This is a March meetup of our group. The upcoming event will cover three presentations.
The first talk will be given by Ruggero Altair Tacchi, Data Scientist at Quid. He will talk about the dimensionality reduction, clustering and visualization techniques used by Quid. Next you will hear about the work done on visual analysis of massive web session data by Zeqian "Jack" Shen, Architect in the Behavior and Product Experience Team at eBay.
The final presenter will be Marcus Hanwell, Technical Leader in the Scientific Computing Group at Kitware, Inc.
7:00 pm Food, beer and conversation
7:30 pm Ruggero Altair Tacchi
8:00 pm Jack Shen
8:30 pm Break
8:45 pm Marcus Hanwell
Ruggero Altair Tacchi, Extracting intelligence from Big Data
Big Data is one of the hottest topics in the world of Data Science. And yet most of the effort seems focussed on describing surface level information in the datasets, without ever understanding the deeper relationships found through exploring the data as logical, interrelated clusters. Quid is pioneering solutions in Data Science to help extract intelligence from data, using Natural Language Processing and Big Data Visualization techniques to enable the exploration and understanding of complex relationships within a dataset. In the presentation we will demonstrate some of our dimensionality reduction, clustering, and visualization techniques, using a live demo of the Quid platform. We will also show some case studies from prior analyses, including mapping tech startup innovation, news analysis, and US patent analysis.
Jack Shen, Visual Analysis of Massive Web Session Data
Tracking and recording users’ browsing behaviors on the web down to individual mouse clicks can create massive web session logs. While such web session data contain valuable information about user behaviors, the ever increasing data size has placed a big challenge to analyzing and visualizing the data. An efficient data analysis framework requires both powerful computational analysis and interactive visualization. Following the visual analytics mantra “Analyze first, show the important, zoom, filter and analyze further, details on demand”, we introduce a two-tier visual analysis system, TrailExplorer2, to discover knowledge from massive log data.
Marcus Hanwell, Big data visualization frameworks and applications at Kitware
Kitware develops permissively licensed open source frameworks and applications for scientific data applications, and related areas. Some of the frameworks developed by our High Performance Computing and Visualization group address current challenges in big data visualization and analysis in a number of application domains including geospatial visualization, social media, finance, chemistry, biological (phylogenetics), and climate. The frameworks used to develop solutions in these areas will be described, along with the applications and the nature of the underlying data. These solutions focus on shared frameworks providing data storage, indexing, retrieval, client-server delivery models, server-side serial and parallel data reduction, analysis, and diagnostics. Additionally, they provide mechanisms that enable server-side or client-side rendering based on the capabilities and configuration of the system.
Ruggero Altair Tacchi
Ruggero Altair Tacchi is a Data Scientist at Quid, Inc. He currently works on visualization techniques and quantitative modeling for large and complex data sets, and has led analyses on engagements in the high tech and financial services industries. Prior to joining Quid, Ruggero earned an MS in Physics at Sapienza University (Italy) and a PhD in Physics at University of California, Davis. During his research he focused on particle physics and group theory with an emphasis on Higgs Boson composite models.
Jack Shen is an architect in the Behavior and Product Experience Team at eBay. He builds large scale data platforms and visual analytic tools. Previously, he was a research scientist at eBay Research Labs. He obtained his PhD in information visualization at UC Davis
Marcus D. Hanwell is a Technical Leader at Kitware, Inc. He leads the Open Chemistry project, developing open-source tools for chemistry, bioinformatics, and materials science research. He completed an experimental PhD in Physics at the University of Sheffield, a Google Summer of Code developing Avogadro and Kalzium, and a postdoctoral fellowship combining experimental and computational chemistry at the University of Pittsburgh before moving to Kitware, Inc. in late 2009.
He is a member of the Blue Obelisk, blogs, @mhanwell on Twitter and is active on Google+. He is passionate about open science, open source and making sense of increasingly large scientific data to understand the world around us.