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Keynote Lectures

Speed, Data and Ecosystems: Excelling in a Software-Driven World
Jan Bosch, Chalmers University of Technology, Sweden

The Role of Technology and Communication in Enabling Behavioural Change for Cities of the Future
Siobhán Clarke, Trinity College Dublin, Ireland

Data-Driven Genomic Computing: Making Sense of the Signals from the Genome
Stefano Ceri, Politecnico di Milano, Italy

Advances and Future Challenges in Machine Learning and Knowledge Extraction
Andreas Holzinger, Medical University Graz, Austria

 

Speed, Data and Ecosystems: Excelling in a Software-Driven World

Jan Bosch
Chalmers University of Technology
Sweden
 

Brief Bio
Jan Bosch is professor of software engineering at Chalmers University Technology in Gothenburg, Sweden. He is director of the Software Center (www.software-center.se), a strategic partner-funded collaboration between 10 large European companies (including Ericsson, Volvo Cars, Volvo Trucks, Saab Defense, Jeppesen (Boeing)  and  Siemens) and five universities focused on software engineering excellence. Earlier, he worked as Vice President Engineering Process at Intuit Inc where he also led Intuit's Open Innovation efforts and headed the central mobile technologies team. Before Intuit, he was head of the Software and Application Technologies Laboratory at Nokia Research Center, Finland. Prior to joining Nokia, he headed the software engineering research group at the University of Groningen, The Netherlands. He received a MSc degree from the University of Twente, The Netherlands, and a PhD degree from Lund University, Sweden. His research activities include evidence-based development, software architecture, innovation experiment systems, compositional software engineering, software ecosystems, software product families and software variability management. He is the author of several books including "Design and Use of Software Architectures: Adopting and Evolving a Product Line Approach" published by Pearson Education (Addison-Wesley & ACM Press) and ÒSpeed, Data and Ecosystems: Excelling in a Software-Driven WorldÓ published by Taylor and Francis, editor of several books and volumes and author of a significant number of research articles. He is editor for Journal of Systems and Software as well as Science of Computer Programming, chaired several conferences as general and program chair, served on numerous program committees and organized countless workshops.

In the startup space, Jan is chairman of the board of Fidesmo in Stockholm,  Auqtus and, until recently, Remente, in Gothenburg, Sweden. He serves on the advisory board of Assia Inc. in Redwood City, CA, Peltarion AB in Stockholm and Burt AB in Gothenburg, Sweden. Jan also runs a boutique consulting firm, Boschonian AB, that offers its clients support around the implications of digitalization including the management of R&D and innovation. For more information see his website: www.janbosch.com.


Abstract
We are living in the most exciting time in the history of mankind. The last century has seen unprecedented improvements in the quality of the human condition and technology is at the heart of this progress. Now we are experiencing an even bigger leap as we move towards a new level of digitisation and automation. Ranging from self-driving cars to factories without workers to societal infrastructure, every sensor and actuator is becoming connected and new applications that enable new opportunities are appearing daily. The fuel of this emerging connected, software-driven reality is software and the key challenge is to continuously deliver value to customers. The future of software engineering in this context is centered around three main developments: Speed, Data and Ecosystems. The focus on speed is concerned with the constantly increasing rate of deploying new software in the field. This continuous integration and deployment is no longer only the purview of internet companies but is also increasingly deployed in embedded systems. Second, data is concerned with the vast amounts of information collected from systems deployed in the field and the behavior of the users of these systems. The software-intensive systems industry needs to significantly improve its ability to exploit the value present in that data. Finally, ecosystems are concerned with the transition in many companies from doing everything in-house to strategic use of innovation partners and commodity providing partners. The keynote addresses these three main developments, provides numerous examples from the Nordic and international industry and predicts the next steps that industry and academia need to engage in to remain competitive.



 

 

The Role of Technology and Communication in Enabling Behavioural Change for Cities of the Future

Siobhán Clarke
Trinity College Dublin
Ireland
 

Brief Bio
Prof. Siobhán Clarke is a Professor in the School of Computer Science and Statistics at Trinity College Dublin. She joined Trinity in 2000, having previously worked for over ten years as a software engineer for IBM. Her current research focus is on software engineering models for the provision of smart and dynamic software services to urban stakeholders, addressing challenges in the engineering of dynamic software in ad hoc, mobile environments. She has published over 150 papers and is a Science Foundation Ireland Principal Investigator, exploring an Internet of Things middleware for adaptable, urban-scale software services.

Prof. Clarke is the founding Director of Future Cities, the Trinity Centre for Smart and Sustainable Cities, with contributors from a range of disciplines, including Computer Science, Statistics, Engineering, Social Science, Geography, Law, Business and the Health Sciences. She leads the School’s Distributed Systems Group, and was elected Fellow of Trinity College Dublin in 2006.


Abstract
It is expected that some 5 billion people representing ~60% of the world’s population will live in urban areas by 2030. The growth of cities is an evolving phenomenon that is often unplanned, leading to serious social problems such as traffic congestion, noise pollution, energy wastage, and high levels of carbon dioxide emissions. Given growing urban populations, it is clear we need to change our behaviour to better manage the sharing of increasingly constrained urban resources, such as the road network, energy, water, and so on. This is also an exciting time for ICT, with great advances in sensor technology and wireless communication giving some optimism that in this age, we may be capable of coping with the challenges ahead. This talk explores how automated communication and collaboration, using real-time decision-making, can play a part in assisting citizens in making better use of the resources available to them. The goal is not to take over citizens' lives, but to remove the onus on citizens to be constantly aware of potential opportunities for optimising resource sharing. In particular, the talk uses examples from autonomous vehicles and energy demand-side management.



 

 

Data-Driven Genomic Computing: Making Sense of the Signals from the Genome

Stefano Ceri
Politecnico di Milano
Italy
 

Brief Bio
Stefano Ceri is professor of Database Systems at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) of Politecnico di Milano; he was visiting professor at the Computer Science Department of Stanford University (1983-1990). His research work covers four decades (1976-2016) and has been generally concerned with extending database technologies in order to incorporate new features: distribution, object-orientation, rules, streaming data; with the advent of the Web, his research has been targeted towards the engineering of Web-based applications and to search systems. More recently he turned to crowd searching, to social media analytics, and to genomic computing.

He is the recipient of two ERC Advanced Grants: "Search Computing (SeCo)" (2008-2013), focused upon the rank-aware integration of search engines in order to support multi-domain queries and “Data-Centered Genomic Comouting (GeCo)” (2016-2021), focused upon new abstractions for querying and integrating genomic datasets.  He is the recipient of the ACM-SIGMOD "Edward T. Codd Innovation Award" (New York, June 26, 2013), an ACM Fellow and a member of Academia Europaea.


Abstract
Genomic computing is a new science focused on understanding the functioning of the genome, as a premise to fundamental discoveries in biology and medicine. Next Generation Sequencing (NGS) allows the production of the entire human genome sequence at a cost of about 1000 US $; many algorithms exist for the extraction of genome features, or "signals", including peaks (enriched regions), mutations, or gene expression (intensity of transcription activity). The missing gap is a system supporting data integration and exploration, giving a “biological meaning” to all the available information; such a system can be used, e.g., for better understanding cancer or how environment influences cancer development.

The GeCo Project (Data-Driven Genomic Computing, ERC Advanced Grant, 2016-2021) has the objective or revisiting genomic computing through the lens of basic data management, through models, languages, and instruments, focusing on genomic data integration. Starting from an abstract model, we developed a system that can be used to query processed data produced by several large Genomic Consortia, including Encode and TCGA; the system employs internally the Spark engine, and prototypes can already be accessed from Cineca or from PoliMi servers. During the five-years of the ERC project, the system will be enriched with data analysis tools and environments and will be made increasingly efficient. Among the objectives of the project, the creation of an “open source” repository of public data, available to biological and clinical research through queries, web services and search interfaces.



 

 

Advances and Future Challenges in Machine Learning and Knowledge Extraction

Andreas Holzinger
Medical University Graz
Austria
 

Brief Bio
Andreas Holzinger is head of the Research Unit Human–Computer Interaction, Institute of Medical Informatics, Statistics and Documentation, Medical University Graz, Associate Professor of Applied Informatics at the Faculty of Computer Science, Institute of Informationsystems and Computer Media and Lecturer at the Faculty of Electrical and Information Engineering, Institute of Genomics and Bioinformatics at Graz University of Technology. He serves as consultant for the Canadian, Swiss, French and Dutch Government, for the German Excellence Initiative and as national expert in the European Commission (Lisbon Delegate 2000). Andreas, born 1963, started as an apprentice in Information Technology in 1978; while working as an industrial engineer, he resumed a parallel second-chance education, finished his PhD in Cognitive Science in 1997 and completed his second doctorate (Habilitation) in Computer Science in 2003. Since 1999 participation in leading positions in 30+ R&D multi-national projects, budget 3+ MEUR;300+ publications, 3600+ citations; Andreas was Visiting Professor in Berlin, Innsbruck, Vienna, London, and Aachen. He is passionate on bringing together Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD), with the goal of supporting human intelligence with machine intelligence – to discover new, previously unknown insights into complex biomedical data. Homepage:http://www.hci4all.at; Current main lecture:http://genome.tugraz.at/medical_informatics.shtml


Abstract
Today the problem are heterogeneous, probabilistic, high-dimensional and complex data sets. The challenge is to learn from such data to extract and discover knowledge, and to help to make decisions under uncertainty. In automatic machine learning (aML) great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from "big data" with many training sets. However, sometimes we are confronted with a small amount and complex data sets, where aML suffers of insufficient training samples. The application of such aML approaches in complex application domains such as health informatics seems elusive in the near future, and a good example are Gaussian processes, where aML (e.g. standard kernel machines) struggle on function extrapolation problems which are trivial for human learners. In such situations, interactive Machine Learning (iML) can be beneficial where a human-in-the-loop helps in solving computationally hard problems, e.g., subspace clustering, protein folding, or k-anonymization of health data, where the knowledge and experience of human experts can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem reduces greatly in complexity through the input and the assistance of a human agent involved in the learning phase. ML is a fast growing and very practical field with many business applications and much open research challenges, particularly in multi-task learning, transfer learning and hybrid multi-agent systems with humans-in-the-loop. Consequently, successful ML needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization and tackling complex challenges needs both disciplinary excellence and a cross-disciplinary skill-set and international joint work without any boundaries.



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