Tree Technology S.A.
TREE Technology SA (TREE, www.treetk.com) is a Spanish R&D-performing SME providing information and communication technology solutions based on Big Data and Artificial Intelligence for different sectors and markets (including healthcare, safety and security, finance, public bodies, cultural heritage, energy, space, industry, and transport). TREE works within an open innovation model to provide their customers with advanced ICT solutions, helping them to optimise their processes and improve their business. R&D activities, in particular cooperative initiatives, are key to the company business model in assessing the maturity of emerging technologies, gathering new and differential knowledge, and identifying strategic partners to create new business opportunities.
Its R&D unit focuses on Artificial Intelligence and Big Data, integrating emerging technologies as part of the Smart Data ecosystem. In this context, Machine Learning and Analytics, Computer Vision, Cognitive Systems, Distributed and Scalable Computing, or Visual Analytics occupy a relevant position among the company’s research lines.
This multi-faceted and cross-cutting expertise in data has motivated the assignment the leadership of WP2 to Tree Technology. Indeed, WP2 (“System Architecture Specifications and Design”) deals with the definition of requirements for all the components of the TeamAware ecosystem including the different subsystems, the platform, and the secure and standardised network. The analysis is made across the
- organisational,
- technical, and
- legal
dimensions with the cooperation with the rest of partners involved in the work package. As part of the activities carried out in this work package, Tree Technology also leads tasks T2.2 (“End-users needs, requirements, constraints and scenarios”) and T2.5 (“System architecture and communication network design”) devoted to the definition of validation scenarios and the design of the TeamAware systems, respectively.
Tree Technology also has a pre-eminent role in WP3 and WP4. The goal of WP3 (“Visual Scene Analysis System”) is to design and develop the TeamAware system devoted to the recognition of a disaster zone with a drone-mounted camera and the subsequent analysis of the video footage and images. Within this work package, Tree Technology leverages its Computer Vision expertise to lead T3.3 (“Semantic understanding of environmental features”) related to the analysis of images and classification of the elements involved in the scene, as well as T3.5 (“System validation”) involving the definition of unit tests as part of the global validation activities.
In turn, WP4 (“Infrastructure Monitoring System”) deals with a system capable of identifying structural risks and threats surrounding the first responders based on the visual detection of damages on structures and infrastructures within the critical event area, using drone surveillance. Again, Tree Technology relies on its Computer Vision expertise to achieve a more effective collaboration towards the adaptations’ design of the TeamAware system.
Other activities performed by Tree Technology also involve WP12 (“Integration and Test”), WP13 (“Demonstration and Validation”), aside from other cross-cutting dissemination and management activities.
Jorge Fontenla
Dr. Jorge Fontenla, R&D Project Manager in TREE, holds a degree in Telecommunication Engineering by the University of Vigo with the specialisations of Telematics (2006) and Radiocommunications (2010), a PhD in Telematics (2010), and an MsC in Signal Processing for communications (2014). He has a wide experience in a variety of fields of applications, although his main areas of expertise are E-Learning, Cloud Computing, Software-Defined Networks, Cybersecurity, and Connected and Autonomous Transportation. He has participated and coordinated some of the most relevant European projects in this regard, including SONATA (H2020 – 671517), C-ROADS Spain (CEF Transport 2016), CONCORDA (CEF Transport 2016), and CRUSOE (CEF Telecom 2016). He has authored more than 40 scientific publications and holds two US patents.
Serge Sushkov
MSc (1996), PhD (2003) from Physics Institute of Humboldt University of Berlin, Germany. His background comes from the High-Energy Physics science, where he worked between 1994 and 2009 mostly on the CERN-based (http://cern.ch) Experiments. His activities included statistical data analysis (data mining, pattern recognition, machine learning, Neural Networks), Monte-Carlo simulations, large-scale data processing with LCG-GRID software, including software & UNIX system administration. From the middle of 2004 till the end of 2009 he actively participated in SW design and SW development of Trigger and Data Acquisition (TriggerDAQ) for ATLAS experiment (http://Atlas.cern) at CERN, Geneva, Switzerland. There he obtained initial experiences in SW Development and Project Management methodologies.
Since 2010 and till now, Serge worked in various FinTech and IT companies in Barcelona area, Spain, taking roles of Senior Data Engineer, Data and SW Architect, including Team Management and Project Management / CEO. Over those years, he accumulated rich professional skills in the IT areas of data/DB/DWH architecture (SQL / NoSQL), data integration (ETL, pipelines), real-time / live stream data processing, data analysis with R, data monitoring /reporting and Business Intelligence, including web development, SW development methodologies (Agile, SCRUM) and Project Management. In terms of IT technology stacks, he worked with wide range of them: Microsoft SQL Server & Microsoft C# / .NET stacks, Oracle SQL Server, Informatica Cloud ETL, SalesForce CRM, open web stacks with LAMP (Linux, Apache HTTP Server, MySQL/MariaDB, PHP) and MEAN (MongoDB, Ember, Angular, Node.js), as well as Android mobile SW development and Big Data processing with Hadoop / Map-Reduce / Apache Spark & Scala. Among the projects were Serge served as a major contributor in SW architecture area were P2P Lending FinTech where he designed web-based P2P Lending platform from scratch, and his own CamerLender.net start-up projects where he designed and prototyped Mongo+Node.js backend server with Android client App implementing crowdsourcing approach for photo & video exchange social network.
Víctor Fernández-Carbajales
Dr. Víctor Fernández-Carbajales Cañete (M): Head of Computer Vision in TREE, holds a degree in Electronic Engineering from the Autonomic University of Madrid (2004) and Ph. D. in Computer and Telecommunication Engineering from the Autonomic University of Madrid (2018). He has a wide experience in R&D project related to a wide range of technologies, though he is specialized in video-surveillance systems, low-level video processing, semantics and personalization technologies and Internet of Things. As a researcher, he has been involved in several national and international projects, like: Cathedra UAM-Infoglobal (PROFIT FIT-360000-2006-89; image processing algorithms to integrate intelligent video surveillance system in indoor scenarios); SmartPrevent (FP7-606952; detection and prevention of frequent petty crimes with high impact to local communities and citizens in urban scenarios); SAFEROADS (E!-8217; tools for the automation of traffic management, based on the already existing camera infrastructure, with the purpose of improving the current capacities); APRIL (H2020-870142; Robots handling flexible materials in production line environments) and VOJEXT (H2020-952197; Value Of Joint EXperimentation in digital Technologies for manufacturing and construction). As a manager, he was the coordinator of the European projects CogLaboration (FP7-287888), SmartPrevent (FP7-287888) and SAFEROADS (E!-8217), among others. As Technical manager, he was coordinator of the European projects APRIL (H2020-870142) and VOJEXT (H2020-952197).
Aratz Setién
Aratz Setién is a telecommunications engineer specialised in computer vision, data analytics, and medical applications. With more than 13 years of experience in the ICT sector, he has been involved in diverse projects as R&D Engineer and Project Manager, including international (ICT FP7 - Collaborative Project: Embedded Computer Engineering Learning Platform E2LP, H2020 - Integrated personalized care for patients with Advanced Chronic Diseases to improve health and quality of life ADLIFE), regional (VIRUSES - Visually Immersive Researching Unit for Scientific and Educational Scenarios. Patent ES2649789A1) or private funded (eVida©Knee), with diverse publications on the work carried out. Focusing his activity on the research and health sector in the last years, he is specialised in Computer Vision, Medical Imaging, and Machine/Deep Learning technologies with strong knowledge of the ultimate trends and technologies in this area.
