Showcasing Next-Generation Flexible and Hybrid Electronics Manufacturing with AI and Digital Twins at FLEX 2026
Northeastern University College of Engineering faculty and researchers will showcase cutting-edge advances in flexible and hybrid electronics manufacturing at FLEX 2026, the premier international conference for Flexible and Hybrid Electronics (FHE), taking place in Phoenix, Arizona.
Benyamin Davaji, Assistant Professor in the College of Engineering, alongside Haiyang Yun, Senior PhD Student, will instruct a professional course titled “Digital Twins for Printed Electronics: How Can AI Learn FHE Printing” on February 24, 2026, from 1:30–4:30 p.m. MT.
The course highlights research from Northeastern’s Autonomous Integrated Microsystems (AIMS) Laboratory, focusing on deep neural network–based predictive models that connect design, fabrication, and metrology data into continuously learning digital twins—virtual representations of physical manufacturing systems that enable real-time process monitoring and optimization.
Printed and flexible hybrid electronics manufacturing often faces challenges such as equipment drift, batch-to-batch variation, and environmental fluctuations, all of which can impact yield and consistency. Digital twin frameworks address these challenges by enabling early detection of process changes, virtual experimentation, and data-driven optimization that reduces development time and material waste.
Participants will be guided through the complete digital twin workflow, including image processing, virtual metrology, AI model training, and hyperparameter tuning. The course also features a hands-on module in which attendees build their own digital twin using real-world datasets.
This course offering underscores Northeastern’s leadership in integrating artificial intelligence with advanced manufacturing technologies and preparing the next generation of engineers to lead in smart, data-driven production systems.
For more information, visit the FLEX 2026 course page.