About me

I am a Staff Applied Research Scientist at Snorkel AI, leveraging generative models for dataset generation & captions in the retail industry context.

Prior to that I was a research scientist at Bosch, where I focus on addressing Open-World problems such as Object Detection and Segmentation within the context of self-driving scenes. Additionally, I specialize in multimodal (Vision-Language) representation learning for lifelong learning

Before joining Bosch, I was a postdoctoral researcher at Mila under the supervision of Joelle Pineau. My research during this period centered on two key streams: developing a theoretical understanding of Catastrophic Forgetting and exploring the application of self-supervised learning in Reinforcement Learning.

I earned my Ph.D. from McGill University where I delved into cutting-edge topics such as Generative Adversarial Networks (GANs), with a specific focus on addressing mode collapse problems. In tandem, I explored the realm of deep reinforcement learning, where I tackled exploration challenges by implementing innovative multimodal policies.

Research Interests

  • Vision-Language
  • LLMs
  • Multimodal Representation Learning
  • Lifelong Learning
  • Reinforcement learning


  • PhD Operation Management (2014-2019) - McGill university
  • MSc Applied Mathematics (2012-2013) - University College London
  • Bsc Mechanical Engineering (2010-2013) - Arts et Metiers ParisTech