The 14th International Workshop on Information Search,
Integration and Personalization

Data-Driven Decision Making Technologies and Applications

Madrid, Spain (postponed, new dates soon)                 

ANNOUNCEMENT March 22 2020 | Due to the overall situation across the globe caused by the coronavirus outbreak, ISIP2020 needs to be postponed. New dates to be released soon.

Background and Motivation

The 14th International Workshop on Information Search, Integration, and Personalization started as a series of workshops in 2003, and its first edition was placed under the auspices of the French embassy in Tokyo. The event has grown during 13 years, creating synergies between participant researchers and delivering several collaborations, joint publications, joint student supervisions and research projects.

The workshop series has now reached a mature state with an increasing number of researchers participating every year. In its 14th edition, with a special focus on Data-Driven Decision Making Technologies and Applications, the workshop will be hosted by the Information Processing and Telecommunications Center of the Universidad Politécnica de Madrid in Spain.

The workshop papers will be published in a proceedings book with ISBN. In a post-workshop call, a number of selected contributions are invited to be extended and published in the Springer series “Communications in Computer and Information Science” (CCIS), following a separated reviewing process.
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Workshop objectives and topics

In its 2020 edition, ISIP Workshop’s Special Topic is “Data-Driven Decision-Making Technologies and Applications”. The Special Topic includes research outcomes and experiences in infrastructures, analysis strategies and algorithms, workflows, visualization and interaction technologies that facilitates identifying alternatives, modeling beliefs and preferences, assessing resolutions and making choices based on data. Use case and applications for industries such as telecommunications, healthcare, transportation, manufacturing art and media production or fintech are also welcomed.

Nowadays the production of digital contents, data and services has reached a speed never experienced before. Large amounts of content are already on the Web, waiting for being reused both for personal or professional purposes. These contents, including multimedia documents, application tools, and services are being accumulated on the Web, in cloud systems, and in local and global data structures. There is thus a need for new theories and technologies for advanced information search, integration through interoperation, and personalization of digital services. Additionally, in science and technology, with progressively sophisticated research going on, there is a growing need for interdisciplinary availability, distribution and exchange of the latest research results, in organic forms, including not only research papers and multimedia documents, but also various tools developed for measurement, analysis, inference, design, planning, simulation, interaction and production as well as the related large data sets. And similar needs are also rising for the interdisciplinary and international availability, distribution and exchange of ideas and works among artists, musicians, designers, architects, directors, and producers.

In this context, ISIP offers a forum for presenting original work and stimulating discussions and exchanges of ideas around information search, integration of information sources and personalization of information experiences. Topics of interest include but are not limited to:

  • Information search in large data sets (databases, digital libraries, data warehouses)
  • Comparison of different information search technologies, approaches, and algorithms
  • Novel approaches to information search
  • Personalized information retrieval and personalized web search
  • Data Quality
  • Federation of Smart Objects
  • (Social) Cyber-Physical Systems
  • (Big) Data Analytics for personalization
  • Data Mining
  • Integration of Web-services, Knowledge bases, Digital libraries
  • Machine learning and AI for information-related applications
  • Visual and sensory information processing and analysis
  • Ontology-based Data Access, Integration, and Management
  • Provenance Tracking in the Context of Data Integration
  • Privacy in the context of data integration, web data privacy
  • Ontology Alignment, Instance Matching, Ontology Mapping

Submit your papers before TBD, 2020. Check important dates, submission guidelines and registration procedure.

  • Submission Guidelines

    All submissions will be handled electronically via the workshop’s EasyChair Website. Authors are asked to submit a two pages extended abstract following the format here. Papers will be peer-reviewed by the TPC; accepted papers for the workshop will be published in the Workshop Proceedings (with ISBN).

    Selected papers will be invited to submit a full paper for the workshop post-proceedings, to be be published in the Springer series “Communications in Computer and Information Science” (CCIS). Information for Authors of Springer Proceedings can be found here.

  • Important dates

    Postponed, new date soon, 2020: Workshop papers deadline

    Postponed, new date soon, 2020: Notification

    Postponed, new date soon, 2020: Camera-ready workshop papers

    Postponed, new date soon: Workshop dates

  • Registration

    Fee for conference attendance will be 150€ up to (new date soon), 2020.

    Early bird registration (new date soon, 2020): 150€

    Late registration: 200€

    The registration link will be soon included.

    Some scholarships will be provided for doctoral students. Authors of accepted papers must pay the full-fee.


General Chairs

  • José R. Casar

    Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, Spain.

    Nicolas Spyratos

    Paris-Sud University, France.

    Yuzuru Tanaka

    Hokkaido University, Japan.

Programme Co-Chairs

  • Dominique Laurent

    Université de Cergy-Pontoise, France

    Ana M. Bernardos

    IPTC, U. Politécnica de Madrid, Spain.

Local Organizing Committee

  • Giorgos Kontaxakis (Chair)
    Rubén Sansegundo
    Luis Hernández

    Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, Spain.

Programme Committee

Federico Álvarez, IPTC-UPM, Spain
Manuel Álvarez-Campana, IPTC-UPM, Spain
José Luis Blanco, IPTC-UPM, Spain
Stephane Bressan, National University of Singapore, Singapore
Julián Cabrera, IPTC-UPM, Spain
Richard Chbeir, Pau University, France
Yingying Chen, Zhejiang Institute of Economics and Trade, China
Yeo-Wei Choong, HELP College of Art and Technology, Malaysia
Panos Constantopoulos, Athens University of Economics and Business, Greece
Laurent D’Orazio, Université Rennes, CNRS, France
Michel De Rougemont, University Paris II, France
Antonio Fernández Anta, IMDEA Networks, Spain
Giorgos Flouris, Univ. Pau & Pays Adour, France
Sol Garrido Maíz, SAP, Spain
Bill Grosky, University of Michigan-Dearborn, USA
Gabriel Huecas, IPTC-UPM, Spain
Haridimos Kondylakis, Institute of Computer Science, FORTH, Greece
Dimitri Kotzinos, University of Cergy-Pontoise, France
Anne Laurent, University of Montpellier, France
Maurizio Lenzerini, Sapienza University of Rome, Italy
Marisa López-Vallejo, IPTC-UPM, Spain
Carlo Meghini, CNR ISTI, France
Jean-Marc Petit, Université de Lyon, INSA Lyon, France
Xenia Naidenova, Military Medical Academy, Saint Petersburg, Russia
Dimitris Plexousakis, Institute of Computer Science, FORTH, Greece
Carlos Rebate, Misait, Spain
Somchoke Ruengittinun, Kasetsart University, Bangkok, Thailand
Domenico Saccà, University of Calabria, Italy
Constantine Stephanidis, Institute of Computer Science, FORTH, Greece
Costantino Thanos, ISTI CNR Pisa, Italy
Dimitrios Tzovaras, Informatics and Telematics Institute / Centre for Research and Technology Hellas, Greece
Juan C. Yelmo, IPTC-UPM, Spain
Naoki Yoshida, The University of Tokyo, Japan
Masaharu Yoshioka, Hokkaido University, Japan
Pedro José Zufiria, IPTC-UPM, Spain


Keynote 1: Translating images to cardiovascular risk prediction

by Charalambos Antoniades
MD PhD FRCP FESC, Professor of Cardiovascular Medicine University of Oxford
Deputy Head, Division of Cardiovascular Medicine University of Oxford | Director of the Oxford Academic Cardiovascular CT programme& Core Lab | Consultant Cardiologist Oxford University Hospitals NHS Foundation Trust | Chair-Elect, British Atherosclerosis Society

Summary: Artificial intelligence is now used in medical imaging, aiding image capture, segmentation, analysis and interpretation. Recent advancements in the analytical methods used for these tasks (e.g. deep learning/machine learning, radiomic analysis and others) allow us to analyse and interpret images in an unprecedented way, bringing us for the first time in front of true personalised medicine. We have recently developed novel radiotranscriptomic approaches to translate the radiomic profile of computed tomography images into biologically meaningful information. A technology developed using this approach, the Fat Attenuation Indexing, was shown to enable non-invasive detection of inflammation in the coronary arteries, and it has a striking prognostic value in cardiovascular medicine, by identifying he “vulnerable” patient and guiding deployment of therapeutic strategies in preventive medicine.

Bio: Charis is a Professor of Cardiovascular Medicine at the University of Oxford, Deputy Head of the Division of Cardiovascular Medicine. He is a Consultant Cardiologist in Oxford University Hospitals running a Hypertension service of the Trust and Directs the Oxford Academic Cardiovascular CT programme and image analysis core lab. His research is focused on translational imaging in cardiovascular diseases, and applies a wide range of artificial intelligence methods to discover new imaging biomarkers. He has raised >£30m for his research programme over the last 10 years, and he has published >300 papers in high impact journals like the Lancet, Science Translational Medicine, Circulation, JACC and others). In 2016 he received the outstanding achievement award of the European Society of Cardiology and in 2018 he received the “Fellow of the Year” award of the British Heart Foundation. He is Deputy Editor of Cardiovascular Research, editor of British Journal of Pharmacology and board member of various societies. He is Chair-Elect of the British Atherosclerosis Society, starting his tem in Jan 2021. He is also founder and Chief Scientific Officer of Caristo Diagnostics, a University of Oxford spinout company.

Keynote 2: Big Data Assimilation: A New Science for Weather Prediction and Beyond

by Takemasa Miyoshi
PhD, Team Leader, Data Assimilation Research Team, RIKEN Center for Computational Science | Chief Scientist, Prediction Science Laboratory, RIKEN Center for Pioneering Research | Deputy Director, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) | Affiliate Professor, Graduate School of Science, Kyoto University | Visiting Principal Scientist, Application Laboratory, Japan Agency for Marine-earth Science and Technology (JAMSTEC) | Visiting Professor, Department of Atmospheric and Oceanic Science, University of Maryland, USA | Research Counselor, National Meteorological Service, Argentina

Summary: Computer model simulation would be a powerful tool for science-driven, objective decision making by testing various potential decisions in simulated worlds, but this requires reliable simulations to represent the real world accurately. Data Assimilation was introduced in numerical weather prediction to combine computer model simulations with real-world observations, using dynamical systems theory and statistical mathematics. Computing, remote sensing, and information/communication technologies are all advancing rapidly, and Data Assimilation is becoming more popular as a means to perform cyber-physical fusion in other science and technology fields. At RIKEN, the Japan’s flagship research institute for all sciences, we pioneered future possibilities of numerical weather prediction by taking advantage of the powerful K computer, and Big Data from advanced sensing technologies such as the Phased Array Weather Radar and the Himawari-8 geostationary satellite. We thus developed innovative “Big Data Assimilation” (BDA) technology, and made possible a 30-second-update of severe weather prediction at 100-m resolution, two orders of magnitude higher and faster than what is currently used in operational numerical weather prediction centers. I will talk about the exciting results of our BDA efforts in numerical weather prediction, and give a perspective towards Data Assimilation becoming a new science hub – from severe weather forecasting to many other new important applications. This will play an essential role in using simulations for scientific decision making.

Bio: Dr. Takemasa Miyoshi received his B.S. degree (2000) in theoretical physics on nonlinear dynamics from the Kyoto University, and M.S. (2004) and Ph.D. (2005) degrees in meteorology on ensemble data assimilation from the University of Maryland (UMD). Dr. Takemasa Miyoshi started his professional career as a civil servant at the Japanese Meteorological Agency (JMA) in 2000. He was a tenure-track Assistant Professor at University of Maryland in 2011. Since 2012, Dr. Miyoshi has been leading the Data Assimilation Research Team in RIKEN Center for Computational Science (R-CCS), working towards his goals of advancing the science of data assimilation as well as a deep commitment to education. Dr. Miyoshi’s scientific achievements include more than 110 peer-reviewed publications and more than 130 invited conference presentations including the Core Science Keynote at the American Meteorological Society Annual Meeting (2015). Dr. Miyoshi has been recognized by several prestigious awards such as the Yamamoto-Syono Award by the Meteorological Society of Japan (2008), the Young Scientists' Prize by the Minister of Education, Culture, Sports, Science and Technology (2014), the Japan Geosciences Union Nishida Prize (2015), the Meteorological Society of Japan Award (2016) - the highest award of the society, and the Yomiuri Gold Medal Prize (2018).

Keynote 3: Current Frontiers of Machine Learning: myths and realities

Prof. Zazo
by Santiago Zazo
Full Professor at Universidad Politécnica de Madrid | Member of the Information Processing and Telecommunications Center

Summary: This talk provides an introductory overview of the current situation of Machine Learning related topics under the modern framework of Deep Neural Network (DNN) architectures. The common thread of this presentation will review some misleading understanding as myths and the realities behind them. Topics like DNNs as universal solvers; the powerfulness of Deep Generative Models approaching (and excelling) so far only-human abstract aptitudes as painting, writing, composing or playing; new Deep Reinforcement Learning methods providing optimum decision capabilities in dynamic scenarios with full and partial observabilities; and Transfer Learning, considered by many experts as the key element of modern learning, where Deep Neural Networks trained to solve some especific task become also capable of being re-purposed on different tasks, will be covered from intuition to theoretical and practical perspectives. Finally, these discussions will be illustrated under a common scenario where different contributions of research activities at IPTC will show, on the one hand, the state of the art and, on the other hand, those still missing challenges where myths meet reality as distributed intelligence.

Bio: Santiago Zazo is a professor in Signal Processing and Machine learning at the Universidad Politécnica de Madrid and researcher at the Information Processing and Telecommunications Center at the same University. He is author and coauthor of about 50 papers in highly ranked journals and more than 150 international conference papers. In the past, his main research activities were related to signal processing in communications like OFDM, CDMA and MIMO but about 10 years ago he initiated a new motivating research area in distributed processing and deep learning. This research line covers the Multiagent / Game Theory topic dealing with random variables estimation, random fields, decision making, dynamic systems, optimum control theory... that can be formalized as a multiagent processing solving the paradigm of distributed processing. Recently, this line has been complemented with deep learning techniques, specially those based on reinforcement, permitting us to obtain affordable solutions in problems with high complexity or dimensionality, under the framework of deep neural networks. Some examples of these applications are optimal attack and defence mechanisms in communication networks, autonomous navigation in terrestrial vehicles or aerial and submarine drones, or finding optimum therapies against certain deseases as cancer. He currently combines this research with teaching responsibilities in machine learning related courses like distributed optimization and reinforcement learning.


The conference will be held in the premises of ETSI Telecomunicación - Information Processing and Telecommunications Center in Madrid, Spain. The facilities of ETSIT-IPTC are located at Ciudad Universitaria Campus in the city of Madrid (Av. Complutense 30).

For information about Madrid and Spain you can visit these websites:
Official Tourism Madrid:
Day trips:


Some hotels with reasonable access to the Workshop venue:
Hotel Jardines de Sabatini (10% discount, include reference ISIP2020 in your booking)
Hotel Exe Moncloa
Hotel Indigo
Courtyard by Marriott Madrid Princesa
Sercotel Gran Hotel Conde Duque
Leonardo Hotel Madrid City Center
VP Jardín Metropolitano
Hotel RIU Plaza España
Exe Suites 33

In case you need any help with accomodation, visas or travel issues, please contact us.


    By Metro: Take Line 6 (the grey one) to ‘Ciudad Universitaria’ station. Once there, there is a 13' walk to the ETSIT. But you can also take a bus (Line 82, U or G), which stops just at the metro exit and goes straight to the ETSIT entrance.

    By bus: a) Line F: Departs from Cuatro Caminos. b) Line U: Departs from metro station of ‘Ciudad Universitaria’ (Line 6). c) Lines 82 y G: Depart from the proximity of ‘Moncloa’ metro station (Line 6 and 3).

    From the Airport: The airport is composed by four terminals, all of them accessible by Metro ('Aeropuerto T4' and 'Aeropuerto T1-T2-T3' stations). Line 8 (pink colored) will take you to the heart of the city ('Nuevos Ministerios' Station, Line 6) in less than 25 minutes. In ‘Nuevos Ministerios’ you should change to Line 6 to reach ‘Ciudad Universitaria’. The trip costs 4,5 euros (single ticket + airport supplement), but you can also buy a 10 trip ticket (12,20 euros, you can use it in buses or metro rides) and pay the airport extra fare (3 euros) separately. All the information about fares and visitor cards is available here In case you choose to take a taxi, 30 € is the flat fare to any city center destination (within M-30 ring).

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