Professor Anuradha Annaswamy

Massachusetts Institute of Technology (USA)

Keynote: “Socio-technical modeling and control for urban mobility”

Dr. Anuradha Annaswamy is Founder and Director of the Active-Adaptive Control Laboratory in the Department of Mechanical Engineering at MIT. Her research interests span adaptive control theory and its applications to aerospace, automotive, and propulsion systems as well as cyber-physical systems such as Smart Grids, Smart Cities, and Smart Infrastructures. Her current research team of 15 students and post-docs is supported at present by the US Air-Force Research Laboratory, US Department of Energy, Boeing, Ford-MIT Alliance, and NSF. She has received best paper awards (Axelby; CSM), Distinguished Member and Distinguished Lecturer awards from IEEE CSS, and a PYI award from NSF. She is a Fellow of IEEE and IFAC. She will serve as the CSS President in 2020.





Professor Iven Mareels

Director of IBM Research (Australia)

Keynote: “Renewable Energy Based Grid Futures – A View from the Last Mile”

Prof. Iven Mareels is the director of IBM Research – Australia. He is an eminent leader in the Australian research community and joined IBM Research in February 2018 following a 20-year career at the University of Melbourne, where he spent the last 10 years as the Dean of the Melbourne School of Engineering. Prof. Mareels leads the IBM Research team in Melbourne and works with the IBM network of research labs to accelerate the work IBM Research leads in the areas of health informatics, artificial intelligence, blockchain and quantum computing.
Prof. Mareels is a researcher at heart and loves to explore new directions, opportunities and solve problems. He is passionate about exploring complex issues in depth and making a difference in people’s lives by transforming ideas into innovative technology.
Over the years, Prof. Mareels has played a leading role in the development of hardware and software that manages water distribution in a highly effective way. This technology has a proven ability to improve water management significantly, all but eliminating the majority of water losses in large scale water distribution networks. This technology has been commercialized by Rubicon Water Pty Ltd. For this work, he received a Clunies Ross Award from the Academy of Technological Sciences and Engineering in 2008.
More recently, at IBM Research, Prof. Mareels has been focusing on two key AI application areas. First in the context of energy management. In particular, his team focuses on demand management, as a new paradigm in grid management. The team is exploiting the thermal inertia (thermal energy services consume more than 40% of electricity supply) to drastically increase overall energy efficiency whilst reducing the cost for consumers and creating more opportunities to integrate renewables. Secondly, he is focusing on AI for the Eye. An ambitious scientific program that employs readily available image technologies to observe through the eye, brain and cardiovascular health. Combining a time series of images with regular lifestyle observations, his team is driving towards personalized preventive medicine at scale. This approach will significantly increase the productivity of health practitioners and reduce the societal and economic burden associated with reactive medicine.
Prof Mareels received the Masters of Electromechanical Engineering in 1982 summa cum laude from the University of Gent, Belgium and the Ph.D. from the Australian National University in 1987 with a thesis on dynamics of adaptive or learning systems. He has published widely, with more than 500 refereed publications, and he has supervised more than 50 Ph.D. students. He holds 39 internationally granted patents that focus on the management of large scale, open channel, water distribution networks.
Prof Mareels is a Fellow of The Academy of Technological Sciences and Engineering (Australia); The Institute of Electrical and Electronics Engineers (USA), the International Federation of Automatic Control and Engineers Australia. He is a Foreign Member of the Royal Flemish Academy of Belgium for Science and the Arts. He is internationally registered as a professional engineer: FIEAust CPEng EngExec NER APEC Engineer IntPE(Aus).



Professor Junmin Wang

University of Texas at Austin (USA)

Keynote: “Learning-based and Personalizable Ground Vehicle Controls”

Junmin Wang is the Accenture Endowed Professor in Mechanical Engineering at the University of Texas at Austin.  In 2008, he started his academic career at Ohio State University, where he founded the Vehicle Systems and Control Laboratory, was early promoted to Associate Professor in September 2013 and then very early promoted to Full Professor in June 2016.  He also gained five years of full-time industrial research experience at Southwest Research Institute (San Antonio Texas) from 2003 to 2008. Prof. Wang has a wide range of research interests covering control, modeling, estimation, optimization, and diagnosis of dynamical systems, especially for automotive, smart and sustainable mobility, human-machine, and cyber-physical system applications.  Dr. Wang is the author or co-author of more than 310 peer-reviewed publications including 150 journal articles and 13 U.S. patents. Prof. Wang is a recipient of numerous international and national honors and awards including 2019 IEEE Best Vehicular Electronics Paper Award, 2018 IEEE Andrew P. Sage Best Transactions Paper Award, 2017 IEEE Transactions on Fuzzy Systems Outstanding Paper Award, 2012 NSF-CAREER Award, 2011 SAE International Vincent Bendix Automotive Electronics Engineering Award, 2009 ONR-YIP Award. He is an IEEE Vehicular Technology Society Distinguished Lecturer and Speaker, SAE Fellow, and ASME Fellow. Dr. Wang received the B.E. in Automotive Engineering and his first M.S. in Power Machinery and Engineering from the Tsinghua University, Beijing, China in 1997 and 2000, respectively, his second and third M.S. degrees in Electrical Engineering and Mechanical Engineering from the University of Minnesota, Twin Cities in 2003, and the Ph.D. degree in Mechanical Engineering from the University of Texas at Austin in 2007.



Professor Fabio Bonsignorio

Heron Robots (Italy)

Keynote: “Towards Industry 4.0 Precision Agriculture and beyond”

Prof. Fabio Bonsignorio is CEO and Founder of Heron Robots (advanced robotic solutions),  see www.heronrobots.com. He has been Visiting Professor at the Biorobotics Institute of the Scuola Superiore Sant’Anna in Pisa in the period 2014-2019. He has been a professor in the Department of System Engineering and Automation of the University Carlos III of Madrid until 2014. In 2009 he was awarded the Banco de Santander Chair of Excellence in Robotics at the same university.  He has been working in the R&D departments of several major Italian and American companies, mainly in the applications of intelligent systems and technology transfer with coordination/management responsibilities for more than 20 years. He is a Founding Director of euRobotics aisbl, the private part of SPARC, the Eu Robotics PPP. He is a past elected member of the Research Board of Directors of SPARC. He coordinated and has been the main teacher of the ShanghAI Lectures (www.shanghailectures.org) since the 2013 edition. The ShanghAI Lectures are an advanced network MOOC teaching initiated several years ago by Rolf Pfeifer. He is currently coordinating the 2019 edition. His preferred research topics are in advanced robotics: Machine Learning,  Deep Learning, Block-Chain, control, modeling, software architectures, AI, cognition, robot swarms, intelligent agents, epistemological issues in robotics, performance evaluation and foundational issues like ’morphological computation’ . He has pioneered and introduced the topic of Reproducible Research and Benchmarking in Robotics and AI, where is one of the leading experts, if not the leading one. He is the Reproducibility Editor of the IEEE Robotics and Automation Magazine. He is author or co-author of more than 150 publications in the areas of robotics, cognition and manufacturing systems in the last few years since he became an almost full-time researcher. His first paper on robot control dates back to 1985 (probabilistic control!). He is a senior member of IEEE/RAS. He coordinated the EURON Special Interest Group on Good Experimental Methodology and Benchmarking in Robotics, is Co-Chair of the IEEE RAS TC-Pebras and has been a board member of EURON III. He is a member of the GeorgeGiralt Ph.D. Award jury. He has been a reviewer for many conferences and journals. He is a Project reviewer for Ecsel, FET and Echord++ in H2020 and has been for FP7. He was a member of the joint Europ-Euron-other experts restricted team preparing the Robotics Public-Private Partnership in Horizon 2020, the successor program at EU level of FP7. He was in the advisory board of Robo-Spect H2020 IA and of Excellabust H2020 Twinning project. He is the coordinator of the euRobotics Topic Group on Experiment Replication, Benchmarking, Challenges, and Competitions and is co-chair of the IEEE TC- Pebras. He has participated in the design and launched the new euCognition society. He has been publication chair in the 2014 IEEE RAS Humanoids 2014 conference and Entrepreneurship Co-Chair of IROS 2018. He has been general co-chair of the IEEE RAS 2015 Summer School on Replicable and Measurable Robotics Research and will be for the upcoming 2020 Edition. He has been the corresponding and more active editor of the Special Issue on Replicable and Measurable Robotics Research on IEEE Robotics and Automation Magazine, appeared in September 2015. This special issue is the very first example of a higher impact archival robotics journal issue with replicable and measurable results pioneering Reproducible Research in RAS and to a certain extent IEEE at large. He has been in the Program Committee of the European Robotics Forum since 2017. He is in the Management Committee of the COST Action CA17137 – A network for Gravitational Waves, Geophysics and Machine Learning, who has been one of the main proposers. He co-organized the 1st Conference on Machine Learning for Gravitational Waves, Geophysics, Robotics, Control Systems. Through HeronRobots he is developing new (patent pending) technologies for soft lightweight manipulators and networks of mobile robots for low frequency sensing in Gravitational Waves detection and Geophysics applications.



Professor Daniel Silveira

GMV Innovating Solutions (Spain)

Keynote: “ESROCOS: a robotic operating system for space and terrestrial applications”

Daniel Silveira is a highly experienced systems engineer and an expert on OBSW RTOS for IMA/TSP architecture. He graduated in Computer Science from Instituto Superior Técnico – Technical University of Lisbon (Portugal). He gained his experience as a system engineer in mobile operators (TMN and DSTS), BAE Systems and GMV. During the course of the last 12 years he has participated in space and robotics research projects and missions for a wide range of applications; IMA/TSP, robotics and multi-core in Space, Model-based Space OBSW, V&V of Space Software for Galileo and other, Space Safety-Critical Software Research (RAMS), Satellite Control Systems and Mobile Satellite Networks.





Jorge Monteiro

Space Way, C-MAST (Portugal)

Keynote: “Space sector in Portugal and the urge for Space Education”

Portuguese and born in Coimbra, Jorge has been fascinated since his childhood by the space sciences and the world of entrepreneurship. He is currently director of SpaceWay and a researcher at C-MAST (Center for Mechanical and Aerospace Science and Technologies), where he manages nanosatellite projects. He is also the National Point of Contact in Portugal for space from Space Generation Advisory Council. Jorge has a master’s degree in Aeronautical Engineering from the University of Beira Interior and an executive course on business and management from Porto Business School. He also participated in several international space education programs such as ESA Alpbach Summer School (2016), ESA Concurrent Engineering Workshop (2017) and Space Station Design Workshop (2017) and won the award for innovation by AIRBUS in the ActInSpace contest (2018).      




UBIsym titles

Urban mobility in Transportation is witnessing a transformation due to the emergence of new concepts in Mobility on Demand, where new modes of transportation other than private individual cars and public mass transit are being investigated. With a projection of a total number of 2 billion vehicles on roads by the year 2050, such innovations in transportation are urgently needed. One such paradigm is the notion of shared mobility on demand, which consists of customized dynamic routing for multi-passenger transport. A solution to this problem consists of a host of challenges that ranges from distributed optimization, behavioral modeling of passengers, traffic flow modeling, and distributed control. Recent efforts in our group have made some inroads into this problem and form the focus of this talk. A socio-technical model that combines behavioral models of passengers based on Cumulative Prospect Theory and traffic models will be discussed. The solution to dynamic routing is presented in the form of an optimization problem solved via an Alternating Minimization based approach. The model together with the optimization framework is then used to propose a dynamic tariff that can be viewed as a model-based control strategy based on Transactive Control, a methodology that is being explored in power grids for incentivizing flexible consumption.
The electricity grid is undergoing a paradigm shift. The classic grid goes back to the days of the first pioneers such as Edison, Westinghouse, and Siemens and has little changed over a century of deployment. The classic electricity grid is a centralized system with few large power sources with inherently large inertia supplying over a large network a distributed base of many relatively small consumers, who are essentially in control of their demand. The new grid will have many distributed generators, using unreliable and variable primary energy (read solar energy), and using power electronics to inject power into the grid. Moreover, the roles of the consumer will change dramatically, and they will be able to participate in the electricity market in many different capacities, perhaps even sacrificing some of their control over their consumptive energy demand. In the new grid, the engineering complexity is therefore significantly larger than in the classic grid. The sources are spatially distributed, demonstrate many different technologies and exhibit a greater range of different capacities, with generally less (temporal) reliability than is classically the case. Equally on the demand side technologies are changing, with an expanding electrical footprint as general personal transport becomes increasingly electrified. Moreover, new consumers (prosumers, and aggregators) and new services are entering the electricity energy market. In engineered systems variability in supply is normally counteracted through buffers, and complexity requires more control to maintain the desired quality of service. The electricity grid is no exception. However, buffers require the consideration of energy as the primary quantity to manage rather than power. Moreover, distributed control requires more sensors and communication than hitherto has been necessary. This talk presents an overview of the main issues, and through a control engineering lens develops how modern “internet-of-things” technology may enable the paradigm shift towards energy as the main guiding principle to control the grid, whilst maintaining the classic quality of service measures in terms of reliability, voltage and frequency regulation that we have come to enjoy. Remarkably this transition may even be realized whilst leaving the consumer in control of their demand, at least from an energy perspective.
The recent advances on vehicular technologies have led the ground transportation into a new era where the human-vehicle-roadway harmony is paramount for the next-generation intelligent vehicles and mobility. Synergistic combinations of physical insights into vehicle system characteristics, computational and communication capabilities, personalized understanding of human users as well as theories of optimization and control may offer effective means for substantially improving vehicle efficiency, driving safety, and environmental consciousness in real-world operations. This talk introduces a variety of smart vehicle system estimation and control research activities aiming to safe and efficient ground transportation by enabling optimally-personalized vehicle control. Innovative syntheses of estimation, optimization, and control theories with physical understanding of vehicle, human, and transportation systems for conventional, electrified, connected and automated vehicles will be emphasized through examples. Along with the system analytical designs, experimental and simulation results will be given to demonstrate the importance and efficacy of the learning-based and personalizable vehicle control technologies for current and future ground vehicles and mobility.
The significant progress we witness in sensors, actuators, materials, Internet of Things, perception and many other areas of Robotics and AI enable a radical redesign of production and distribution processes, in any economic sector, from Industry to Agriculture and Logistics. The more mature changes affecting industry are referred to as 'Digitization of the European Industry' at European level and 'Industry 4.0' in Italy and Germany. The same technologies can be applied to Agriculture leading to the concept of Precision Agriculture or ‘Agriculture 4.0’. A quite positive side effect of the recent advances is that the Circular Economy paradigm becomes economically sustainable allowing to cope with quite serious sustainability issues we are facing. We will describe and discuss the technological and practical issues and opportunities of the ongoing research and applications for Industry 4.0, Precision Agriculture and the Circular Economy and will explore and make some conjectures on what will come next. We will discuss how and why the issues related to the reproducibility of research results and methods for the objective evaluation of intelligent robots performances are of critical importance in the current context. The aim of this talk is to give a deep and hands-on understanding of the opportunities and challenges related to the radical transformation of product and service ecology made possible by the recent technological advancements in IOT, Machine and Deep Learning, Computer Vision and Object Recognition.
ESROCOS (http://www.h2020-esrocos.eu) is a European Project in the frame of the PERASPERA SRC, (http://www.h2020-peraspera.eu/), targeting the design of a Robot Control Operating Software (RCOS) for space robotics applications. ESROCOS goal is to provide an open-source framework to assist in the development of flight software for space robots, providing adequate features and performance with space-grade Reliability, Availability, Maintainability and Safety (RAMS) properties. This presentation presents ESROCOS and summarizes the approach.
In this talk, there will be shown new advancements in the Portuguese space sector and why it is so important to promote space education.