Pol Puigdemont Plana (2025)
Applied Machine Learning in Discrete or Constrained domains, Combinatorial Optimization, Graphs and Scheduling
Aidan Li (2024)
Causal inference Probabilistic machine learning Graph neural networks Cognitive science
Kaito Fujii (2024)
Submodular Optimization, Online Learning, Game Theory
Tian Xu (visiting PhD student – 2024)
Imitation Learning Theory, Reinforcement Learning.
Yihang Chen (2024)
Large Language Models: Safety in LLMs Applied Probability: Stochastic Control, Optimal Transport, Generative Flow Networks AutoML: Pruning, Neural Architecture Search
Basile Lewandowski (2024)
Federated Learning Optimization Distributed Computing
Artem Agafonov (visiting PhD student 2023)
Convex optimization Stochastic optimization High-order optimization Machine learning
Anh Duc Nguyen (2023)
Convex Optimization Online Learning
Wanyun Xie (2023)
Distributed machine learning, Optimization, Communication Systems
Mohammadamin Sharifi (2022)
Machine learning, Optimization
Rayan Harfouche (2022)
Statistical Physics, Optimization, Information theory
Yongtao Wu (2022)
Deep learning, Over-parametrized models
Artem Zholus (2022)
Machine Learning
Hlib Tsyntseus (2021)
Mathematical optimization, Statistics and Applications
Prateek Varshney (2021)
Applied deep learning, Optimization techniques, Casual Inference, Computational Neuroscience, Language Representation, Statistical Sampling Techniques
Daria Kotova (2021)
Machine Learning, Gaussian Processes
Jonathan Sauder (2020)
Machine Learning, Compressive Sensing
Zhaodong Sun (2020)
Generative model, Deep learning, Inverse problem
Cheng Shi (2020)
Statistical Physics and Electronic Information, Spin Glass Theory and Information Theory.
Pedro Abranches (2020)
Bayesian optimization Machine Learning Causality Neuroscience
Dadi Leelo Tadesse (2020)
Research Interests: Optimization Algorithms and Randomness.
Bora Dogan (2019)
nternship project topic: Reinforcement Learning on Networks
Pai-An Wang (2019)
Internship project topic:
Clément Lalanne (2018)
Internship project topic: Storage-optimal continuous optimization
Mehmet Fatih Sahin (2018)
Internship project topic: Projection-Free Adaptive Convex Optimization
Thomas Sanchez (2018)
Internship project topic: Learning-based Compressive Sensing for dynamic MRI
Renbo Zhao (2017)
Internship project topic: Stochastic three-operator splitting method via variance reduction.
Junyao Zhao (2017)
Internship project topic: Robust submodular maximization, submodularity in non-convex optimization.
Alban Pierre (2016)
Internship project topic: Molecular energy prediction using coulomb, wavelet and scattering representations. Spectral optimizers for gradient descent.
Behrooz Azarkharlili (2016)
Internship project topic: Bayesian Optimization
Yu-Chun Kao (2016)
Internship project topic: Alternating Minimisation
Gergery Odor (2015)
Internship project topic: Theoretical guarantees for optimization algorithms Quantum tomography
Nissim Zerbib (2015)
Internship project topic: Theoretical guarantees for M-estimators in high dimension Matrix completion
Siddhartha Satpathi (2015 & 2013)
Internship project topic: Group Sparse Models and Submodular function theory.
Vipul Gupta (2015)
Internship project topic: Efficient sampling and compression of ensembles of intracortical EEG signals
Amirhossein Hadavi (2014)
Internship project topic: Graphical modeling of brain connections and random matrix theory for applications in linear inverse problems.
Rajshekar Das (2014)
Internship project topic: Active sampling for digital confocal microscopy.
Prateek Vashishtha (2014)
Internship project topic: Structured sparsity with shearlets as sparsifying basis for Compressive Sensing
Roozbeh Hasheminezhad (2014)
Internship project topic: Convex model-based signal recovery via expander matrices.
Ehsan Abbasi (2013)
Internship project topic: Matrix completion.
Rabeeh Karimi Mahabadi (2013)
Internship project topic: Sparse Covariance Selection and Phase-retrieval.
Sajal Jain (2012)
Internship project topic: Analysis of structured sparse signals using Linear Programming.
Hemant Tyagi (2012)
Internship project topic: Low dimensional models for high dimensional data.
Nirav Bhan (2012)
Internship project topic: Discrete Structured Sparsity Models and Dynamic Programming.
Mohammad Hossein Shafinia (2011)
Internship project topic: Synthesis and atomic norm formulation equivalence for sparse signal recovery.
Shayan Dashmiz (2011)
Internship project topic: Sparse Data Analysis.