Organisatieprofiel

Introductie / missie

The chair studies data mining (DM) techniques and knowledge discovery approaches that are at the core of data science. The group is known for its contributions to the areas of predictive analytics, automation of machine learning and networked science, subgroup discovery and exceptional model mining, and similarity computations on complex data. Its research is inspired by theoretical computer science, systems development and real-world applications of (big) data-driven discovery in healthcare, banking, energy, retail, telecom, and education among others.

Over de organisatie

We develop generic approaches and specialized techniques that cover a wide range of descriptive, predictive and prescriptive analytics and work effectively with text, image, transactional, graph and time-series data in a responsible manner. E.g. we use Deep Learning methods to develop models for high dimensional heterogeneous, unstructured and evolving data and apply this models to areas such as medical imaging, genomics, anomaly detection and sentiment analysis. We further work on methods for analyzing and explaining the model’s decisions and performance and facilitate effective DM with domain expert in the loop.

Success stories

We have created OpenML: an online collaborative platform for studying machine learning techniques. OpenML is used by almost 2,000 researchers, students, and practitioners world-wide, and contains around 20,000 datasets, 3,000 machine learning workflows, and 1,7 million shared experiments. It has won the Dutch Data Prize, as well as backing from Microsoft Research. It is crucial for the development of automated machine learning that is adopted by companies such as Philips.

Further information at OpenML.org 

  • NWO RATE-Analytics (with Tilburg University, Rabobank and Achmea) "Next generation predictive analytics for data-driven banking and insurance".
  • ImpulseKYC-Analytics (with Rabobank) "Know your customer predictive analytics" project aims at developing approaches for effective DM on heterogeneous and evolving data sources with expert-in-the-loop.
  • STW CAPA (with Adversitement and StudyPortals)"Context-aware predictive analytics" advanced the current state of the art in Web analytics.
  • NWO Veni "Detection methods for similarity structures in time-dependent data"develops foundations for advanced time series and trajectories clustering.
  • H2020 SODA (ICT-2016-1; Big Data PPP) "Scalable Oblivious Data Analytics" facilitates secure DM; together with Crypto group we develop practical approaches for DM with multi-party computation.

Vingerafdruk Verdiep u in de onderzoeksgebieden waarop Data Mining actief is. Deze onderwerplabels komen uit het werk van de leden van deze organisatie. Samen vormen ze een unieke vingerafdruk.

  • Netwerk Recente externe samenwerking op landenniveau. Duik in de details door op de stippen te klikken.

    projecten

    Interoperability of Heterogeneous IoT Platforms

    Exarchakos, G., Mocanu, D. C., van der Lee, T. & Exarchakos, G.

    1/01/1631/12/18

    Project: Onderzoek direct

    Onderzoeksoutput

    Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling

    Du, X., Pei, Y., Duivesteijn, W. & Pechenizkiy, M., 2020, (Geaccepteerd/In druk) In : Data Mining and Knowledge Discovery.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    Open Access
  • On local and global graph structure mining

    Pei, Y., 5 feb 2020, Eindhoven: Technische Universiteit Eindhoven. 198 blz.

    Onderzoeksoutput: ScriptieDissertatie 1 (Onderzoek TU/e / Promotie TU/e)

    Open Access
    Bestand

    Pedestrian orientation dynamics from high-fidelity measurements

    Willems, J., Corbetta, A., Menkovski, V. & Toschi, F., 14 jan 2020, In : arXiv. 15 blz., 2001.04646.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademic

    Open Access
    Bestand
  • Prijzen

    Third Prize - National Olympiad in Informatics

    Decebal C. Mocanu (Ontvanger), 1997

    Prijs: AndersDiscipline gerelateerdWetenschappelijk

    Activiteiten

    • 3 Genodigd spreker
    • 1 Keynote spreker
    • 1 Bezoek externe academische instelling

    Machine Learning, better, together.

    Joaquin Vanschoren (Spreker)
    8 dec 2018

    Activiteit: Types gesprekken of presentatiesGenodigd sprekerWetenschappelijk

    Tutorial on Automatic Machine Learning

    Frank Hutter (Spreker), Joaquin Vanschoren (Spreker)
    3 dec 2018

    Activiteit: Types gesprekken of presentatiesKeynote sprekerWetenschappelijk

    Democratizing and Automating Machine Learning

    Joaquin Vanschoren (Spreker)
    28 aug 2018

    Activiteit: Types gesprekken of presentatiesGenodigd sprekerWetenschappelijk

    Knipsels

    4. The internet will continue to make life better

    Joaquin Vanschoren

    28/10/19

    1 item van Media-aandacht

    Pers / media: Vakinhoudelijk commentaar

    Data correlation helps recognize pickpockets

    Mykola Pechenizkiy

    12/07/18

    2 items van Media-aandacht

    Pers / media: Vakinhoudelijk commentaar

    Conference Interpretation Today

    Mykola Pechenizkiy

    19/04/18

    1 item van Media-aandacht

    Pers / media: Vakinhoudelijk commentaar

    Scripties/Masterproeven

    A framework for understanding business process remaining time predictions

    Auteur: Verhoef, C., 28 okt 2019

    Begeleider: Pechenizkiy, M. (Afstudeerdocent 1) & Scheepens, R. J. (Afstudeerdocent 2)

    Scriptie/masterproef: Master

    Algorithms for center-based trajectory clustering

    Auteur: van de L'Isle, N., 28 jan 2019

    Begeleider: Buchin, K. (Afstudeerdocent 1) & Driemel, A. (Afstudeerdocent 2)

    Scriptie/masterproef: Master

    Bestand

    An exploration and evaluation of concept based interpretability methods as a measure of representation quality in neural networks

    Auteur: Remmits, Y., 30 sep 2019

    Begeleider: Menkovski, V. (Afstudeerdocent 1) & Stolikj, M. (Externe coach)

    Scriptie/masterproef: Master

    Bestand