You are all invited to attend the following seminar on graph visualization. The seminar will review the state of the art techniques for visualizing graphs, and also present GraphInsight, a powerful and scalable visualization tool.
GraphInsight is *free* to use, and should be very useful for several groups dealing with graph data. Attendees will have the opportunity to play with the system.
Title: Interactive graph exploration with GraphInsight
Speakers: Carlo Nicolini and Michele Dallachiesa
Location: Garda room, Povo-1
Date/time: Jun,12 – 2.30pm
Applications that make decisions based on graph data are increasingly prevalent, including computer network security, social network analysis, bioinformatics, cloud computing, and knowledge extraction.
Graph visualization allows researchers to see, explore, and understand large amounts of data at once, possibly suggesting new research directions and algorithm improvements. In spite of their importance, there is a lack of efficient and scalable graph visualization tools.
In this seminar, we will review the most widely used graph drawing and labeling techniques, focusing on their scalability issues and the most successful optimization strategies. We will also present GraphInsight, a C/C++ flexible and scalable application for 2D and 3D interactive graph exploration that we have developed.
Finally, we will show a demo of our system, and let attendees interact with it. GraphInsight is free to use for research purposes.
Michele Dallachiesa is a PhD candidate at the University of Trento, Italy. He received his BSc and MSc in Computer Science from the University of Trento. During his MSc, he was also a Research Fellow at the machine Learning and Intelligent OptimizatioN (LION) Group and then Co-Founder of Reactive Search Srl. In his PhD, he collaborated with Microsoft Research Cambridge to visualize the internal dynamics of modern SAT solvers. He visited as intern student the IBM T.J. Watson Research Center, and the Qatar Computing Research Institute. He is currently a member of the Database and Information anagement Group (dbTrento) at the University of Trento. In his spare time, he works on GraphInsight, an application for interactive graph data exploration.
His research interests are in processing and analyzing streaming data in real time, including frequent items discovery, sketching of time series, data cleaning, probabilistic models for uncertainty management, and pattern matching of uncertain time series.
Carlo Nicolini is scientific programmer at Istituto Italiano di
Tecnologia (IIT), Italy. He received his BSc and MSc in Physics from the University of Trento. After his MSc he was research fellow at the Machine Learning and Intelligent Optimization (LION) group at DISI, UniTN. His research work spanned from the field of numerical optimization to graph drawing and machine-learning techniques for human activity recognition.
He’s currently working in a research project for Cognitive Neuroscience at IIT, where he developed an immersive virtual reality stereoscopic system for psychophysical experiments in human space perception.