# About me

I am a Postdoctoral Researcher at Ecole Polytechnique Federale de Lausanne (EPFL) since November 2020. My research interests lie in machine learning and computer vision, and more precisely in learning (robust) representations and generative modeling.

## News

- January 2023: The following paper has been accepted at
**Transactions on Machine Learning Research (TMLR)**: '*Revisiting adversarial training for the worst-performing class*'. - December 2022: The following paper has been accepted at
**Transactions on Pattern Analysis and Machine Intelligence**: '*Linear Complexity Self-Attention with 3rd Order Polynomials*'.

**best reviewer**at

**NeurIPS 2022**.

**NeurIPS 2022**:

- 'Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)',
- 'Generalization Properties of NAS under Activation and Skip Connection Search',
- 'Sound and Complete Verification of Polynomial Networks',
- 'Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study'.

**best reviewer award (top 10%)**at

**ICML 2022**.

**ECCV 2022**: 'Augmenting Deep Classifiers with Polynomial Neural Networks' and 'MimicME: A Large Scale Diverse 4D Database for Facial Expression Analysis'. More information soon.

**highlighted reviewer award**at

**ICLR 2022**.

**CVPR 2022**: '

*Cluster-guided Image Synthesis with Unconditional Models*'.

**My talk**on polynomial networks at the UCL Centre for Artificial Intelligence has been uploaded online.

**ICLR 2022**: '

*Controlling the Complexity and Lipschitz Constant improves Polynomial Nets*' and '

*The Spectral Bias of Polynomial Neural Networks*'.

**NeurIPS 2021**: 'Conditional Generation Using Polynomial Expansions'.

**best reviewer award (top 10%)**at

**ICML 2021**.

**Proceedings of the IEEE (2021)**: '

*Tensor methods in computer vision and deep learning*'