The amount of digitally recorded information in today’s world is growing exponentially. Massive volumes of user-generated information from smart phones and social media are fueling this Big Data revolution. As data flows throughout every sector of our global economy, questions emerge from commercial, government, and non-profit organizations interested in the vast possibilities of this information. What is Big Data? How does it create value? How can we as digital consumers and producers personally benefit?
While Big Data has the potential to transform how we live and work, others see it as an intrusion of their privacy. Data protection concerns aside, the mere task of analyzing and visualizing large, complex, often unstructured data will pose great challenges to future data scientists.
On Monday, March 7, from 6:30 to 8:30 p.m., please join our speakers at the German Center for Research and Innovation (GCRI) in New York as they discuss the impact and challenges of using distributed computational power and data. Questions addressed will include whether new methods for machine learning are needed which respect local constraints on energy, computational power, and varying communication links as well as whether access to Big Data helps in the automated discovery of hypotheses and their validations.
Prof. Dr. Katharina Morik, Head of the Collaborative Research Center SFB876 and Professor of Computer Science at TU Dortmund University in Germany, will discuss resource-aware data science. She will present the smartphone as a resource-restricted system, drawing upon studies of thousands of app usages. She will also describe logistics hardware made by SFB876 and explain resource-restricted machine learning. Starting with natural language processing, Prof. Dr. Morik’s interests transitioned to machine learning ranging from inductive logic programming to statistical learning and then to the analysis of very large data collections, high-dimensional data, and resource awareness. Since 2011, she has been leading the Collaborative Research Center SFB876 on resource-aware data analysis, an interdisciplinary center comprising 14 projects, 20 professors, and about 50 Ph.D. students or postdoctoral fellows.
Prof. Dr. Morik will be joined by Prof. Dr. Kristian Kersting, Associate Professor of Computer Science at TU Dortmund University. Prof. Dr. Kersting will present real-time traffic as a resource-restricted system and explain the role of Markov random fields (MRF). He will focus on how Big Data analytics enables better logistics and transport. Prof. Dr. Kersting moved to the Fraunhofer IAIS and the University of Bonn using a Fraunhofer ATTRACT Fellowship in 2008 after completing a postdoctoral fellowship at MIT in Cambridge, MA. Before moving to the TU Dortmund University in 2013, he was appointed Assistant Professor for Spatiotemporal Patterns in Agriculture at the University of Bonn in 2012. His main research interests are data mining, machine learning, and statistical relational artificial intelligence, with applications to medicine, plant phenotyping, traffic, and collective attention.
Prof. Dr. Dr. Wolfgang Rhode, Professor of Astroparticle Physics at TU Dortmund University, will also speak. He will elaborate on using data science for science, presenting the telescope as a resource-restricted system. He will explore how real-time Big Data analytics are revolutionizing science to become data-volume driven. Since 2003, Prof. Dr. Dr. Rhode has been working as a professor in Dortmund. His current experiments IceCube, MAGIC, FACT, and CTA focus on the observation of high-energy neutrinos and gamma-rays from extraterrestrial sources. A central topic of his research agenda is the development of new methods to enable Big Data analysis in physics.
Dr. Claudia Perlich, Chief Scientist at Dstillery, will draw upon her experience in real-time advertising, highlighting ad pushing as a resource-restricted service. She will speak about real-time services on apps and how Big Data analytics can help create new business plans. Dr. Perlich leads the machine learning efforts that power Dstillery’s digital intelligence for marketers and media companies. With more than 50 published scientific articles, she is a widely acclaimed expert on Big Data and machine learning applications, and an active speaker at data science and marketing conferences around the world. Dr. Perlich is the past winner of the Advertising Research Foundation’s (ARF) Grand Innovation Award and has been selected for Crain’s New York 40 Under 40 list, Wired Magazine’s Smart List, and Fast Company’s 100 Most Creative People. Prior to joining Dstillery in 2010, Claudia worked at IBM’s Watson Research Center.
Dr. Tina Eliassi-Rad, Associate Professor of Computer Science at Northeastern University in Boston, MA, will moderate the discussion. Dr. Eliassi-Rad is also on the faculty of the Network Science Institute at Northeastern. Her research is rooted in data mining and machine learning and spans theory, algorithms, and applications of massive data from networked representations of physical and social phenomena. Her work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, and cyber situational awareness.
This discussion will take place on Monday, March 7, from 6:30 to 8:30 p.m. at the German Center for Research and Innovation (871 United Nations Plaza, First Avenue, btw. 48th & 49th Streets).
