Speakers

Ralf Herbrich is Director of Machine Learning Science at Amazon Berlin, Germany. In 2011, he worked at Facebook leading the Unified Ranking and Allocation team. This team is focused on building horizontal large-scale machine learning infrastructure for learning user-action-rate predictors that enabled unified value experiences across the products. Ralf joined Microsoft Research in 2000 as a Postdoctoral researcher and Research Fellow of the Darwin College Cambridge. From 2006 – 2010, together with Thore Graepel, he was leading the Applied Games and Online Services and Advertising group which engaged in research at the intersection of machine learning and computer games and in the areas of online services, search and online advertising combining insights from machine learning, information retrieval, game theory, artificial intelligence and social network analysis. From 2009 to 2011, he was Director of Microsoft’s Future Social Experiences (FUSE) Lab UK working on the development of computational intelligence technologies on large online data collections.

Prior to joining Microsoft, Ralf worked at the Technical University Berlin as a teaching assistant where I obtained both a diploma degree in Computer Science in 1997 and a Ph.D. degree in Statistics in 2000. Ralf’s research interests include Bayesian inference and decision making, computer games, kernel methods and statistical learning theory. Ralf is one of the inventors of the Drivatars™ system in the Forza Motorsport series as well as the TrueSkill™ ranking and matchmaking system in Xbox 360 Live. He also co-invented the adPredictor click-prediction technology launched in 2009 in Bing’s online advertising system.

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Jan Pospisil is Director of Data Analytics at SIEMENS Digital Factory, Plant Analytics Services – a multinational company headquartered in Berlin and Munich and the largest industrial engineering company in Europe. Jan and his team develop highly automated anomaly and fault detectors for industrial devices based on KNIME. He is the initiator of the cooperation between KNIME and Siemens, which commenced in 2013.

Tobias Kötter is a Senior Data Scientist at KNIME in Berlin. His research interests include large scale data integration and mining, graph mining, text mining and creativity support systems. At KNIME he is the scientist to talk to on the topic of using KNIME with Big Data and integrating Hadoop and Spark. He received his PhD in Computer Science from the University of Konstanz.

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Benjamin Spiegel is the CEO of MMI Agency – a Houston-based brand activation agency that has been serving Fortune 500 clients since 1986. An industry veteran with extensive experience in advertising, media, data and technology, Spiegel has developed highly successful marketing campaigns for numerous global brands. Spiegel will be speaking at the KNIME Spring Summit this February, and he recently sat down with us to discuss his passion for modern-day data analytics.

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Rosaria Silipo is not only an expert in data mining, machine learning, reporting, and data warehousing, she has become a recognized expert on the KNIME data mining engine, about which she has published three books: KNIME Beginner’s Luck, The KNIME Cookbook, and The KNIME Booklet for SAS Users. Previously Dr. Silipo worked as a freelance data analyst for many companies throughout Europe. She has also led the SAS development group at Viseca (Zürich), implemented the speech-to-text and text-to-speech interfaces in C# at Spoken Translation (Berkeley, California), and developed a number of speech recognition engines in different languages at Nuance Communications (Menlo Park, California). Dr. Silipo gained her doctorate in biomedical engineering in 1996 from the University of Florence, Italy.

Phil Winters (KNIME)’ passionate focus on the customer over the last 30+ years has earned him international recognition as “The Father of Customer Intelligence”. He is a pioneer in defining new approaches that help organizations to raise their customer value and increase loyalty by delivering outstanding customer experience. An accomplished and dynamic public speaker, in his keynotes Phil draws on examples from his work with some 300 companies worldwide in developing customer strategies to grow their businesses, as well as in the implementation of the requisite underlying business initiatives and IT infrastructure.

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Mike Mazanetz works as a manager in Discovery Chemistry for Evotec UK Ltd, a contract research organisation. He’s been a KNIME advocate since 2004 and is the co-author of the KNIME Cookbook and he is also a certified KNIME coach. His interests lie in finding novel solutions to data informatics problems in business operations and in the biotechnology and life-sciences sectors.

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George Papadatos is a Senior Technical Officer at the ChEMBL group of the EMBL-EBI, where he currently manages SureChEMBL, a large, freely available patent chemistry resource. After obtaining his MSc and PhD in Chemoinformatics, he completed a postdoctoral research fellowship at the Computational Drug Design group at Eli Lilly. George has been a KNIME evangelist for the last 7 years, juggling multiple roles as a KNIME tutor, academic, power user and community node developer.

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Matthias Negri received his MSc (2004) in Medicinal Chemistry from the University of Bologna and his PhD degree (2010) in Pharmaceutical Sciences in co-tutele from the University of Saarland and the University of Bologna. He specialized in computational drug design and molecular modelling and was active in several drug design projects in the oncology, infective and hormone-dependent disease fields. Due to the interdisciplinary character of those projects, he worked with several groups at both institutions and with industrial partners, gaining important experience in sharing data and cooperating with and managing external collaborations. After two postdoctoral experiences (University of Saarland and Helmholtz Institute for Pharmaceutical Research Saarland) he moved to Boehringer Ingelheim in 2014, where he joined the Scientific Information Center in Biberach. He is currently responsible for chemistry related searches, text- and data-mining as well as the integration of novel tools in the R&D landscape.

Abstract:
Chemistry appears in manifold ways in documents and databases: as names, codes, images, attachments, tables. It is further linked in all its flavors to a wealth of data, spread over a multitude of unstructured and structured sources, which usually needs to be harmonized and combined in order to leverage their real value, e.g. for the pharmaceutical industry. Several tools in the fields of cheminformatics, OCR, OSR and text-mining are required to fulfil these tasks and KNIME offers an elegant way to do it. In this talk tips and tricks are presented, highlighting the possibilities as well as the difficulties encountered.

Presentation tags:
pipelining, data/text-mining, chemistry recognition and extraction, OCR correction

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Dominique Genoud studied at the Federal institute of Technolgy in Lausanne Switzerland (EPFL), he then worked in different places in Switzerland as Software and hardware engineer. From 1995 to 1999 he was researcher at IDIAP Switzerland in voice recognition and biometrics systems where he obtained his PhD thesis in Information systems. In 1999 he made a postdoctoral at ICSI UC Berkeley.

From 1999 to 2002 he worked as senior research engineer at Nuance Communications in Menlo Park California. Dominique Genoud has several international publications (articles, books and patents) in the fields of biometrics and data analysis systems, etc. From 2002 to 2006 he worked as manager at Polyright, a Swiss company active in software products for RFID solutions.

Since 2006 he is CEO of Loutze-informatique.com, a software company that he founded. He joined the software engineering unit of the Institute of Information Systems at HES-SO Valais-Wallis in 2010. Dominique current research activities are focused on information systems for energy (smart-grids/micro-grids) and multisource intelligent data analysis applied in domain such as the social media, text mining, biotechnology and energy.

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Philipp Katz received his PhD at the TU Dresden, Germany. In his thesis he researched geographical information extraction approaches and methods for retrieving news-relevant user-generated content. He is using KNIME since 2009 and began developing the Palladian nodes with colleagues in 2011. In 2015, Philipp co-founded the startup LINEUPR, a web platform for organizers to create stunning mobile event guides. Based on daily requirements at LINEUPR, he built the Selenium Nodes for "remote controlling" web browsers, which are publicly available now.

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Brian Muchmore is currently a Bioinformatician at the Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO) specializing in the data analysis of high dimensional cytometry datasets. He runs Spain's only mass cytometer and is also heavily involved in the PRECISEADS project, whose purpose is to gather a wide range of data from thousands of patients suffering from auto-immune disorders that share common pathophysiological mechanisms in order to molecularly reclassify the diseases and develop targeted therapies.

Abstract:
Although KNIME is inherently portable, some of the capabilities that make KNIME such a powerful tool, such as access to multiple programming languages or the ability to call external tools, may require installing a number dependencies, which can often be messy and impractical. Meanwhile, Docker has quickly become the de facto choice for application containerization without the overhead associated with virtual machines. Thus, "dockerizing" KNIME is a natural solution to package KNIME together with any needed dependencies without having to install these dependencies system-wide. This talk will give an introduction to the high-level concepts involved in dockerizing KNIME while also giving a brief tutorial of how you can create your own custom KNIME image that is low on system-resources, easily shareable and self-contained.

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Rutao Luo has over 15 years of modeling and control engineering experience in industry and academia. He currently works as a data analytics engineer in the Engineering Analysis team at Comcast. His major task is to build state‐of‐art models for Comcast to forecast network traffic, optimize network quality and improve the customer experience. Before joining Comcast in September of 2014, James worked for GE as a design engineer for control systems.
Rutao holds a M.Sc. degree in Electrical Engineering and a M.Sc. degree in Applied Mathematics from University of Delaware. James performed research at University of Delaware from 2007‐2012 and published more than 10 papers in the area of modeling and control engineering. He actively serves for several journals and peer‐review conferences as a reviewer.

Abstract:
Comcast is a United States based, multinational mass media company and is among the largest broadcasting and cable companies in the world by revenue. Comcast provides a variety of products in QAM‐based video, IP‐based video, high‐speed internet, home security solutions and other services across its vast network. All services are characterized by interdependence, mutual interaction, information feedback and circular causality. The complexity and interdependency has led to the need for state‐of‐the‐art models to help our executive leaders make better strategic decisions. The Engineering Analysis team proposed a holistic solution, called the “Universal Model,” which is implemented in KNIME (and R) and provides a holistic model for all of our products/services. This bestin‐class solution helps us meet the following challenges:

1. To guarantee that the most updated, and verified assumptions will be applied to all subsystems.
2. To model not only each subsystem’s dynamics, but also to model the interdependence among them.
3. To enable our internal customers, including the executive leaders, to run the models by themselves through KNIME webportal.
4. To handle the large and complex data from difference sources.
5. To control the model version efficiently by using the KNIME Server.

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Albert van Duijn is a Senior business Analyst and manages a of a group of business analysts within Elsevier's Publishing Department. He has a master in Physical Geography and Public Information Management. He used to be an ICT consultant for 7 years at one of the leading Dutch consultancy firms before joining Elsevier almost three years ago.
Within Elsevier he and his group are working on delivery of regular reports and dashboards, providing on demand custom analytics and are involved in many projects related to improving the inner workings of Elsevier's information services and internal processes.

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Alexander Klenner-Bajaja has a PhD in bioinformatics from the Goethe University of Frankfurt, Germany. After his post-doctoral studies at the Fraunhofer Institute SCAI, where he was responsible for the implementation of a scientific data and text mining platform, he joined the European Patent Office (EPO) in The Hague in early 2014 to support the directorate Search & Knowledge within the EPOs Information Management Department. He is part of a team that is in charge of testing and providing innovative automated search solutions for the patent examiners of the EPO.

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After studying mathematics and business in Hanover and London, Philipp Seifert started in the Direct Marketing Department at Otto Office. He then worked for TUI, where he set up a new base for direct marketing by establishing a marketing data mart. In his position at Weight Watchers, he built a web-based sales controlling tool, which is still used worldwide, and a location management system based on multistage data mining processes. At Asstel Versicherungen, he implemented a campaign management tool, which was especially designed for a data warehouse. Since 2013, he has been leading the Marketing Department of the menswear retailer Walbusch and is responsible for the transition from print to online.

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Björn Arnold is a Senior Software Architect at Bosch Software Innovations, the Bosch Group's software and systems house and "Internet of Things" (IoT) solution provider. There he was responsible for integrating the KNIME Analytics Platform into the Bosch IoT platform in order to leverage the business value of Big Data by means of state-of-the-art data analytics techniques. He received his MSc in Medical Informatics from the University of Heidelberg and started his career as a Software Engineer at a consultancy firm before joining Bayer as a Software Architect to rebuild the corporate information and collaboration systems landscape. As part of these activities he was working on delivering regular reports and dashboards as well as providing on-demand custom analytics, which raised his interest in statistics and data mining in general. Currently he is engaged with aligning the use of Big Data with privacy and security constraints.

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Dean Abbott is Co-Founder and Chief Data Scientist of SmarterHQ, and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades of experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs. He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

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