Neuromorphic AI Research

Portrait of Lorenzo Pes

Lorenzo Pes

Doctoral Candidate in Electrical Engineering at Eindhoven University of Technology, working on hardware-software co-design for spiking and artificial neural networks in physical devices, with a focus on efficient on-device continual learning.

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Career

Eindhoven University of Technology

Doctoral Candidate · Full-time

Oct 2023 - Present · Eindhoven, North Brabant, Netherlands

  • Neuromorphic engineering.
  • Online and continual learning.
  • Hardware/software co-design.
  • Digital and analog hardware design.
  • Photonic devices.

Cents

Machine Learning Engineer · Freelance

Oct 2023 - Jun 2025

  • Recommendation systems.
  • Neural collaborative filtering.
  • Reinforcement learning for recommendation systems.

Back End Developer

Sep 2022 - Oct 2023

  • SQL databases.
  • Looker Studio.

IBM Research

Research Internship · Internship

Sep 2022 - Feb 2023 · Zurich, Switzerland

  • NeuroAI toolkit.
  • Spiking neural network development in PyTorch.
  • Custom training algorithm design.
  • Online Spatio Temporal Learning implementation in the HERMES neuromorphic chip.
  • Forward training algorithm design for spiking RNNs.

Online Spatio-Temporal Learning with Target Projection

Teletecnica Srl

Hardware Engineer · Internship

Feb 2021 - Aug 2021 · Sigillo, Umbria, Italy

  • Full PCB design in KiCad.
  • Battery monitor design for UPS systems measuring voltage, current, and temperature across 12 batteries via RS485.
  • Relay and digital reading module development for a rectifier system.
  • User interface creation with LVGL (C) for managing RS485 boards on Raspberry Pi touchscreens.
  • Embedded programming using STM32CubeIDE in C.

Agence de mobilite durable

Hardware Engineer · Internship

Oct 2019 - Apr 2020 · Montreal, Quebec, Canada

  • PCB design in Eagle for parking status display devices using LoRa and LoRaWAN.
  • Integration of battery management, LED drivers, solar cell interface, and LoRa module.
  • STM32 embedded C firmware development for BMS and LoRa communication.
  • Hardware test campaigns with oscilloscopes, function generators, and power supply units.

Education

Delft University of Technology

Master of Science (MS) · Electrical Engineering: Microelectronics

Sep 2021 - Sep 2023

Concordia University

Bachelor of Engineering · Electrical Engineering, Electrical, Electronics and Communications Engineering

Sep 2017 - Dec 2020

Projects

Continual Learning in Spiking Neural Networks

Investigating biologically inspired learning rules and active dendrites to reduce catastrophic forgetting in time-to-first-spike neural networks.

Forward-Only Learning

Developing memory-efficient and scalable alternatives to backpropagation through time for training spiking neural networks on dynamic signals.

Hardware-in-the-Loop Photonic Training

Exploring optical correlators and hardware-aware training pipelines that combine neuromorphic principles with physical photonic systems.

Publications

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Contact

Affiliation

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.

Professional Snapshot

Background includes internships in embedded hardware design and a research internship at IBM Zurich, alongside work spanning neuromorphic AI, embedded systems, and microelectronics.