Persoonlijk profiel

Research profile

I believe in neuromorphic technologies as a possible breakthrough for efficient and decentralized AI. My research focuses on the hardware-software co-design of learning algorithms for spiking and artificial neural networks in physical devices, with the goal of enabling on-device continual learning. 

Academic background

I received a B.Eng from Concordia University (Montreal, Canada) with a specialization in VLSI/electronics and a MSc from Delft University of Technology (Delft, Netherlands) with a specialization in microelectronics. I gained experience through three internships: two as an embedded hardware designer and one as a research intern at IBM Zurich. My skills include the design of electrical boards (KiCad), digital design (Verilog), embedded programming (C/C++), artificial and spiking neural networks deployment in Pytorch (Python) as well as analog design (Cadence).

Opleiding / Academische kwalificatie

Electrical engineering, Master, Delft University of Technology

Datum van toekenning: 29 sep. 2023

Electrical engineering, Bachelor, Concordia University

Datum van toekenning: 8 dec. 2020

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