Agenda

Microelectronics Colloquium

• Monday, 1 June 2026
• 14:00-15:00
• EWI Lecture Hall Chip

Machine Learning-Based Calibration of Analog-to-Digital Converters

ADC calibration algorithms are paramount in modern IC design to relax or overcome analog limitations. While digital-assisted analog and digital post-correc­tion techniques are widespread in literature, a relatively new approach – machine learning (ML)-based calibration – has the potential to calibrate highly complex errors but is still largely unexplored. In this forum, an overview of ML-based calibration methods and their challenges is presented followed by an outlook on future directions.

Speaker Bio:

Maarten Molendijk received the M.Sc. degree in electrical engineering (cum laude) from Eindhoven University of Technology, Eindhoven, The Netherlands, in 2022. In the same year, he joined NXP Semiconductors, where he works in the analog mixed-signal department on novel machine learning-based calibration methods for analog-to-digital converters. In 2024, he began pursuing a Ph.D. degree at Eindhoven University of Technology on this topic. His research interests include analog circuit modeling and calibration, interpretable machine learning, and signal processing.