University, Philadelphia in 2001 and 2003, respectively. He is currently an Associate Professor in the School of Computer Science and Engineering at the University of New South Wales in Sydney, Australia. His current research interests include embedded sensor networks, participatory sensing, mobile networking, privacy and security. He has published over 125 peer-reviewed articles and delivered over 15 tutorials and keynote talks on these research topics. Salil was the program co-chair for IEEE LCN 2014 and IEEE MoWNet 2014 and has also served on the organising committee of a number of IEEE and ACM international conferences (e.g, ACM SenSys, ACM CoNext, IEEE WoWMoM, IEEE LCN, ACM MSWiM,, IEEE SenseApp, ACM IWCMC, ISSNIP). He currently serves as the Area Editor for Pervasive and Mobile Computing, International Journal of Ad Hoc and Ubiquitous Computing and the ICST Journal on Ubiquitous Environments. Salil is a Senior Member of both the IEEE and the ACM and also serves on the TCCC Executive Committee. He is a recipient of the Alexander von Humboldt Research Fellowship for 2014 and is currently visiting Technische Universität Darmstadt in Germany.
Speaker: Kobi Gal Ph.D.
Host: Prof. Sven Seuken, Ph.D.
The range and complexity of human decision-making raises significant challenges to the design of successful computer agents for interacting with people. I'll describe work that addresses these challenges by combining insights from behavioral economics and psychology. I will present work showcasing these challenges and some proposed solutions. One study will present techniques for automated advice provision in settings involving computers and their human users such as route selection systems and office assistants. Another study will present algorithms for plan recognition and visualisation in domains where agents’ actions exhibit exploration and mistakes. I will discuss the significance of these studies to human-computer decision-making and computer science and conclude with some interesting open problems.
Dr. Ya'akov (Kobi) Gal is a faculty member of the Department of Information Systems Engineering at the Ben-Gurion University of the Negev, and an associate at the School of Engineering and Applied Sciences at Harvard University. His work investigates representations and algorithms for making decisions in heterogeneous groups comprising both people and computational agents. He has published over 40 papers in highly refereed venues on topics ranging from artificial intelligence to the learning and cognitive sciences. He is a recipient of the Wolf foundation's 2013 Krill prize for young Israeli scientists, a Marie Curie International fellowship, and a three-time recipient of Harvard University’s outstanding teacher award.
Speaker: Prof. Michael Xiaoquan Zhang Ph.D.
Host: Prof. Daning Hu, Ph.D.
We examine whether and in what way a social-media platform, Wikipedia, affects the corporate information environment. We argue that collaborative information processing via Wikipedia reduces information asymmetry between insiders and outsiders and among outsiders, especially for retail investors, who are at a greater information disadvantage. We use updates to public companies’ Wikipedia entries to proxy for collaborative information processing via Wikipedia and the profitability and intensity of insider trades to proxy for information asymmetry. We find that Wikipedia updates are negatively associated with the profitability of insider trades after controlling for alternative information sources, and the association is stronger for firms owned to a greater extent by retail investors. We also find that Wikipedia updates are negatively associated with insider trades based on superior knowledge of future performance but not with insider trades against extant misvaluation.
Prof. Dr. Michael Zhang is an Associate Professor of Information Systems at the Hong Kong University of Science and Technology, and an affiliated faculty at MIT Center for Digital Business. He holds a PhD in Management from MIT Sloan School of Management, an MSc in Management, a BE in Computer Science and a BA in English from Tsinghua University. Before joining the academia, he worked as an analyst for an investment bank, and as an international marketing manager for a high-tech company. He holds a US patent, and started a social network company. Professor Zhang’s research interests are on issues related to creation, dissemination and processing of information in business and management contexts. His works study entrepreneurship, innovation, pricing, online word-of-mouth, online advertising, incentives of creation in open source and open content projects, and use of information in financial markets. His research has appeared in American Economic Review, Management Science,Journal of Marketing, MIS Quarterly, Journal of MIS, Decision Support Systems, and Journal of Interactive Marketing. He has also been actively involved in professional services, including serving as an Associate Editor for Information Systems Research, a Guest Associate Editor for MIS Quarterly, and a member of the editorial boards of Production and Operations Management andElectronic Commerce Research and Applications.
Speaker: Prof. Dr. Antonio Krüger
Host: Prof. Elaine Huang, Ph.D.
In this talk I will discuss the relevance the concepts of "attention" and "interruption" when designing ubiquitous computing interfaces. In fact, these two concepts have been at the core of Mark Weiser's Vision of Ubiquitous and Calm Computing. With more and more possibilities to measure human attention and interruptions they gain more relevance in actual design of User Interfaces in Ubiquitous Computing Environments. I will present various examples of our work in this area, including studies on how users can handle interruption on mobiles and how to assess attention in ubiquitous computing environments.
Prof. Dr. Antonio Krüger received a diploma in computer science and economics at Saarland University in 1995. Afterwards he joined the Cognitive Science Graduate Programme of the same University and finished it with a doctoral degree in 1999. His doctoral thesis was on the "Automated Abstraction of 3D-Graphics".He was early involved in several Artificial Intelligence projects at the German Research Centre for AI (DFKI GmbH), and later from 1999-2003 at the Intelligent Systems Lab of Saarland University as a Senior Researcher. In 2000 he co-founded the University spin-off Eyeled GmbH, a company focusing on mobile computing solutions. Within the company he is responsible for the technology transfer of university research. From 2004 to 2009 he was an associate professor for Geoinformatics and Computer Science at Münster University, Germany. From 2005 to 2009 he was the managing director of the institute for Geoinformatics at the same University. Since 2009 Antonio Krüger is a full professor for Computer Science at Saarland University. At the same time he has been appointed as the Scientific Director of the Innovative Retail Laboratory at the German Research Center for Artificial Intelligence (DFKI) in Saarbrücken, Germany.
