Session Co-Chairs: Demetris Zeinalipour (University of Cyprus, Cyprus), Jianliang Xu (Hong Kong Baptist University, Hong Kong), Mohamed F. Mokbel (University of Minnesota, USA) and Takahiro Hara (Osaka University, Japan) and
Nikos Mamoulis (University of Ioannina, Greece)
Abstract: Recent successes in AI can be attributed to the fact the supervised learning in static prediction tasks is effectively a solved problem. However, predictions on their own are not sufficient for decision making. Using road traffic signal control as a use case, we will highlight how reinforcement learning and its more recent offline variant can serve as a principled way of driving data-driven decision making.
Bio: Sanjay Chawla is a Research Director at the Qatar Computing Research Institute (QCRI). Before that he was a professor in the Faculty of Engineering, University of Sydney. His research interests span data mining and machine learning. He was a PC-Cochair of ACM SIGKDD 2021.
Session Co-Chairs: Christos Laoudias (University of Cyprus, Cyprus), Manon Kok (Delft University of Technology, Netherlands) and Sunwoo Kim (Hanyang University, Republic of Korea)
Description: Indoor Information Systems (IIS) have witnessed significant growth over the past decade, driven by the fact that 90% of our activities are carried out in indoor spaces. As a result, new research paradigms in constituent technologies have emerged, ranging from data-driven localization algorithms, to data privacy handling schemes, and indoor data management operators. Towards this direction, successful launching of popular applications relied on stored indoor spatial models fusing sensor information, exploiting sensor prevalence in smartphone devices and wireless connectivity pervasiveness, in light of the big data era and accompanying technologies. This workshop aims to discuss current trends and highlight future directions on both established and potentially transforming Algorithms for Indoor Architectures and Systems.
Organizers: Christos Laoudias (University of Cyprus, Cyprus),
Manon Kok (Delft University of Technology, Netherlands) and
Sunwoo Kim (Hanyang University, Republic of Korea)
Session Co-Chairs: Herodotos Herodotou (Cyprus University of Technology, Cyprus); Alexander Artikis (NCSR Demokritos, Greece) and Matthias Renz (Kiel University, Germany)
Description: The growth of the maritime sector has produced an increase of the global maritime traffic and of the activities exploiting the ocean environment and its resources. Safety and security of maritime navigation remain a concern, like the global societal objective of reducing the environmental impact of maritime activities to pursue a sustainable and inclusive "blue growth". Technological innovations led to the development of automated monitoring systems and maritime sensors networks, producing a tremendous increase of the maritime data available and opening new avenues to interdisciplinary science-driven maritime operations and policy making. Institutional and industrial initiatives are developing infrastructures for maritime data sharing and offering advanced processing, fusion, and analysis, developing added values products in support of the maritime operational and industrial communities, policy making and informed citizenship.The Maritime Big Data Workshop 2022 is organized under the umbrella of the 23rd IEEE International Conference on Mobile Data Management (MDM 2022). It will be an opportunity for researchers, technology providers, institutions participating in interdisciplinary big data initiatives, and representatives of the operational community, to meet and exchange on research results and innovations in the maritime context. The workshop will welcome the presentation of novel big data computational solutions with application in the maritime context.
Discussion:
The workshop will be organized in a manner that fosters interaction and exchange of ideas among the participants. Besides regular papers, we will also consider vision, retrospective, and work-in-progress papers that have the potential to stimulate debate on existing solutions or open challenges. We additionally plan to accept a limited number of demonstration papers where researchers and technologists will have the opportunity to describe an innovative system or tool in the area of data management for mobile and wireless access. We discourage the submission of incremental papers.
Organizers: Herodotos Herodotou (Cyprus University of Technology, Cyprus),
Alexander Artikis (University of Piraeus, Greece) and
Matthias Renz (Kiel University, Germany)
Description: Social network and mining research has advanced rapidly with the prevalence of the online social websites and instant messaging social communications systems. In addition, thanks to the recent advances in deep learning, many novel applications with mobile devices and social networks have been proposed and deployed. These social network systems are usually characterized by complex network structures and abundant contextual information. Moreover, by incorporating the spatial dimension, mobile and location-based social networks are now immersed in people’s everyday life via numerous innovative websites. In addition, mobile social networks can be exploited to foster many interesting applications and analysis, such as recommendations of locations and travel planning of friends, location-based viral marketing, community discovery, group mobility and behavior modeling.
Organizers: Wang-Chien Lee (Pennsylvania State University, USA),
De-Nian Yang (Academia Sinica, Taiwan),
Chih-Ya Shen (National Tsing Hua University, Taiwan) and
Jen-Wei Huang (National Cheng Kung University, Taiwan)
Description: Mobile and ubiquitous computing has emerged as today's most prevalent computing paradigm, thanks to the tremendous advances in a broad range of technologies and applications, including wireless networking, Internet of things, mobile and sensor systems, RFID technology, and various location-based services. The workshop is intended to solicit technical papers pertaining to the broadly-conceived mobile and ubiquitous systems. The papers must be original, previously unpublished research, and not currently under review by another conference or journal. We encourage submissions of all types -- theory, algorithm, experiment, and experience papers, with preference to system and real-world deployment.
Organizers: Yun Peng (Hong Kong Baptist University) and
Xiaoyi Fu (Hong Kong Baptist University)
Day 2 - Conference: Tuesday, June 7, 2022 (EU-AMERICAS)
Session Co-Chairs: Demetris Zeinalipour (University of Cyprus, Cyprus), Jianliang Xu (Hong Kong Baptist University, Hong Kong), Mohamed F. Mokbel (University of Minnesota, USA), and Mohamed Sarwat (Arizona State University, USA),
Xing Xie (Microsoft Research Asia, China), and
Karine Zeitouni (University of Versailles Saint-Quentin, France)
Abstract: Federated learning (FL) is an emerging distributed collaborative learning paradigm by decoupling the learning task from the centralized server to a decentralized population of edge clients. One of the attractive features of federated learning is its default client privacy, allowing clients to keep their sensitive training data locally and only share local model updates with the federated server. However, recent studies have revealed that such default client privacy is insufficient for protecting the privacy of client training data from both gradient leakage attacks and data poisoning attacks. This keynote will describe gradient leakage attacks and data poisoning attacks, and provide insights for designing effective privacy and security strategies for combating privacy leakage attacks and data poisoning attacks.
Bio: Ling Liu is a Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in the Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large scale big data-powered artificial intelligence (AI) systems, and machine learning (ML) algorithms and analytics, including performance, availability, privacy, security and trust. Prof. Liu is an elected IEEE Fellow, a recipient of IEEE Computer Society Technical Achievement Award (2012), and a recipient of the best paper award from numerous top venues, including IEEE ICDCS, WWW, ACM/IEEE CCGrid, IEEE Cloud, IEEE ICWS. Prof. Liu served on editorial board of over a dozen international journals, including the editor in chief of IEEE Transactions on Service Computing (2013-2016), and the editor in chief of ACM Transactions on Internet Computing (since 2019). Prof. Liu is a frequent keynote speaker in top-tier venues in Big Data, AI and ML systems and applications, Cloud Computing, Services Computing, Privacy, Security and Trust. Her current research is primarily supported by USA National Science Foundation under CISE programs, IBM and CISCO.
(#75)Integrating Heterogeneous Sources for Learned Prediction of Vehicular Data Consumption, Andi Zang (Northwestern University, USA), Xiaofeng Zhu (Microsoft, USA), Ce Li (University of Electronic Science and Technology, China), Fan Zhou (University of Electronic Science and Technology, China), and Goce Trajcevski (Iowa State University, USA)
(#57)Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection, Erik Andersen (University of Southern Denmark, Denmark), Marco Chiarandini (University of Southern Denmark, Denmark), Marwan Hassani (Eindhoven University of Technology, Netherlands), Stefan Jänicke (University of Southern Denmark, Denmark), Panagiotis Tampakis (University of Southern Denmark, Denmark), and Arthur Zimek (University of Southern Denmark, Denmark)
(#90)A Geospatial Method for Detecting Map-Based Road Segment Discrepancies, Jiawei Yao (University of Washington Tacoma, USA), Eyhab Al-Masri (University of Washington Tacoma, USA), Mohamed Ali (University of Washington Tacoma, USA), Vashutosh Agrawa (Microsoft Corporation, USA), Ming Tan (Microsoft Corporation, USA), Harsh Govind (Microsoft Corporation, USA), Adel Sabour (University of Washington Tacoma, USA), Abdulrahman Salama (University of Washington Tacoma, USA), Daniel Jiang (University of Washington Tacoma, USA), Reuben Keller
(University of Washington Tacoma, USA), Dino Jazvin (University of Washington Tacoma, USA), Ravi Prakash (Microsoft Corporation, USA), and Egor Maresov (Microsoft Corporation, USA)
Abstract: Recently, the trend of developing digital twins for smart cities has driven a need for managing large-scale Multidimensional, Dynamic, and Scene-oriented (MDS for short) spatial data. Due to the large data scale and complex data structure, queries over such data are more complicated and expensive than those on traditional spatial data, which poses challenges to the system efficiency and deployment costs. This talk will introduce Ganos, a cloud-native spatial database engine of PolarDB that is developed by Alibaba Cloud, to efficiently manage MDS spatial data. Ganos provides a systematic framework of data models, access methods, and operations for the MDS data. Especially, it optimizes query processing using cloud-native capabilities, and thus provides a new practice of moving from traditional on-premise spatial database to cloud-native spatial database. Ganos has been released since 2018, and it has been applied to many applications in different fields. This talk also shares the lessons learned from the customers and the expectations of modern cloud applications for new spatial database features.
Bio: Feifei Li is currently a Vice President of Alibaba Group, director of the database team of Alibaba Cloud Intelligence, and director of the database lab of DAMO academy. He has won multiple awards from ACM and IEEE and others. He is a recipient of the EDBT 2022 10 Years Test of Time Award, IEEE ICDCS 2020 best paper award, ACM SoCC 2019 Best Paper Award Runner-up, IEEE ICDE 2014 10 Years Most Influential Paper Award, ACM SIGMOD 2016 Best Paper Award, ACM SIGMOD 2015 Best System Demonstration Award, and IEEE ICDE 2004 Best Paper Award. He has been an editor, PC co-chair, and core committee member for many prestigious journals, conferences, and technical meetings. He has led the R&D efforts of building cloud-native database systems and products at Alibaba, such as cloud-native relational database PolarDB and cloud-native data warehouse AnalyticDB which help Alibaba Cloud Database to be named as a worldwide Cloud DBMS leader in the annual magic quadrant market report released by Gartner. He is an ACM/IEEE Fellow and featured on People of ACM.
Mobile Data Management for Green Mobility Moderators:
Christophe Claramunt (Naval Academy Research Institute, France) and Baihua Zheng (Singapore Management University, Singapore).
Panelists:
Christine Bassem (Wellesley College, USA), Kristian Torp (Aalborg University, Denmark), Goce Trajcevski (Iowa State University, USA), Demetris Zeinalipour (University of Cyprus, Cyprus)
Abstract: While many countries are developing appropriate actions towards a greener future and are moving towards adopting mobility activities, the real-time management and planning of transportation facilities and services still require the development of advanced mobile data management infrastructures. Indeed, novel green mobility solutions such as electric, hybrid, solar and hydrogen vehicles as well as public transportation resources are very likely to reduce the carbon footprint, but their successful implementation still requires appropriate mobile data management resources and application that will give a clear picture and demonstration of their effectiveness.
Amongst many issues still to address apart from social and economical ones, technological challenges are already in the front line. This panel aims to discuss the major challenges and open topics surrounding the technological and research challenges closely related to green mobility and with a specific focus on mobile data management issues such as but not limited to:
Development of smart mobility massive data management infrastructures
Open big data and services (traffic management, parking services, …) in support of green mobility (goods and people)
Current data management challenges and barriers in the development of green mobility at city, regional and global scales
Current breakthroughs in the development of real-time mobile data management infrastructures for green mobility
Transportation-demand applications, mobility on demand, share-services and autonomous vehicles, transportation of goods (logistics)
Real-time air quality vs. mobility in urban environments
Enabling ICT, AI and security solutions for green mobility (sensors, architectures)
Success stories as well as major failures in the development of green mobility
The panelists are expected to bring wealth of experience and vision from the academic, governmental and industrial sector to report on current successful experiences and answer a set of challenging questions that are currently open to public debate as well as the global benefits one can expect when developing green mobility and how mobile data infrastructures and services will help.
Bio: Panel Moderators
Christophe Claramunt is a professor in computer science at the French Naval Academy. His research is oriented towards theoretical, pluri-disciplinary and practical aspects of geographical information science (GIS). His main research interests are oriented to environmental, maritime and and urban GISs. He has long contributed to the development of computing and GIS systems in developping countries and actively orientates his research on the development of green and environmental friendly computing applications.
Baihua Zheng received the PhD degree in computer science from the Hong Kong University of Science and Technology, China, in 2003. She is currently a professor with the School of Information Systems, Singapore Management University, Singapore. Her research interests include mobile/pervasive computing, spatial databases, and big data analytics.
Panelists
Christine Bassem is an Assistant Professor at the Wellesley College Computer Science Department, which she joined after receiving her Ph.D. in Computer Science from Boston University in 2015. Her broad research interests are in mechanism and algorithm design in dynamic distributed systems, including crowd networks, mobile ad-hoc networks, and transport networks. Her current research is on the optimization of incentive-compatible mechanisms for coordinating the mobility of crowds in spatio-temporal networks, such as those found in mobile crowdsensing and ride-sharing platforms, with a focus on incentives, quality-of-work, reliability, and privacy.
Kristian Torp is a professor of Computer Science at Aalborg University Denmark.
Goce Trajcevski is a Harpole-Pentair Associate Professor at the Department of Electrical and Computer Engineering at Iowa State University, USA.
Demetris Zeinalipour is an Associate Professor of Computer Science at the University of Cyprus. His primary research interests include Data Management in Computer Systems and Networks. He actively engages in activities to help curbing the climate crisis, including research and practice on green planning systems for self-consumption of renewable energy, development of the vgate platform for virtual conferences during the COVID and upcoming energy crisis as well as platforms for virtual and augmented reality in the tourism sector.
Session Chair: Karine Zeitouni (University of Versailles Saint-Quentin, France)
(#10)Collecting Individual Trajectories Under Local Differential Privacy, Jianyu Yang (Beijing University of Posts and Telecommunications, China), Xiang Cheng (Beijing University of Posts and Telecommunications, China), Sen Su (Beijing University of Posts and Telecommunications, China), Huizhong Sun (Beijing University of Posts and Telecommunications, China), and Changju Chen (Beijing University of Posts and Telecommunications, China)
Mobile Applications for Privacy-Preserving Digital Contact Tracing, Christos Laoudias (KIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus), Steffen Meyer (Fraunhofer Institute of Integrated Circuits, Germany), Philippos Isaia (KIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus), Thomas Windisch (Fraunhofer Institute of Integrated Circuits, Germany),
Justus Benzler (Robert Koch Institute, Germany), and Maximilian Lenkeit (SAP SE, Technology & Innovation, Germany)
Abstract: Mobile applications for triggering Covid-19 exposure notifications without sacrificing the users’ privacy are a promising tool for complementing manual contact tracing that is a resource-demanding and labor-intensive task when the infections grow rapidly. This advanced seminar presents the fundamental concepts behind the realization of large-scale Mobile Contact Tracing Apps (MCTA). We provide an overview of this emerging field, while focusing on Bluetooth-based privacy-preserving solutions. We tackle the topic from multiple perspectives: background, state-of-the-art technologies, protocols, real-life implementations, performance indicators, security and privacy aspects, as well as future directions. The seminar presents the big picture, so that the target audience can further expand their knowledge by studying the material and following the references. Our presentation will be delivered through the lens of 2 country-wide MCTA, namely the Corona-Warn-App (CWA) and the CovTracer-Exposure Notification (CovTracer-EN) app deployed in Germany and Cyprus, respectively.
Bio: Christos Laoudias is a Research Lecturer at the KIOS Center of Excellence, University of Cyprus with long experience in localization, tracking, and navigation using wireless networks. He is the Technical Coordinator of the CovTracer-Exposure Notification (CovTracer-EN) Cyprus national contact tracing app for Covid-19. Before that he was leading the geolocation technology research team in Huawei Technologies Ireland Research Center working on the design of data-driven positioning solutions for cellular network planning and optimization. He holds a Diploma in Computer Engineering and Informatics (2003) and a M.Sc. in Integrated Hardware and Software Systems (2005) from the University of Patras, Greece, and a Ph.D. in Computer Engineering from the University of Cyprus (2014). He has contributed to the development of several award-winning indoor localization prototype systems, which have been released under open-source license, including Airplace and Anyplace. He has published several research and demo papers at the IEEE MDM conference and presented an advanced seminar on “Mobile Data Management in Indoor Spaces” at the MDM 2015.
Steffen Meyer studied Computer Science at Friedrich-Alexander University Erlangen-Nurnberg and University of Bath with focus on Operating Systems and Communications Systems. He joined Fraunhofer Institute for Integrated Circuits (IIS) in Erlangen/Nuremberg in 2002. From 2006 on he was head of “Cooperative Systems and Locating” Group working on Locating Solutions in wireless networks, location-based services and distributed cooperative applications. Since 2020 he is head of the “Location Awareness and Process Analytics” Group at Fraunhofer IIS with focus on Signal-Strength based location technologies and their application in human-centered working processes. In early 2020 he joined the PEPP-PT Project as a very first aim on building a German Corona Warn (CWA) App coordinating the development of BLE Distance Estimation and Risk Calculation Algorithms. In May 2020 he continued these activities in the CWA lead by SAP and T-Systems, now coordinating the parameterization and testing of BLE distance estimation-based risk calculation with the GAEN Framework.
Phillipos Isaia is a Senior Software Engineer at the KIOS Center of Excellence, University of Cyprus. He received his BSc degree in Computer Science from Loughborough University UK, in 2012. He then joined the Loughborough University Computer Science research department as a PhD student and he was awarded the Doctor of Philosophy degree in Software-Defined Networking (SDN) in 2018. In his doctoral research he worked on improving the performance of SDN using dynamic flow installation and management techniques. In addition, he implemented several data and packet prioritization algorithms working in collaboration with external partners of Loughborough University. He currently works on various projects related to eHealth, emergency response, critical infrastructures and simulation synchronization platforms. These projects include but are not limited to Covid-19 emergency response platforms as a lead software engineer, CovTracer-EN as a lead architect and security specialist, EU Recovery and Resilience Fund (RRF) Cyprus Innovative Public Health ICT System (CIPHIS) as a lead architect, and RRF Digital Police (DigiPol) as a technical coordinator.
Thomas Windisch studied information technology at the West Saxon University of Applied Sciences in Zwickau. Since completing his diploma thesis in 2007 and graduating as a qualified engineer, Thomas Windisch worked at the Nuremberg site of Fraunhofer IIS. His work focuses on research and further development of localization and networking technologies. In 2012, Mr. Windisch successfully completed his second degree as M. Eng. with a focus on energy optimization of communication networks. Since then he worked as a senior engineer for wireless communication until 2014. In the years until 2020, Mr. Windisch led the group “Embedded Communication Systems” with a focus on wireless networking. From 2020 on, he is dedicated to the topics of localization and data analysis, as well as Bluetooth distance estimation for digital Covid-19 contact tracing in the positioning and networks business unit in Nuremberg. He focused his activities on supporting the Corona-Warn-App under the leadership of SAP and T-Systems and supported the parameterization and testing of BLE distance estimation-based risk calculation with the GAEN Framework.
Justus Benzler is a medical epidemiologist at the Robert Koch Institute (RKI) in Berlin, Germany. After several years of clinical practice in obstetrics and surgery in Germany and then as district medical officer in Burkina Faso, he specialized in medical informatics. He set up Demographic and Health Surveillance systems in Burkina Faso and South Africa, focused on Malaria and HIV. His work within Infectious Disease Surveillance at RKI since 2002 was intermitted by multi-year assignments with the Secretariat of the Pacific Community and with WHO, where he focused on dengue and yellow fever prevention and control, respectively. He contributed to the design and development of the Infectious Disease Surveillance systems DEMIS (German national system) and SORMAS (used in several countries worldwide). In spring 2020, Justus participated in the Pan-European Privacy-Preserving Proximity Tracing initiative, before Germany adopted the GAEN framework. Since then he worked on the development and improvement of Corona Warn App, the German national proximity tracing tool, and on other Covid-related digital tools such as the German apps for handling and validating DCCs (EU Digital Covid Certificates) from the epidemiological and data science perspective.
Maximilian Lenkeit is a Development Architect at SAP SE and part of the architecture team of the Corona-Warn-App, Germany’s digital contact tracing solution. He joined the project team in summer 2020 just after the initial release. Since then, he contributed to adopting several new functionalities, such supporting interoperability with other European countries and the migration to an improved version of the GAEN protocol. His background is in Business Information Technology and he has been working for SAP SE since 2009.
Mobile Applications for Privacy-Preserving Digital Contact Tracing, Christos Laoudias (KIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus), Steffen Meyer (Fraunhofer Institute of Integrated Circuits, Germany), Philippos Isaia (KIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus), Thomas Windisch (Fraunhofer Institute of Integrated Circuits, Germany),
Justus Benzler (Robert Koch Institute, Germany), and Maximilian Lenkeit (SAP SE, Technology & Innovation, Germany)
Abstract: Mobile applications for triggering Covid-19 exposure notifications without sacrificing the users’ privacy are a promising tool for complementing manual contact tracing that is a resource-demanding and labor-intensive task when the infections grow rapidly. This advanced seminar presents the fundamental concepts behind the realization of large-scale Mobile Contact Tracing Apps (MCTA). We provide an overview of this emerging field, while focusing on Bluetooth-based privacy-preserving solutions. We tackle the topic from multiple perspectives: background, state-of-the-art technologies, protocols, real-life implementations, performance indicators, security and privacy aspects, as well as future directions. The seminar presents the big picture, so that the target audience can further expand their knowledge by studying the material and following the references. Our presentation will be delivered through the lens of 2 country-wide MCTA, namely the Corona-Warn-App (CWA) and the CovTracer-Exposure Notification (CovTracer-EN) app deployed in Germany and Cyprus, respectively.
Bio: Christos Laoudias is a Research Lecturer at the KIOS Center of Excellence, University of Cyprus with long experience in localization, tracking, and navigation using wireless networks. He is the Technical Coordinator of the CovTracer-Exposure Notification (CovTracer-EN) Cyprus national contact tracing app for Covid-19. Before that he was leading the geolocation technology research team in Huawei Technologies Ireland Research Center working on the design of data-driven positioning solutions for cellular network planning and optimization. He holds a Diploma in Computer Engineering and Informatics (2003) and a M.Sc. in Integrated Hardware and Software Systems (2005) from the University of Patras, Greece, and a Ph.D. in Computer Engineering from the University of Cyprus (2014). He has contributed to the development of several award-winning indoor localization prototype systems, which have been released under open-source license, including Airplace and Anyplace. He has published several research and demo papers at the IEEE MDM conference and presented an advanced seminar on “Mobile Data Management in Indoor Spaces” at the MDM 2015.
Steffen Meyer studied Computer Science at Friedrich-Alexander University Erlangen-Nurnberg and University of Bath with focus on Operating Systems and Communications Systems. He joined Fraunhofer Institute for Integrated Circuits (IIS) in Erlangen/Nuremberg in 2002. From 2006 on he was head of “Cooperative Systems and Locating” Group working on Locating Solutions in wireless networks, location-based services and distributed cooperative applications. Since 2020 he is head of the “Location Awareness and Process Analytics” Group at Fraunhofer IIS with focus on Signal-Strength based location technologies and their application in human-centered working processes. In early 2020 he joined the PEPP-PT Project as a very first aim on building a German Corona Warn (CWA) App coordinating the development of BLE Distance Estimation and Risk Calculation Algorithms. In May 2020 he continued these activities in the CWA lead by SAP and T-Systems, now coordinating the parameterization and testing of BLE distance estimation-based risk calculation with the GAEN Framework.
Phillipos Isaia is a Senior Software Engineer at the KIOS Center of Excellence, University of Cyprus. He received his BSc degree in Computer Science from Loughborough University UK, in 2012. He then joined the Loughborough University Computer Science research department as a PhD student and he was awarded the Doctor of Philosophy degree in Software-Defined Networking (SDN) in 2018. In his doctoral research he worked on improving the performance of SDN using dynamic flow installation and management techniques. In addition, he implemented several data and packet prioritization algorithms working in collaboration with external partners of Loughborough University. He currently works on various projects related to eHealth, emergency response, critical infrastructures and simulation synchronization platforms. These projects include but are not limited to Covid-19 emergency response platforms as a lead software engineer, CovTracer-EN as a lead architect and security specialist, EU Recovery and Resilience Fund (RRF) Cyprus Innovative Public Health ICT System (CIPHIS) as a lead architect, and RRF Digital Police (DigiPol) as a technical coordinator.
Thomas Windisch studied information technology at the West Saxon University of Applied Sciences in Zwickau. Since completing his diploma thesis in 2007 and graduating as a qualified engineer, Thomas Windisch worked at the Nuremberg site of Fraunhofer IIS. His work focuses on research and further development of localization and networking technologies. In 2012, Mr. Windisch successfully completed his second degree as M. Eng. with a focus on energy optimization of communication networks. Since then he worked as a senior engineer for wireless communication until 2014. In the years until 2020, Mr. Windisch led the group “Embedded Communication Systems” with a focus on wireless networking. From 2020 on, he is dedicated to the topics of localization and data analysis, as well as Bluetooth distance estimation for digital Covid-19 contact tracing in the positioning and networks business unit in Nuremberg. He focused his activities on supporting the Corona-Warn-App under the leadership of SAP and T-Systems and supported the parameterization and testing of BLE distance estimation-based risk calculation with the GAEN Framework.
Justus Benzler is a medical epidemiologist at the Robert Koch Institute (RKI) in Berlin, Germany. After several years of clinical practice in obstetrics and surgery in Germany and then as district medical officer in Burkina Faso, he specialized in medical informatics. He set up Demographic and Health Surveillance systems in Burkina Faso and South Africa, focused on Malaria and HIV. His work within Infectious Disease Surveillance at RKI since 2002 was intermitted by multi-year assignments with the Secretariat of the Pacific Community and with WHO, where he focused on dengue and yellow fever prevention and control, respectively. He contributed to the design and development of the Infectious Disease Surveillance systems DEMIS (German national system) and SORMAS (used in several countries worldwide). In spring 2020, Justus participated in the Pan-European Privacy-Preserving Proximity Tracing initiative, before Germany adopted the GAEN framework. Since then he worked on the development and improvement of Corona Warn App, the German national proximity tracing tool, and on other Covid-related digital tools such as the German apps for handling and validating DCCs (EU Digital Covid Certificates) from the epidemiological and data science perspective.
Maximilian Lenkeit is a Development Architect at SAP SE and part of the architecture team of the Corona-Warn-App, Germany’s digital contact tracing solution. He joined the project team in summer 2020 just after the initial release. Since then, he contributed to adopting several new functionalities, such supporting interoperability with other European countries and the migration to an improved version of the GAEN protocol. His background is in Business Information Technology and he has been working for SAP SE since 2009.
(#106)A Dashboard Tool for Mobility Data Mining Preprocessing Tasks, Yaksh J. Haranwala (Memorial University of Newfoundland, Canada), Salman Haidri (Memorial University of Newfoundland, Canada), Terrence S. Tricco (Memorial University of Newfoundland, Canada), Vinicius Prado da Fonseca (Memorial University of Newfoundland, Canada), and Amilcar Soares (Memorial University of Newfoundland, Canada)
(#109)AutoMATise: Multiple Aspect Trajectory Data Mining Tool Library, Tarlis Tortelli Portela (Federal University of Santa Catarina, Brazil & University of Pisa & ISTI-CNR & IFPR, Italy), Vania Bogorny (Federal University of Santa Catarina, Brazil), Anna Bernasconi (University of Pisa, Italy), and Chiara Renso (ISTI-CNR, Italy)
(#116)MapsVision: A Computer Vision-Based System for Detecting Discrepancies in Map Textual
Labels, Adel Aly (University of Washington, Tacoma, USA), Jiawei Yao
(University of Washington, Tacoma, USA), Abdul Salama (University of Washington, Tacoma, USA), Cordel Hampshire (University of Washington, Tacoma, USA), Eyhab Al-Masri (University of Washington, Tacoma, USA), Mohamed Ali (University of Washington, Tacoma, USA), Harsh Govind (Microsoft Corporation, Redmond, USA), Ming Tan (Microsoft
Corporation, Redmond, USA), Vashutosh Agrawal (Microsoft Corporation, Redmond, USA), Egor Maresov (Microsoft Corporation, Redmond, USA), and Ravi Prakash (Microsoft Corporation, Redmond, USA)
(#118)CovidLens: Visually Understanding the Covid-19 Indicators Through the Lens of Mobility
Data, Mohamed Sharaf (United Arab Emirates University, UAE), Xiaozhong Zhang (University of Pittsburgh, USA), Panos Chrysanthis (University of Pittsburgh, USA), Wadima Alsaedi (United Arab Emirates University, UAE), Maitha Alkalbani (United Arab Emirates University, UAE), Heba Helal (United Arab Emirates University, UAE), and Alyazia Aldhaheri (United Arab Emirates University, UAE)
(#119)Targeted Content-Sharing in a Multi-Group DTN Application using Attribute-Based Encryption, Xiaofei Cao (Missouri University of Science and Technology, USA), Shudip Datta (Missouri University of Science and Technology, USA), Ram Charan Bolla (Missouri University of Science and Technology, USA), and Sanjay Madria (Missouri University of Science and Technology, USA)
(#120)Efficient Detection of COVID-19 Exposure Risk, Brian T. Nixon (University of Pittsburgh, USA), Rakan Alseghayer (University of Pittsburgh, USA), Benjamin Graybill (University of Pittsburgh, USA), Xiaozhong Zhang (University of Pittsburgh, USA), Constantinos Costa (University of Pittsburgh, USA), and Panos K. Chrysanthis (University of Pittsburgh, USA)
(#121)EnterCY: A Virtual and Augmented Reality Tourism Platform for Cyprus, Soteris Constantinou (University of Cyprus, Cyprus), Andreas Pamboris (Frederick University, Cyprus), Rafael Alexandrou (Frederick University, Cyprus), Christophoros Kronis (Frederick University, Cyprus), Demetrios Zeinalipour-Yazti (University of Cyprus, Cyprus), Harris Papadopoulos (Frederick University, Cyprus), and Andreas Konstantinidis (Frederick University, Cyprus)
(#122)Jarvis: A Voice-Based Context-as-a-Service Mobile Tool for a Smart Home Environment, Ngoc Dung Huynh (Deakin University, Australia), Mohamed Reda Bouadjenek (Deakin University, Australia), Ali Hassani (Deakin University, Australia), Imran Razzak (Deakin University, Australia), Kevin Lee (Deakin University, Australia), Chetan Arora (Deakin University, Australia), and Arkady Zaslavsky (Deakin University, Australia)
(#106)A Dashboard Tool for Mobility Data Mining Preprocessing Tasks, Yaksh J. Haranwala (Memorial University of Newfoundland, Canada), Salman Haidri (Memorial University of Newfoundland, Canada), Terrence S. Tricco (Memorial University of Newfoundland, Canada), Vinicius Prado da Fonseca (Memorial University of Newfoundland, Canada), and Amilcar Soares (Memorial University of Newfoundland, Canada)
(#109)AutoMATise: Multiple Aspect Trajectory Data Mining Tool Library, Tarlis Tortelli Portela (Federal University of Santa Catarina, Brazil & University of Pisa & ISTI-CNR & IFPR, Italy), Vania Bogorny (Federal University of Santa Catarina, Brazil), Anna Bernasconi (University of Pisa, Italy), and Chiara Renso (ISTI-CNR, Italy)
(#116)MapsVision: A Computer Vision-Based System for Detecting Discrepancies in Map Textual
Labels, Adel Aly (University of Washington, Tacoma, USA), Jiawei Yao
(University of Washington, Tacoma, USA), Abdul Salama (University of Washington, Tacoma, USA), Cordel Hampshire (University of Washington, Tacoma, USA), Eyhab Al-Masri (University of Washington, Tacoma, USA), Mohamed Ali (University of Washington, Tacoma, USA), Harsh Govind (Microsoft Corporation, Redmond, USA), Ming Tan (Microsoft
Corporation, Redmond, USA), Vashutosh Agrawal (Microsoft Corporation, Redmond, USA), Egor Maresov (Microsoft Corporation, Redmond, USA), and Ravi Prakash (Microsoft Corporation, Redmond, USA)
(#118)CovidLens: Visually Understanding the Covid-19 Indicators Through the Lens of Mobility
Data, Mohamed Sharaf (United Arab Emirates University, UAE), Xiaozhong Zhang (University of Pittsburgh, USA), Panos Chrysanthis (University of Pittsburgh, USA), Wadima Alsaedi (United Arab Emirates University, UAE), Maitha Alkalbani (United Arab Emirates University, UAE), Heba Helal (United Arab Emirates University, UAE), and Alyazia Aldhaheri (United Arab Emirates University, UAE)
(#119)Targeted Content-Sharing in a Multi-Group DTN Application using Attribute-Based Encryption, Xiaofei Cao (Missouri University of Science and Technology, USA), Shudip Datta (Missouri University of Science and Technology, USA), Ram Charan Bolla (Missouri University of Science and Technology, USA), and Sanjay Madria (Missouri University of Science and Technology, USA)
(#120)Efficient Detection of COVID-19 Exposure Risk, Brian T. Nixon (University of Pittsburgh, USA), Rakan Alseghayer (University of Pittsburgh, USA), Benjamin Graybill (University of Pittsburgh, USA), Xiaozhong Zhang (University of Pittsburgh, USA), Constantinos Costa (University of Pittsburgh, USA), and Panos K. Chrysanthis (University of Pittsburgh, USA)
(#121)EnterCY: A Virtual and Augmented Reality Tourism Platform for Cyprus, Soteris Constantinou (University of Cyprus, Cyprus), Andreas Pamboris (Frederick University, Cyprus), Rafael Alexandrou (Frederick University, Cyprus), Christophoros Kronis (Frederick University, Cyprus), Demetrios Zeinalipour-Yazti (University of Cyprus, Cyprus), Harris Papadopoulos (Frederick University, Cyprus), and Andreas Konstantinidis (Frederick University, Cyprus)
(#122)Jarvis: A Voice-Based Context-as-a-Service Mobile Tool for a Smart Home Environment, Ngoc Dung Huynh (Deakin University, Australia), Mohamed Reda Bouadjenek (Deakin University, Australia), Ali Hassani (Deakin University, Australia), Imran Razzak (Deakin University, Australia), Kevin Lee (Deakin University, Australia), Chetan Arora (Deakin University, Australia), and Arkady Zaslavsky (Deakin University, Australia)
(#78)DriBe: On-road Mobile Telemetry for Locality-Neutral Driving Behavior Annotation, Debasree Das (Indian Institute of Technology Kharagpur, India), Sugandh Pargal (Indian Institute of Technology Kharagpur, India), Sandip Chakraborty (Indian Institute of Technology Kharagpur, India), and Bivas Mitra (Indian Institute of Technology Kharagpur, India)
(#80)On Epidemic-Aware Socio Spatial POI Recommendation, Cedric Parfait Kankeu Fotsing (National Tsing Hua University, Taiwan), Ya-Wen Teng (Academia Sinica, Taiwan), Guang-Siang Lee (Academia Sinica, Taiwan), Chih-Ya Shen (National Tsing Hua University), Yi-Shin Chen (National Tsing Hua University), and De-Nian Yang (Academia Sinica, Taiwan)
(#61)Optimizing Graph-Based Approximate Nearest Neighbor Search: Stronger and Smarter, Jun Liu (Tsinghua University, China), Zhenhua Zhu (Tsinghua University, China), Jingbo Hu (Tsinghua University, China), Hanbo Sun (Tsinghua University, China), Li Liu (Kuaishou Technology, USA), Lingzhi Liu (Kuaishou Technology, USA), Guohao Dai (Tsinghua University, China), Huazhong Yang (Tsinghua University, China), and Yu Wang (Tsinghua University, China)
(#26)A Matching Based Spatial Crowdsourcing Framework for Egalitarian Task Assignment, Ramneek Kaur (Indraprastha Institute of Information Technology Delhi, India), Vikram Goyal (Indraprastha Institute of Information Technology Delhi, India), Venkata M. V. Gunturi (Indian Institute of Technology Ropar, India), and Cheng Long (Nanyang Technological University, Singapore)
Session Co-Chairs: Panos K. Chrysanthis (University of Pittsburgh, USA) and Vana Kalogeraki (Athens University of Economics and Business, Greece)
D&I Workshop Falaah Arif Khan (New York University, USA)
Abstract: Session description:
Humor is a contextual element of human communication, representing a critical difference between people and machines. Coupled with visual imagery, it presents a formidable weapon with which to cut through technical jargon and to make the discourse around critical technologies more accessible to the general public. At NYU’s center for responsible AI we run two comic book series: The Data, Responsibly comics series, aimed at budding data scientists and practitioners; and the “We are AI” comic series targeted at the general public. The primary goal of this session is to share insights from our ongoing work in using comic books as a medium of scientific dissemination and to equip participants – through hands-on activities – with the skills to build upon and continue such creative explorations, themselves. Participants will collectively “crowdsource” a comic book about Responsible AI, centered around their personal lived experience. A key novelty of this session will be the use of original artwork to provoke participants to think critically about what democratic, accessible and accountable algorithmic systems look like. We will use panels from our comics to demonstrate to participants how to break down complicated topics into simple, relatable and humorous cartoons. The best part? No art skills needed! At the event, we will engage participants in a creative exploration into what Responsible AI looks like, discussing ideas and viewpoints around the themes of algorithmic justice, fairness, rights and liberties, grounded in their lived experiences. We will emphasize underrepresented viewpoints and center the narrative around marginalized communities.
Take-aways:
The comic book format invites the readers to be part of a solution because they can “see” the systems, values, and impacts clearly and beautifully rendered. It also reveals the limitations of the scientific method in addressing bias in algorithms. This activity will advance creative techniques for improving public engagement in AI, inviting participants to contribute a creative response to the multi-faceted approach of the ‘Data, Responsibly’ comics. Specifically:
o review the illustrative metaphor of ‘data as a mirror reflection of the world’ — a reflection that both distorts, and is distorted by, the world,
o anchor narratives in personal, lived experiences (For example: people with disabilities),
o emphasize accessibility as the norm,
o challenge the extant, binary framing of techno-optimism vs. techno-skepticism, and
o apply the “onion structure” to a narrative, such that both a casual reader and an expert is able to see themselves in the text.
Bio: Falaah is a first year Data Science PhD student at NYU, working with Prof Julia Stoyanovich on the ‘fairness’ and ‘robustness’ of algorithmic systems. An engineer by training and an artist by nature, Falaah creates scientific comic books to bridge together scholarship from different disciplines, and to disseminate the nuances of her research in a way that is more accessible to the general public — She runs the ‘Data, Responsibly’ and ‘We are AI’ comic series with Prof Julia Stoyanovich at NYU’s Center for Responsible AI, and the ‘Superheroes of Deep Learning’ comic series with Prof Zack Lipton (CMU). Falaah holds an undergraduate degree in Electronics and Communication Engineering (with a minor in Mathematics) from Shiv Nadar University, India, and has industry experience in building machine learning models for access management and security at Dell EMC.
Day 4 - Conference: Thursday, June 9, 2022 (EU-AMERICAS)
Session Co-Chairs: Demetris Zeinalipour (University of Cyprus, Cyprus), Jianliang Xu (Hong Kong Baptist University, Hong Kong), Mohamed F. and Mokbel (University of Minnesota, USA)
Abstract: Emerging information technologies such as cyberphysical systems, Internet-of-Things, cloud computing, mobile/wireless networking, and big data technologies are making available new modalities of information and new channels of communication. These technologies have the potential to enable new levels of resilience and efficiencies in community-wide infrastructures and services via smart building services, robust and sustainable water systems and timely access to public safety resources in times of duress. We envision future cyber-physical-human infrastructures (CPHIs) that will provide more efficient operation on a day-to-day basis as well as enhanced situational awareness during extreme events and disasters.
In this talk, we discuss the role of “planned” and “event-driven” mobility in creating resilient CPHIs that require combining technologies at different levels. At the platform level, systems must incorporate intelligent collection and ingest of data from diverse insitu and mobile sensors and sources and timely data exchange across organizations/individuals over heterogeneous communication networks. At the information level, the gathered information is used to extract higher level semantic observations by composing model-driven and AI-driven methods. Adaptation is a fundamental aspect of systems that rapidly transform themselves to meet dynamic needs; we discuss how incorporating mobility is critical to enabling adaptation for resilient community platforms. Drawing on our recent efforts in smart buildings, smartwater platforms and smart firefighting, I will discuss the role of mobility, the Internet-of-Things, and adaptive middleware for community lifelines. This will open up new possibilities for resilient communities of the future.
Bio: Nalini Venkatasubramanian is currently a Professor in the School of Information and Computer Science at the University of California Irvine. She has had significant research and industry experience in the areas of distributed systems, adaptive middleware, pervasive and mobile computing, cyberphysical systems, distributed multimedia and formal methods and has over 300 publications in these areas. As the Co-Director for the Center for Emergency Response Technologies at UC Irvine, Nalini’s recent research has focused on enabling resilient, sustainable and scalable observation and analysis of situational information from multimodal input sources; dynamic adaptation of the underlying systems to enable information flow under massive failures and the dissemination of rich notifications to members of the public at large. She is the recipient of the prestigious NSF Career Award, multiple Undergraduate Teaching Excellence Awards and best paper awards. Prof. Venkatasubramanian has served in numerous program and organizing committees of conferences on middleware, distributed systems and multimedia and on the editorial boards of journals. She received and M.S and Ph.D in Computer Science from the University of Illinois in Urbana-Champaign. Her research is supported both by government and industrial sources such as NSF, DHS, ONR, DARPA, Novell, Hewlett-Packard and Nokia. Prior to arriving at UC Irvine, Nalini was a Research Staff Member at the Hewlett-Packard Laboratories in Palo Alto, California.
Session Chair: Christophe Claramunt (Naval Academy Research Institute, France)
(#64)Practical Privacy Preservation in a Mobile Cloud Environment, Dimitrios Tomaras (Athens University of Economics and Business, Greece), Michail Tsenos (Athens University of Economics and Business, Greece), and Vana Kalogeraki (Athens University of Economics and Business, Greece)
Session Chair: Constantinos Costa (University of Pittsburgh, USA)
(#48)Efficiently Answering k-hop Reachability Queries in Large Dynamic Graphs for Fraud Feature Extraction, Zequan Xu (Xiamen University, China), Siqiang Luo (Nanyang Technological University, Singapore), Jieming Shi (The Hong Kong Polytechnic University, China), Hui Li (Xiamen University, China), Chen Lin (Xiamen University, China), Qihang Sun (Tencent Inc., China), and Shaofeng Hu (Tencent Inc., China)
(#69)Tracking the Evolution of Water Flow Patterns Based on Spatio-Temporal Particle Flow
Clusters, Nelson Tavares de Sousa (Christian-Albrechts-Universität zu Kiel, Germany), Carola Trahms (Christian-Albrechts-Universität zu Kiel, Germany; GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany), Peer Kröger (Christian-Albrechts-Universität zu Kiel, Germany),
Matthias Renz (Christian-Albrechts-Universität zu Kiel, Germany), René Schubert (Univ. Brest, France; GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany), and Arne Biastoch (GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany; Christian-Albrechts-University, Germany)
Session Chair: Maria Luisa Damiani (University of Milan, Italy)
Scalable Analytics on Large Sequence Collections, Karima Echihabi (Mohammed VI Polytechnic University, Morocco) and Themis Palpanas (Universite Paris Cite & French University Institute (IUF), France)
Abstract: Data series are a prevalent data type that has attracted lots of interest in recent years. Specifically, there has been an explosive interest towards the analysis of large volumes of data series in many different domains, and in particular, in the Internet of Things (IoT). In this tutorial, we focus on applications that produce massive collections of data series, and we provide the necessary background on data series management and analytics. Moreover, we discuss the need for fast similarity search for supporting machine learning applications, and describe efficient similarity search techniques, indexes and query processing algorithms. Finally, we discuss the role that deep learning techniques can play in this context. We conclude with the challenges and open research problems in this domain.
Bio: Karima Echihabi is an Assistant Professor at Mohammed VI Polytechnic University (UM6P) in Morocco. She is interested in scalable data analytics and data series management and has performed an extensive analysis of data series indexes. She holds a PhD degree from Mohammed V University (Morocco) and the University of Paris (France) and a Masters Degree in Computer Science from the University of Toronto. She has worked as a software engineer in the Windows team at Microsoft, Redmond (USA), and the Query Optimizer team at the IBM Toronto Lab (Canada).
Kostas Zoumpatianos is a Software Engineer at Snowflake Computing. He has been a Marie Curie Fellow at the University of Paris and a postdoctoral researcher at Harvard University. He got his PhD from the University of Trento in topics related to indexing and managing large collections of data series. He also holds a M.Sc. in Information Management and a Dipl.Eng. in Information and Communication Systems Engineering from the University of the Aegean in Greece.
Themis Palpanas is Senior Member of the French University Institute (IUF), a distinction that recognizes excellence across all academic disciplines, and professor of computer science at the University of Paris (France), where he is director of the Data Intelligence Institute of Paris (diiP), and director of the data management group, diNo. He received the BS degree from the National Technical University of Athens, Greece, and the MSc and PhD degrees from the University of Toronto, Canada. His interests include problems related to data science (big data analytics and machine learning applications). He is the author of 9 US patents and 2 French patents. He is the recipient of 3 Best Paper awards, and the IBM Shared University Research (SUR) Award. He is currently serving on the VLDB Endowment Board of Trustees, and as an Editor in Chief for the BDR Journal. He has served as General Chair for VLDB 2013, and in the program committees of all major conferences in the areas of data management and analysis.
Abstract: We live in the era of massive exodus and delicate personal security issues. Millions of migrant children are lost in Europe, and adults migrating from the LATAM region to North America are missing. Women disappear without a trace as they flee from war, hunger, disease, and bad local economic and political situations. This exodus creates humanitarian problems that countries have to deal with, and inclusive decolonised mobility analytics can bring hope.
Indeed, the “digital age” has brought great innovation, opportunity and connectivity and opens the hope of using data to address important questions about “subaltern” people mobility. However, too often, data is collected, analysed and interpreted in a way that perpetuates the narrative of poverty and need, painting a portrait of disparity and deficit. It is essential to ensure that both data and processing strategies (algorithms) and digital technology do not reproduce colonial paradigms of oppression, domination and harm. To avoid this narrative, it is essential to have a reckoning over lingering colonial history and practices, which are evident in the global imbalance between the Global North and the Global South, a continuation of the extractive and colonial relationship.
This talk will be weaving a trait with two strands: 1) crowds behaviour analytics techniques that combine data management and visualisation to control and model the crowds as complex systems; 2) a decolonisation perspective to perform data analysis more inclusively, allowing displaced communities to speak out.
Bio: Genoveva Vargas-Solar (http://www.vargas-solar.com) is a principal scientist of the French Council of Scientific Research (CNRS) and a member of the DataBase group of the Laboratory on Informatics on Image and Information Systems (LIRIS). She is a regular member of the Mexican Academia of Computing. She obtained her Habilitation à Diriger des Recherches (HDR - tenure) from University of Grenoble. She obtained her first PhD degree in Computer Science at University Joseph Fourier and her second PhD degree in Literature at University Stendhal. She obtained her first master’s degree in computer science at University Joseph Fourier and her second master’s degree in Compared Literature at University Stendhal. She did her undergraduate studies in Computer Systems Engineering at Universidad de las Américas in Puebla. She contributes to the construction of service-based database and ata science management systems. She proposes query evaluation methodologies, algorithms, and tools for composing, deploying, and executing data science functions on just in time architectures (disaggregated data centres). Her research interests in Literature concern middle age Literature, myths’ critics and myths’ analysis applied to different myths of origins. She promotes gender equality and diversity and inclusion (D&I) actions. She is a member of the gender equality committee at LIRIS and she represents EDBT in the inter-conference group D&I databases. She leads the SINFONIA and JOWDISAI projects on women's work in AI and DS. She actively promotes scientific cooperation in Computer Science between Latin America and Europe, particularly between France and Mexico.
Session Co-Chairs: Demetris Zeinalipour (University of Cyprus, Cyprus), Jianliang Xu (Hong Kong Baptist University, Hong Kong), Mohamed F. and Mokbel (University of Minnesota, USA)
(#closing)MDM 2022 Closing and MDM 2023 Presentation, Demetris Zeinalipour (University of Cyprus, Cyprus), Jianliang Xu (Hong Kong Baptist University, Hong Kong), Mohamed F. Mokbel (University of Minnesota, USA), Mohamed Sarwat (Arizona State University, USA), Xing Xie (Microsoft Research Asia, China) and Karine Zeitouni (University of Versailles Saint-Quentin, France)
