Expertise:

· BSc and MSc in Electrical and Computer Engineering from the University of Porto (2016)

· Specialization from ETH Zürich in Embedded Artificial Intelligence (2024, Swiss Post-Grad Diploma of Advanced Studies).

· 10+ years experience in Embedded Software development and Embedded Systems architecture.

· Proficient in several programming languages (C, C++, Python, CUDA-C and Java).

· Expertise in high-performance computing (multi-threaded CPU and GPU programming), data analysis, digital signal processing and AI/ML algorithm deployment on edge devices.

José Fonseca is an electrical and computer engineer, who specializes embedded systems programming, signal processing and AI/ML algorithm deployment on edge devices. He is a Software & Controls Engineer at TRAILA. Before this, José worked at other renowned startups such as WiTricity, and started his career as an Electronics Engineer at CERN, in the prestigious Fellowship Programme. Problem-solving and interdisciplinary thinking are at the core of José’s mindset

Selected Publications:

· J. Fonseca, C. Cioflan, X. Wang and L. Benini, "NanoHydra: Energy-Efficient Time-Series Classification at the Edge," 2025 International Joint Conference on Neural Networks (IJCNN), Rome, Italy, 2025, pp. 1-7, doi: 10.1109/IJCNN64981.2025.11229151.

· J. C. Ferreira and J. Fonseca, "An FPGA implementation of a long short-term memory neural network," 2016 International Conference on ReConFigurable Computing and FPGAs (ReConFig), Cancun, Mexico, 2016, pp. 1-8, doi: 10.1109/ReConFig.2016.7857151.

· P. Moreira et al., "lpGBT: Low-Power Radiation-Hard Multipurpose High-Speed Transceiver ASIC for High-Energy Physics Experiments," in IEEE Transactions on Nuclear Science, vol. 72, no. 1, pp. 24-37, Jan. 2025, doi: 10.1109/TNS.2024.3506753.

· S. Kulis et al., "A High-resolution, Wide-range, Radiation-hard Clock Phase-shifter in a 65 nm CMOS Technology," 2019 MIXDES - 26th International Conference "Mixed Design of Integrated Circuits and Systems", Rzeszow, Poland, 2019, pp. 147-150, doi: 10.23919/MIXDES.2019.8787202.