July 24th to August 4th, 2017

The School will take place between June 24th and August 4th at IME-USP. During that time there will be one basic and ten advanced courses, besides the keynotes, student presentations, and panels with top researchers. Instead of traditional poster sessions, participating students that already have some ongoing research will be invited to pffer short presentations on their work in the style of Lightning Talks, which is more and more used in recent conferences. For each presentation, of about 7 minutes and with few slides, there will be another 7 minutes for discussions with the input from specialists.

Unless otherwise stated, all courses are 6 hours long. The panels will include at least 3 researchers, according to their days in Brazil.

The main courses and talks are:

Title Level Duration (hs) Presenter
Recent Trends and Research Challenges in Smart City Research Advanced Course 3 Fabio Kon
IME-USP
Basic Techniques in Machine Learning Basic Course 3 Marcelo Finger
IME-USP
Participative Sensing Networks on Urban Computing Advanced Course 6 Antonio Loureiro
UFMG
Internet of Things: from Theory to Practice Talk 1 Antonio Loureiro
UFMG
Sustainability Aspects for Smart Cities Talk 1 Cláudia Medeiros
Unicamp
Analysis and Visualization of Urban Data Advanced Course 6 Claudio Silva
NYU
Simulating Cities: The Spacetime Framework Advanced Course 6 Cristina Lopes
UCI
From Research to Innovation in a Smart Cities Ecosystem Advanced Course 3 Gemma Guilera
Future Cities Catapult
Remote Attestation of Low-End Embedded Devices Talk 1 Gene Tsudik
UCI
Security and Privacy in Content-Centric Networking Advanced Course 4 Gene Tsudik
UCI
From Urban Data Flows and Civic Hacking to a Smart City Software Ecosystem Advanced Course 6 Kiev Gama
UFPE
Your Wireless Guide to the Internet of Things & Smart Cities Advanced Course 6 Mischa Dohler
King's College London
Big Mobile Data for Urban Computing Advanced Course 3 Nuria Oliver
Vodafone
Platforms for Smart Cities Application Development Advanced Course 4 Thais Batista
UFRN
Data Mining for Social and Cyber Physical Systems Advanced Course 6 Wagner Meira
UFMG

We already have a tentative schedule (subject to changes):

Time Jul 24th (Monday) Jul 25th (Tuesday) Jul 26th (Wednesday) Jul 27th (Thursday) Jul 28th (Friday) Jul 31st (Monday) Aug 1st (Tuesday) Aug 2nd (Wednesday) Aug 3rd (Thursday) Aug 4th (Friday)
08:00

08:30
Registration  
08:30

9:00
Welcome session Lightining talks Silva Oliver (remote presentation) Lightining Talks Research Oportunites Finger Meira Lightining Talks Lightining Talks
09:00

10:00
Welcome session Kon Silva Oliver (remote presentation) Loureiro
(Talk)
Research Oportunites Finger Meira Lightining Talks Lightining Talks
10:00

10:20
break break break break break break break break break break
10:20

11:20
Dohler Guilera Lopes Tsudik
(Course)
Tsudik
(Talk)
Tsudik
(Course)
Meira Batista Scipopulis Calil
11:20

12:20
Dohler Guilera Lopes Tsudik
(Course)
Lopes Tsudik
(Course)
Meira Batista Medeiros Free Time
12:20

13:45
Lunch Lunch Lunch Lunch Lunch Lunch Lunch Lunch Lunch Lunch
13:45

14:15
Official Opening Dohler Silva Lopes Silva Loureiro
(Course)
Kiev Kiev Batista Posters
14:15

14:45
FAPESP*
14:45

15:45
Guilera Dohler Silva Lopes Silva Loureiro
(Course)
Kiev Kiev Batista Posters
15:45

16:20
break break break break break break break break break break
16:20

18:00
Dohler Panel
Startups
Panel
Privacy
Panel
Large Scale Simulation
Loureiro
(Course)
Loureiro
(Course)
Meira Panel
Software Engineering
Lightining Talks Wrap-up
Social events   Boteco   Recreational run Jam Session   Churrasco   Pizza  
* An overview of the kinds of funding, international cooperation agreements, and opportunities for young researchers offered by FAPESP

Abstracts:

Marcelo Finger

Basic Techniques in Machine Learning [3h course]

We present traditional supervised techniques in machine learning and describe their application using real data. The following techniques will be covered: decision trees, Probabilistic graphical models (Markov models, bayesian networks), neural networks (perceptron and others).

For each method, we plan to discuss the principles behind the model, discuss the basic algorithms for runtime and training, and present some real world applicatons.

Antônio Alfredo Loureiro

Participative Sensing Networks on Urban Computing [6h course]

Participative Sensing Networks (PSNs) are based on user collaboration to gather data on several aspects of our lives, from physical to social. With the growth in smartphone usage and new wireless communication technologies such as 4G phone networks and, soon, 5G, user participation is expected to increase. In this context, PSNs will have a significant role in urban computing, a recent research area aiming at the collection and analysis of urban data from various sources. The goal of this course is to discuss how participative sensing will be fundamental in urban computing, addressing the state of the art, challenges, and opportunities.

Internet of Things: from theory to practise [1h talk]

The proliferation of objects capable of monitoring, processing, and communicating has grown continuously in recent years. In this context rises the Internet of Things (IoT) vision, in which objects can connect over the Internet and establish communication channels for users, devices (D2D), machines (M2M) and implement new applications. Several theoretical and practical issues come up regarding IoT development, such as how to connect these devices to the Internet and how to address these objects. These questions are paired with other challenges, such as the limited processing power, bandwidth, and energy available in these devices. Therefore, new communications and routing paradigms may be explored. Difficulties related to IP addressing and how to adapt it need to be handled. Opportunities for new applications in a network of smart objects come up and bring along new challenges. The goal of this minicourse is to describe the current state of Internet of Things from theory to practise and bring up challenges and research questions. By means of a critical approach, a general overview of the area is presented, showing partial and/or complete solutions proposed in the relevant literature, and also highlighting the main challenges and opportunities the area offers.

Cláudia Medeiros

Sustainability aspects for smart cities [1h talk]

Sustainability is a multidisciplinary research domain that means different things to distinct researchers, depending on their field of interest - and which can range from the (A)rts to (Z)oology. In a broad sense, it can be seen as efforts towards saving our planet, from a micro point of view (a home) to a macro perspective (the Earth and the biosphere). Research in smart cities necessarily involves such aspects, e.g., analyzing how new building technologies can affect the environment, or how traffic solutions will not only improve people's lives, but also decrease carbon emission. The talk will discuss, via some examples, the many dimensions of research on smart cities with respect to sustainability studies. These examples will also (but not only) emphasize open research problems in computer science, that have appeared in response to the need of ensuring that cities be both smart and sustainable.

Claudio Silva

Analysis and Visualization of Urban Data [6h course]

Today, 50% of the world’s population lives in cities and the number will grow to 70% by 2050. Cities are the loci of economic activity and the source of innovative solutions to 21st century challenges. At the same time, cities are also the cause of looming sustainability problems in transportation, resource consumption, housing affordability, and inadequate or aging infrastructure. The large volumes of urban data, along with vastly increased computing power and improved user interfaces enable analysts to better understand cities. Encouraging success stories show better operations, more informed planning, improved policies, and a better quality of life for citizens. However, analyzing urban data often requires a staggering amount of work, from identifying relevant data sets, cleaning and integrating them, to performing exploratory analyses over complex, spatio-temporal data. Our long-term goal is to enable interdisciplinary teams to crack the code of cities by freely exploring the vast amounts of data cities generate. This talk describes challenges which have led us to fruitful research on data management, data analysis, and visualization techniques. I will present methods and systems we have developed to increase the level of interactivity, scalability, and usability for spatio-temporal analyses.

Cristina Lopes

Simulating Cities: The Spacetime Framework [6h course]

With the advent of alternative energy and the Internet of Things, there is suddenly a plethora of new technologies that will require major restructuring of cities. Some examples are autonomous vehicles, solar energy, unmanned aerial vehicles, and smart homes and buildings. In order to establish sound public policies, all these new technologies can greatly benefit from urban simulations, to measure their impact on the city and its people before the policies are defined.

Yet, despite all the reasons why complex simulations are desirable for decision and policy making, and despite advances in computing power, large distributed simulations of urban areas are still rarely used, with most of their adoption in military applications. The reality is that developing distributed simulations is much harder than developing non-distributed ones, and requires a much higher level of software engineering expertise, which usually modeling and simulation experts don’t have.

My students and I have been exploring how some of the ideas underlying Aspect-Oriented Programming can help overcome the design challenges faced by distributed simulations, as applied to urban simulations. There are many similarities between the concept of aspect (as given by AOP) and the general concept of ”aspect of a city” that urban planning researchers routinely use. This tutorial looks at urban simulations from a socio-technical systems design perspective, and puts forward the idea that non-traditional decompositions are not just beneficial for these applications, but are likely the only way to develop realistic urban simulations. I will present a data-oriented framework that we are developing called the Spacetime framework, specifically designed for enabling large, collaborative, and decentralized simulations, and will show how it is being used in practice.

Gemma Guilera

From Research to Innovation in a Smart Cities Ecosystem [3h course]

Numerous fascinating smart cities technologies and services have been developed and proposed over past years. Only a few however made it into the real city ecosystem. This tutorial will explore the traits of technologies and services which are highly likely to succeed in the competitive city market. We will elaborate on innovation dynamics, and how to ensure that a proper demand-side approach allows best returns on research outcomes. The insights shared stem from the Future Cities Catapult, the world’s only innovation hub aiming to accelerate research & innovation in a smart city context.

Gene Tsudik

Remote Attestation of Low-End Embedded Devices [Keynote]

Today, so-called "smart" (and interconnected) devices are propagating into many spheres of life, including: critical infrastructure, industrial control, transportation, as well as home and office automation. These devices are "smart" since they incorporate specialized computing capabilities. However, they are not general-purpose computers and thus can not take advantage of sophisticated security features, such as anti-malware tools. At the same time, as Stuxnet incident illustrated, smart devices represent attractive attack targets, and their compromise poses real threats both to security and privacy. Recent attacks on thermostats, cars and other gadgets demonstrate viability and potential danger of inadequate security. Preventing remote malware attacks on smart devices is a formidable challenge that requires resources and features which incur certain (sometimes prohibitive) costs. For stand-alone devices, the only realistic defense is attack detection and subsequent disinfection. This prompts the need for so-called "remote attestation", a security service that involves a trusted entity (verifier) checking software integrity of a remote and possibly infected device (prover).

The first part of this talk will consider this simple setting and describe recent work in designing remote attestation techniques that aim to minimize requirements needed to support this service, especially for low-end devices. The second part will broaden the scope to systems of interconnected devices, such as drone swarms, building automation systems and automotive components. Remote attestation of grouped and networked devices is challenging because of scale and increased chances of device capture and physical attacks. To this end, this talk will overview some recent results in scalable remote attestation of networked devices and methods for mitigating physical attacks.

Security and Privacy in Content-Centric Networking [4h course]

In the last 6-7 years, several major research efforts have sprung up aiming to design a set of potential next-generation Internet architectures. Content-Centric Networking (CCN) is one such effort. CCN avoids IP's host-based, point-to-point paradigm in order to better accommodate current and emerging patterns of communication. CCN treats data as a first class object, explicitly naming it, instead of its location. Unlike the current Internet which secures the "pipe" that carries data between hosts, CCN secures data – a design choice that decouples trust in data from trust in hosts, enabling scalable and secure communication mechanisms, such as caching of data in routers to optimize bandwidth. CCN poses many interesting security and privacy challenges, including: trust management, accounting, DDoS resilience as well as content protection and privacy. This talk will start with a brief overview of CCN and a summary of various security and privacy issues. The focus will be on network-layer security and privacy challenges and means to address them.

Kiev Gama

From urban data flows and civic hacking to a smart city software ecosystem [6h course]

Smart Cities is a market buzzword that can be seen as a new technological paradigm for the twenty-first century, aimed at organizing major urban centers through the convergence of different information and communication technologies (ICT). Although there is no consensus on a formal definition of a Smart City, it is common view that it became a niche market growing worldwide. By the year 2020, 100 billion dollars will be invested globally only in telecommunications infrastructure in this new sector of urban computing. This new trend on computing involves acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces. Coming from a different direction, another trend within the scope of Smart Cities involves the creation of technological solutions made by the citizens themselves, encouraged the use of open data and transparency to the creation of civic innovation.

This workshop will provide a horizontal perspective on both trends, covering topics such as challenges in the handling of the data captured in urban environments; strategies for fostering citizens participation through civic hacking; and the usage of open data and open platforms for the construction of a smart city as a software ecosystem. Such an ecosystem involves different actors, a shared market for software and services, underpinned by a common technological platform or market and operating through the exchange of information.

Mischa Dohler

Your Wireless Guide to the Internet of Things & Smart Cities [6h course]

The Internet of Things (IoT) is an integral part of a smart city as it allows data to be acquired in real-time from a variety of sensors across the city, and thereby allows to optimize and improve city services. The IoT, however, has not materialized until today as predicted which is mainly due to poor connectivity choices in the past. This tutorial will expose the mistakes made in the past, and contrast these with the emerging technologies which are likely enable the smart cities market. We will learn about emerging low-power wide are networking (LPWAN) technologies, and how they fit into the smart cities ecosystem. You will learn some fascinating insights from one of the pioneers in the Internet of Things and Smart Cities, who will share experience and vision on both emerging fields.

Nuria Oliver

Big Mobile Data for Urban Computing [6h course]

The almost universal adoption of mobile phones is generating unprecedented digital traces of large-scale human behavior which enable us to characterize, understand, model and predict the dynamics of cities, regions and countries. In my talk I will present some of the work that we have carried over the past 8 years at Telefonica Research in the context of urban human behavior modeling from mobile data with a variety of purposes, including predicting crime, recommending mobile apps, or shedding light on how different parts of the city are being used.

In addition to describing the projects, I will highlight some opportunities but also challenges (research and beyond) that we would need to address to leverage this type of data.

Thais Batista

Platforms for Smart Cities Application Development [4h course]

There are several proposed smart cities application development platforms, each one with its characteristics and addressing a specific set of services. However, one cannot fail to note that there is no standard yet and, because the research area is still new, most existing proposals are not yet mature. With that in mind, this course intends to clarify the requirements for smart cities development platforms, briefly present some currently used platforms, analyse whether the presented platforms answer the discussed requirements, and present in more detail the platform that answers the largest number of them.

Wagner Meira Jr.

Data Mining for Social and Cyber Physical Systems [6h course]

A massively connected society, like those that characterize smart cities, already produces a gigantic amount of data that is also incomplete, noisy, heterogeneous, and asynchronous from social sources (e.g., social networks and the web) and cyberphysical (e.g., physical and veicular sensors). In many contexts, these data may be mined and produce high value information in bulk. In this course we will discuss data mining paradigms to deal with problems such as alarm triggering, sub-trajectory clustering, and behavior inference from incomplete data, as well as strategies that guarantee computational viability while maintaining the quality of the results. We will showcase the various problems and solutions with relevant applications such as epidemic vigilance and urban mobility. The course also includes some practical activities modeling problems and developing solutions to realistic scenarios.