Machine Learning and Optimization Group at RIST

Romanian Institute of Science and Technology - RIST
Str. Virgil Fulicea nr. 17, 400022 Cluj-Napoca, Romania


# Research Interests


  • Deep Learning
  • Machine Learning
  • Information Geometry
  • Riemannian and Stochastic Optimization
  • Reinforcement Learning

  • # Members


    Luigi Malagò group leader lastname-without-any-accent[AT]rist[DOT]ro
    Dimitri Marinelli postdoc researcher lastname[AT]rist[DOT]ro
    Septimia Sarbu postdoc researcher lastname[AT]rist[DOT]ro
    Volpi Riccardo postdoc researcher lastname[AT]rist[DOT]ro
    Titus Nicolae research assistant lastname[AT]rist[DOT]ro
    Alexandra Pește research assistant lastname-without-any-accent[AT]rist[DOT]ro
    Raluca Drozan project assistant firstname[DOT]lastname[AT]rist[DOT]ro

    # News


  • [19-05-2017] Prof. Giovanni Pistone, from Collegio Carlo Alberto, Italy, will visit our group from 8 to 14 May 2017.
  • [18-05-2017] PhD Deepika Kumari, from Guru Gobind Singh Indraprastha University, India, will visit our group from 3 to 7 July 2017. She will have a public seminar on the 04.07.2017 entitled "Geometry of Biharmonic Submanifolds".
  • [16-05-2017] Alexandra and Titus will participate to the Data Science Summer School 2017, at École Polytechnique, from 28 August to 1 September 2017. Alexandra will present a poster on variational autocoders and Titus on geometric methods to train neural networks.

  • # Grants


    The Machine Learning and Optimization Group is supported by the POC 2014-2020 grant - ANCSI Competitiveness Operational Programme 2014-2020. Project name: DeepRiemann - Riemannian Optimization Methods for Deep Learning (2016-20) (~1.9M EUR)

    The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group.

    # Open Positions

    Postdoc positions on Machine Learning, Deep Learning, Optimization, and Information Geometry


  • 2 postdoc positions on Deep Learning and Machine Learning, starting spring 2017
  • 1 postdoc positions on Machine Learning, Optimization, Deep Learning and Information Geometry, starting spring 2017
  • 1 open position for research assistant / PhD student on Deep Learning and Machine Learning, starting fall 2017
  • The lab has open positions for Summer Internships for Universitatea Babeș-Bolyai (UBB) and Universitatea Tehnica din Cluj-Napoca (TU) students, starting from July 2017

  • # How to reach us


    The office is located in the city center of Cluj, only 9km away from the Cluj International Airport (Aeroportul International Avram Iancu Cluj). The simplest way to reach our office from the airport is to take a Taxi (around 25 lei). Alternatively, you can take the buses n. 5 or 8 in front of the airport, both stop at less than 10 minutes by walk from the office (ticket 2 lei). More information about the location of the bus stops can be found using Google Maps.






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    (Last update 5 May 2017)