- with Alejandro de la Concha on multivariate signals and graph signals segmentation (supervision of MSc thesis).
- with Anthea Mérida on ensemble methods (supervision of MSc thesis).
- with Ioannis Bargiotas and Myrto Limnios on statistical applications for biomedical engineering (collaboration, 2018-…).
- with Mathilde Fekom on seeing the diffusion control in an online learning framework (supervision of PhD thesis, 2017-…).
- with Batiste Le Bars on detection problems on networks (supervision of PhD thesis, 2017-…).
- collaboration with Sergio Pegnier on Transfer Learning problems.
- collaboration with Kevin Scaman (Microsoft Research, INRIA Paris-Saclay, France). We work on network diffusion models with application on large social graphs.
(Co-)supervision at ENS Paris-Saclay:
- with Amel Addala on a problem related to simulations of harmonic perturbations in EDF’s power network using Machine Learning. (supervision of MSc thesis, 2019).
- with Rafael Gromit and Blandine Galiay on sequential selection processes over graphs (Licence thesis, 2019).
- with Vincent Laheurte and Ferdinand Campos will work on statistical homogeneity testing (Licence thesis, 2019).
- with Antoine Prouff and Antoine Bordas on greedy dynamic resource allocationstrategies (L3 internship, 2018).
- with Emile Ciuperca and Mathieu Helfter on graph signals and graph kernels (L3 internship, 2018).
- with Thales Loiola Raveli will be working on the modeling of transportation traffic (intern from ENSTA Paritech, 2018).
- with Marin Scalbert on modeling and mining from railway traffic data (BSc internship, 2017).
- with Matteo Neri on studying the diffusive properties of perturbations in transportation networks (supervision of MSc thesis, 2017).
- with Mathilde Fekom on seeing the diffusion control in an online learning framework (supervision of MSc thesis, 2017).
- with Otávio Leite Bastos de Nazaré on financial networks and default propagation (intern from ENSTA Paritech, 2017).
- with Luca Corinzia, on spectral methods for suppressing Information Cascades, (MSc thesis, 2016).
- with Stefano Sarao, on extensions of SIS model and LRIE strategy for social diffusion control, (MSc thesis, 2016).
- with Xavier Lioneton, on clustering twitter propagation data, (MSc thesis, 2016).
- with Suzanne Schlich and Julie Tourniaire, on feature engineering and clustering of url progation profiles on twitter (Licence thesis, 2015).
- with Pierre Abgrall and Jules Baleyte, on systemic risk analysis in financial networks (Licence thesis, 2015).
- with Mateo Sesia, on network inference by observing SIS processes (MSc thesis, 2014).
- with Patrick Saux and David Marchand, on network inference (Licence thesis, 2014).
(Co-)supervision at the CS Department at the University of Ioannina:
- “Document Classification using Advanced Representations”, Eirini Niaka, (Undergraduate thesis, 2011-2012).
- “Knowledge extraction from text collections using semantic information”, Nasos Tsamis (Undergraduate thesis, 2010-2011).
- “Event detection in text streams”, Panagiotis Zagorisios (Undergraduate thesis, 2012-2013 – MSc thesis, 2014-2015). This work led to the paper: “Improving Text Stream Clustering using Term Burstiness and Co-burstiness”, A. Kalogeratos, P. Zagorisios, and A. Likas, SETN, 2016. [pdf][slides][bib]
- “Information system for the rapid automatic identification of natural products in crude extracts based on NMR data“, Katerina Nikolaidi (Undergraduate thesis, 2011-2012). Ack: In collaboration with Lecturer Α. Tzakos and postdoctoral researcher V. Kontogianni, Department of Chemistry University of Ioannina.
- Teaching of the module AI/ML for network modeling – part of the scientific training of multidisciplinary students on AI (Spring 2020).
- TA for the Optimization course for the ENS Paris-Saclay M1 students of the Maths Department (given by Alain Trouvé) (Spring 2019, Spring 2020).
- TA for the Statistics course of the Agregation Preparatoire (Spring 2019).
- TA for the Introduction to CS Tools courses for the ENS Paris-Saclay L3 students of the Maths Department (Fall 2018).
- TD for the Hyper Performance Computing Master course (M2): Data and Machine Learning (given by Nicolas Vayatis) (Fall 2018, Fall 2019).
- TA for the MVA Master course (M2): Unsupervised Learning: From Big Data to low-dimensional representations (given by Rene Vidal) (Fall 2017).