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).
In my free time, I like learning about new things (e.g., coffee, wine, carpentry) and doing sports (e.g., fitness, basketball).
PhD. in Efficient Deep Learning
Vrije Universiteit Amsterdam
MSc. Computational Engineering, 2018
Technische Universität Berlin
BSc. Mechatronic Engineering, 2016
Universidad Nacional de Colombia