David W. Romero

David W. Romero

PhD. Student in Deep Learning

Vrije Universiteit Amsterdam

I am a 3rd year PhD Student at the Vrije Universiteit Amsterdam supervised by Erik Bekkers (UvA), Jakub Tomczak & Mark Hoogendoorn. Currently, I am a Research Intern at Qualcomm AI Research, and previously this year I spent some time at Mitsubishi Electric Research Laboratories (MERL) as a Research Consultant.

My research is focused on data efficiency, computation efficiency and parameter efficiency aspects of Deep Learning models. Currently, I am particularly interested in neural architectures with extensive parameter sharing such as Continuous kernel CNNs, Group equivariant networks and Self-attention networks. Continuous Kernel CNNs are a new family of neural networks with interesting efficiency properties for which I recently received the Qualcomm Innovation Fellowship Europe (2021).

My PhD is part of the Efficient Deep Learning (EDL) project funded by the NWO. I collaborate with Samotics to apply developments resulting from my research in time-series analysis.

In my free time, I like learning about new things (e.g., coffee, wine, carpentry) and doing sports (e.g., fitness, basketball).


  • Representation Learning
  • Efficiency in Deep Learning.


  • PhD. in Efficient Deep Learning

    Vrije Universiteit Amsterdam

  • MSc. Computational Engineering, 2018

    Technische Universit├Ąt Berlin

  • BSc. Mechatronic Engineering, 2016

    Universidad Nacional de Colombia