Deep Learning and Its Application to Big DataNivio Ziviani |
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AbstractDeep learning is a set of machine learning techniques that have revolutionized many areas of knowledge. Based on the traditional concept of neural networks, the techniques of deep learning allow the training of sophisticated models that are composed of multiple layers to learn representations of large data sets with multiple levels of abstraction. Neural networks trained with this technique improved the state-of-the-art in speech recognition, visual image recognition, audio processing and natural language processing. Deep learning has the potential to profoundly change the way and the speed with which companies interpret their data. This talk will present an introduction to deep learning, including an overview of the technology, tools and real-world examples in the areas of image recognition, natural language processing and discovery of patterns in corporate databases. BiographyNivio Ziviani has a Ph.D. in Computer Science from the University of Waterloo, Canada, 1982. He is CEO of Zunnit Technologies andProfessor Emeritus at the Department of Computer Science of the Federal University of Minas Gerais. He is a member of the Brazilian Academy ofSciences and the Brazilian National Order of the Scientific Merit in the class Comendador. He received the Prize of Scientific Merit of the BrazilianComputer Science Society in 2011. He is co-founder of Miner Technology Group, sold to Folha de São Paulo / UOL group in 1999, AkwanInformation Technologies, sold to Google Inc. in 2005 and Zunnit Technologies. He is author of two books in the area of algorithm design and hasco-authored over 120 papers in the areas of algorithm design and information retrieval, the latter his primary area of research. He was General Co-Chair of the 28th ACM SIGIR Conference on Research and Development in Information Retrieval and co-founder of the International Conferenceon String Processing and Information Retrieval (SPIRE).
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Claudia Bauzer Medeiros |
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BiographyClaudia Bauzer Medeiros is full professor of databases at the Institute of Computing, University of Campinas (Unicamp), Brazil. She holds adegree in Electrical Engineering (1976) and an MSc degree in Computer Science (1979) from PUC-Rio, Brazil and a PhD in Computer Sciencefrom the University of Waterloo, Canada (1985). For the past 20 years, she has been working as a visiting professor at the University Paris-Dauphine, France. She has received Brazilian and international awards for research, teaching, and also for her work in fostering the participation ofwomen in IT-related activities. |
Using the Wisdom of the Crowd in Route PlanningMario A. Nascimento |
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AbstractThere is a good number of applications capable of providing point-to-point directions on a map. They typically aim at providing the most efficient routes, i.e., faster, shorter or fuel-wise less expensive. Such routes may not be attractive for users if they are willing to trade efficiency for "interestingness'', e.g., they may prefer a route with touristic attractions instead of a faster urban route when in a city for the first time. Interestingness, as opposed to regular metrics, such as road distances is not easy to quantify. In this talk we will discuss how information collected from different sources such as travel blogs and picture repositories can be combined to enrich geographical information with "interestingness," thus allowing the finding of interesting (and reasonably efficient) routes. Our experimental results, using real datasets, are encouraging. For instance, we are able to find routes which are not much longer than the shortest one but have more points of (touristic) interest. We hope this kind of work serves as a good motivation for further research using so-called enriched geo-spatial data. BiographyMario A. Nascimento is a Full Professor at (and since 2014 serves as Chair of) the University of Alberta's Department of Computing Science (he has also served as the Associate Chair Research between 2010 and 2013). He earned his PhD in 1996, and before joining the University of Alberta in 1999, he was a researcher with the Brazilian Agency for Agricultural Research and also an adjunct faculty member with the Institute of Computing of the University of Campinas. In addition, Mario has been a visiting professor at the National University of Singapore's School of Computing (Fall/2005), Aalborg University's Department of Computer Science (Winter/2006), LMU Munich (2013-2014) and is currently a Visiting Professor at the Federal University of Ceara in Brazil. According to Google Scholar (as of Nov. 2014) his publications have been cited 2,500+ times, earning him an H-index of 26. Besides often serving as a program committee member for the main database conferences, and as (co) chair of several workshops and symposia, Mario has also served as ACM SIGMOD's Information Director (2002-2005) and ACM SIGMOD Record's Editor-In-Chief (2005-2007). He is currently a member of the VLDB Journal's Editorial Board, the SSTD Endowment's Board of Directors, and has been a senior member of the ACM since 2007. Finally, his main research interests lie in the areas of Spatio-Temporal Data Management and Data Management for Wireless Sensor Networks. (Further information can be found at http://www.cs.ualberta.ca/~mn.) |
Johannes Keizer |
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BiographyDr. Johannes Keizer has more than 20 years of experience in the in the development of complex Information Management Systems. After his studies (Master Degrees in Biochemistry and Biophysics, PhD in Biology) he started a consultancy company for scientific data management (lab data organization, registries of rare deseases, national pesticide management in Italy). In 2000 he joined the Food and Agriculture Organization of the UN to head a big restructuring operation of the "International Information System for Agricultural Science and Technology - AGRIS". From then to 2013 he lead a team of 20 professionals engaged on all levels of Agricultural Information Management (http://aims.fao.org). Since 2014 he has a special mandate for the outsourcing of technical processes in information systems to worldwide partners. Since June 2015 Johannes Keizer is member of the GODAN (http://www.godan.info) secretariat as leader for strategic partnerships.
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The future of university-driven innovation: A roadmap to success |
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Abstract In his keynote, Dr. Kliewe will highlight recent developments in how universities and business organisations work together in order to create innovation and advance the competitiveness of organisations and regions. Building upon this status quo analysis on university-business cooperation (UBC), which is derived from extensive research on UBC practice (conducted at the S2BMRC, www.science-marketing.com) as well as from experiences gained at UIIN (www.uiin.org), Dr. Kliewe will present a roadmap to future success in UBC. With the ultimate goal being to give new impetus to the audience and to challenge what the conference participants take for granted, the roadmap pictures ways how we should think about UBC, but also practical strategies and approaches to be implemented.
Biography Dr. Thorsten Kliewe is currently a Deputy Professor for “Innovation Management and Business Development” at the Science-to-Business Marketing Research Centre (S2BMRC) of Münster University of Applied Sciences (MUAS). Next to teaching, Dr. Kliewe dedicates most of his time to S2BMRC which aims to advance university-business cooperation (UBC) by conducting research and performing training in the wider UBC field. On University level he is Program Director of the new Business Field of MUAS “Transfer 3.0 - Executive Training for University Managers in Latin America”. Dr. Kliewe is also Chairman and CEO of the University Industry Innovation Network (UIIN), an Amsterdam-based spin-out of the S2BMRC supporting the practical implementation of UBC research results and running large-scale events on university-industry interaction and entrepreneurial university development.
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