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do you know that by two thousand and fifty seventy
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percent of the global population believe in c. d.'s
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for such overpopulated c. d.'s to be sustainable it is critical
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that city officials make informed decisions about the city planning
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however cities are complex environments that are shaped by multiple factors
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any location in the city may have all kinds of information associated with it
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from the axial currencies to noise complaints and tax
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activity and this information can be pretty detailed
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for example taxi records can have several attributes such as they pick
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up and drop off time fair deep and number of passengers
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all this complex information is usually publicly available in
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the form of numerous urban data set
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to penalise these data sets and the correlation some on them
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city planners there are two these were utterly takes systems
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using the systems instead of looking at numbers they look at callers
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on the mob as you can see on my slide
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while they can compare multiple data sets using just the single visualisation
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to generate these visualisation as usual analytic systems rely
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on what we call spatial application realise that
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partition the data over to different regions and then compute summarise information for each region
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this data partitioning is achieved by performing point in polygon test
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to determine the data points contained within each polygon or save region
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based tests are computationally heavy and considering the hundreds of millions or
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even billions of points that the data set might contain
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these poses a big challenge for these what analytic systems making interactive response is hard to achieve
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in fact no existing technique can answer spatial application queries in real time
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our research battles this challenge by evaluating spatial navigation queries using
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renderings which are operations highly optimised for graphics hardware
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just to give you some intuition our approach drones the data points on agreed it current fuss and keeps
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track of intersections between the points and the canvas but
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maintaining compassion aggregates in the canvas greed cells
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it then throws the polygonal regions on the same canvas and calculates the aggregate result
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from the bachelor art gets off the grid cells that intersect with each polygon
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this approach leverage is that massive parallelism provided by more than graphics hardware
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and thereby evaluates spatial education queries on the fly in real time
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that way we enable city planners to interactively navigate urban

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Conference program

Welcome address
Andreas Mortensen, Vice President for Research, EPFL
7 June 2018 · 9:49 a.m.
Introduction
Jim Larus, Dean of IC School, EPFL
7 June 2018 · 10 a.m.
The Young Software Engineer’s Guide to Using Formal Methods
K. Rustan M. Leino, Amazon
7 June 2018 · 10:16 a.m.
Safely Disrupting Computer Networks with Software
Katerina Argyraki, EPFL
7 June 2018 · 11:25 a.m.
Short IC Research Presentation 2: Gamified Rehabilitation with Tangible Robots
Arzu Guneysu Ozgur, EPFL (CHILI)
7 June 2018 · 12:15 p.m.
Short IC Research Presentation 3: kickoff.ai
Lucas Maystre, Victor Kristof, EPFL (LCA)
7 June 2018 · 12:19 p.m.
Short IC Research Presentation 5: CleanM
Stella Giannakopoulo, EPFL (DIAS)
7 June 2018 · 12:25 p.m.
Short IC Research Presentation 6: Understanding Cities through Data
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 12:27 p.m.
Short IC Research Presentation 7: Datagrowth and application trends
Matthias Olma, EPFL (DIAS)
7 June 2018 · 12:31 p.m.
Short IC Research Presentation 8: Point Cloud, a new source of knowledge
Mirjana Pavlovic, EPFL (DIAS)
7 June 2018 · 12:34 p.m.
Short IC Research Presentation 9: To Click or not to Click?
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 12:37 p.m.
Short IC Research Presentation 10: RaaSS Reliability as a Software Service
Maaz Mohiuddlin, LCA2, IC-EPFL
7 June 2018 · 12:40 p.m.
Short IC Research Presentation 11: Adversarial Machine Learning in Byzantium
El Mahdi El Mhamdi, EPFL (LPD)
7 June 2018 · 12:43 p.m.
20s pitch 1: Cost and Energy Efficient Data Management
Utku Sirin, (DIAS)
7 June 2018 · 2:20 p.m.
20s pitch 2: Gamification of Rehabilitation
Arzu Guneysu Ozgur, EPFL (CHILI)
7 June 2018 · 2:21 p.m.
20s pitch 4: Neural Network Guided Expression Transformation
Romain Edelmann, EPFL (LARA)
7 June 2018 · 2:21 p.m.
20s pitch 5: Unified, High Performance Data Cleaning
Stella Giannakopoulo, EPFL (DIAS)
7 June 2018 · 2:21 p.m.
20s pitch 6: Interactive Exploration of Urban Data with GPUs
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 2:22 p.m.
20s pitch 7: Interactive Data Exploration
Matthias Olma, EPFL (DIAS)
7 June 2018 · 2:22 p.m.
20s pitch 8: Efficient Point Cloud Processing
Mirjana Pavlovic, EPFL (DIAS)
7 June 2018 · 2:23 p.m.
20s pitch 9: To Click or not to Click?
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 2:24 p.m.
20s pitch 10: RaaSS Reliability as a Software Service
Maaz Mohiuddlin, LCA2, IC-EPFL
7 June 2018 · 2:24 p.m.
20s pitch 11: Adversarial Machine Learning in Byzantium
El Mahdi El Mhamdi, EPFL (LPD)
7 June 2018 · 2:24 p.m.
Machine Learning: Alchemy for the Modern Computer Scientist
Erik Meijer, Facebook
7 June 2018 · 2:29 p.m.