Curriculum vitae

Atif Jamal

Full Professor
Phone : 01 44 05 42 30
Office : P620


Jamal Atif is Professor at the University of Paris-Dauphine, Project Manager "Data Science and Artificial Intelligence" at the Institute of Information Sciences and their Interactions (INS2I) of the CNRS, Deputy Scientific Director of the 3IA PRAIRIE, Head of the MILES team/project at LAMSADE (UMR CNRS-University of Paris-Dauphine), Co-Porter of the Transverse Artificial Intelligence Program at the PSL University, and Director of the Dauphine Numérique program. His current research interests focus on the foundations of responsible artificial intelligence: preservation of privacy in machine learning, robustness of deep learning algorithms to malicious attacks, causality, explicability. Before joining Dauphine-PSL, Jamal Atif was a member of the TAO team (CNRS, Inria, Université Paris-Sud) at LRI from 2010 to 2014, of the ESPACE team at IRD from 2006 to 2010, of LTCI (CNRS-Télécom ParisTech) from 2004 to 2006, and of LIMSI (UPR CNRS) from 2000 to 2004. He is the author of more than 100 scientific publications in the field of AI, has co-supervised or supervised about fifteen PhD students, and won two North American Society of Radiology awards for his thesis work.

Latest publications


Pinot R., Meunier L., Yger F., Gouy-Pailler C., Chevaleyre Y., Atif J. (2022), On the robustness of randomized classifiers to adversarial examples, Machine Learning, vol. 111, n°9, p. 3425–3457

Labernia F., Yger F., Mayag B., Atif J. (2018), Query-based learning of acyclic conditional preference networks from contradictory preferences, EURO Journal on Decision Processes, vol. 6, n°1-2, p. 39-59

Aiguier M., Atif J., Bloch I., Pino Pérez R. (2018), Explanatory relations in arbitrary logics based on satisfaction systems, cutting and retraction, International Journal of Approximate Reasoning, vol. 102, p. 1-20

Aiguier M., Atif J., Bloch I., Hudelot C. (2018), Belief revision, minimal change and relaxation: A general framework based on satisfaction systems, and applications to description logics, Artificial Intelligence, vol. 256, p. 160-180

Isaac Y., Barthélemy Q., Gouy-Pailler C., Sebag M., Atif J. (2017), Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations, Signal Processing, vol. 130, p. 389-402

Atif J., Bloch I., Hudelot C. (2016), Some relationships between fuzzy sets, mathematical morphology, rough sets, F-transforms, and formal concept analysis, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 24, n°S2, p. 1-32

Bloch I., Atif J. (2016), Defining and computing Hausdorff distances between distributions on the real line and on the circle: link between optimal transport and morphological dilations, Mathematical Morphology. Theory and Applications, vol. 1, n°1, p. 79-99

Bloch I., Atif J. (2015), Deux approches pour la comparaison de relations spatiales floues : transport optimal et morphologie mathématique, Revue d'intelligence artificielle (RIA), vol. 29, n°5, p. 595-619

Linguet L., Atif J. (2015), Estimating surface solar irradiance from goes satellite with particle filter model and joint probability distribution, Canadian Journal of Remote Sensing, vol. 41, n°2, p. 71-85

Chapitres d'ouvrage

Linguet L., Atif J. (2016), A Markov Chain Monte Carlo-based Particle Filter Approach for Spatiotemporal Modelling of an Environmental Process, in N. Janardhana Raju, Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment: Challenges, Processes and Strategies Springer, p. 617-621

Communications avec actes

Meunier L., Ettedgui R., Pinot R., Chevaleyre Y., Atif J. (2022), Towards Consistency in Adversarial Classification, in S. Koyejo ; S. Mohamed ; A. Agarwal ; D. Belgrave ; K. Cho ; A. Oh, Neural Information Processing Systems Foundation, Inc.

Saltiel D., Benhamou É., Laraki R., Atif J. (2021), Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA), in , elsevier, Berlin Heidelberg, Springer International Publishing, 1-15 p.

Benhamou É., Saltiel D., Ohana J-J., Atif J. (2021), House allocation with randomly generated preference lists, in , Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers, 10050 - 10057 p.

DO V., Atif J., Lang J., Usunier N. (2021), Online Selection of Diverse Committees, in Zhi-Hua Zhou, International Joint Conferences on Artificial Intelligence Organization (IJCAI), 154-160 p.

Benhamou É., Saltiel D., Ohana J-J., Atif J., Laraki R. (2020), Deep Reinforcement Learning (DRL) for portfolio allocatio, in Dong, Yuxiao; Ifrim, Georgiana; Mladenić, Dunja, Springer, 527-531 p.

Yamane I., Yger F., Atif J., Sugiyama M. (2018), Uplift Modeling from Separate Labels, in S. Bengio; H. Wallach; H. Larochelle; K. Grauman; N. Cesa-Bianchi; R. Garnett, Advances in Neural Information Processing Systems 31 (NIPS 2018), Neural Information Processing Systems Foundation, Inc., 9927--9937 p.

Pinot R., Morvan A., Yger F., Gouy-Pailler C., Atif J. (2018), Graph-based Clustering under Differential Privacy, in Amir Globerson; Ricardo Silva, Uncertainty in Artificial Intelligence (UAI) - Proceedings of the Thirty-Fourth Conference (2018), August 6-10, 2018, Monterey, California, USA, AUAI Press, 329-338 p.

Araújo A., Negrevergne B., Chevaleyre Y., Atif J. (2018), Training Compact Deep Learning Models for Video Classification Using Circulant Matrices, in Leal-Taixé Laura; Roth Stefan, Computer Vision – ECCV 2018 Workshops Munich, Germany, September 8-14, 2018, Proceedings, Part IV, Berlin Heidelberg, Springer, 271-286 p.

Evain T., Ripoche X., Atif J., Bloch I. (2017), Semi-automatic teeth segmentation in cone-beam computed tomography by graph-cut with statistical shape priors, in Olivier Salvado, Gary Egan, 14th IEEE International Symposium on Biomedical Imaging (ISBI), New York, IEEE - Institute of Electrical and Electronics Engineers, 1197-1200 p.

Bojarski M., Choromanska A., Choromanski K., Fagan F., Gouy-Pailler C., Morvan A., Sakr N., Sarlos T., Atif J. (2017), Structured adaptive and random spinners for fast machine learning computations, in Aarti Singh, Jerry Zhu, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), volume 54, IEEE - Institute of Electrical and Electronics Engineers, 1020-1029 p.

Labernia F., Zanuttini B., Mayag B., Yger F., Atif J. (2017), Online learning of acyclic conditional preference networks from noisy data, in George Karypis, Lucio Miele, Proceedings of the IEEE International Conference on Data Mining (ICDM 2017), Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers

Yang Y., De Aldama R., Atif J., Bloch I. (2016), Efficient Semantic Tableau Generation for Abduction in Propositional Logic, in Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen, ECAI 16, IOS Press, 1756-1757 p.

Labernia F., Yger F., Mayag B., Atif J. (2016), Query-based learning of acyclic conditional preference networks from noisy data, in Róbert Busa-Fekete, Eyke Hüllermeier, Vincent Mousseau, Karlson Pfannschmidt, From Multiple Criteria Decision Aid to Preference Learning : Proceedings of the DA2PL'2016 EURO Mini Conference, Paderborn, Paderborn University, 6 p.

Bloch I., Atif J. (2015), Hausdorff distances between distributions using optimal transport and mathematical morphology, in Jón Atli Benediktsson, Jocelyn Chanussot, Laurent Najman, Hugues Talbot, 12th International Symposium on Mathematical Morphology, Springer, 522-534 p.

Yang Y., Atif J., Bloch I. (2015), Abductive reasoning using tableau methods for high-level image interpretation, in Steffen Hölldobler, Markus Krötzsch, Rafael Peñaloza, Sebastian Rudolph, KI 2015: Advances in Artificial Intelligence: 38th Annual German Conference on AI, Berlin Heidelberg, Springer, 356-365 p.

Evain T., Ripoche X., Atif J., Bloch I. (2015), Fuzzy along spatial relation in 3D. Application to anatomical structures in maxillofacial CBCT, in Vittorio Murino, Enrico Puppo, 18th International Conference on Image Analysis and Processing (ICIAP), Springer, 271-281 p.

Communications sans actes

Kirat T., Virginie DO V., Atif J., Tambou O., Tsoukiàs A., Louvaris A. (2021), Fairness as a challenge for computer science and law. Introductory topic, International Workshop Which paths to achieve fairness in algorithmic decisions?, Paris, France

Araújo A., Negrevergne B., Chevaleyre Y., Atif J. (2021), On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory, 35th AAAI Conference on Artificial Intelligence, vancouver, Canada

Pinot R., Ettedgui R., Rizk G., Chevaleyre Y., Atif J. (2020), Randomization matters How to defend against strong adversarial attacks, Thirty-seventh International Conference on Machine Learning (ICML 2020), Vienna, Autriche

Beji C., Benhamou É., Bon M., Yger F., Atif J. (2020), Estimating Individual Treatment Effects throughCausal Populations Identification, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2020), Brugges, Belgique

Pinot R., Yger F., Gouy-Pailler C., Atif J. (2019), A unified view on differential privacy and robustness to adversarial examples, Workshop on Machine Learning for CyberSecurity at ECMLPKDD 2019, Wurzburg, Allemagne

Prépublications / Cahiers de recherche

Scetbon M., Meunier L., Atif J., Cuturi M. (2021), Equitable and Optimal Transport with Multiple Agents, Paris, Preprint Lamsade

Meunier L., Scetbon M., Pinot R., Atif J., Chevaleyre Y. (2021), Mixed Nash Equilibria in the Adversarial Examples Game, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Laraki R., Atif J. (2020), BCMA-ES: a conjugate prior Bayesian optimization view, Paris, Preprint Lamsade

Benhamou E., Atif J., Laraki R., Saltiel D. (2020), NGO-GM: Natural Gradient Optimization for Graphical Models, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Ungari S., Mukhopadhyay A., Atif J. (2020), AAMDRL: Augmented Asset Management with Deep Reinforcement Learning, Paris, Preprint Lamsade

Araújo A., Negrevergne B., Chevaleyre Y., Atif J. (2019), On the Expressive Power of Deep Fully Circulant Neural Networks, Paris, Preprint Lamsade

Benhamou É., Atif J., Laraki R. (2019), A short note on the operator norm upper bound for sub-Gaussian tailed random matrices, Paris, Preprint Lamsade, 12 p.

Benhamou É., Atif J., Laraki R., Laraki R. (2018), A new approach to learning in Dynamic Bayesian Networks (DBNs), Paris, Preprint Lamsade, 17 p.

Benhamou É., Atif J., Laraki R. (2018), A discrete version of CMA-ES, Paris, Preprint Lamsade, 13 p.

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