iMAPS New England Chapter Meeting in collaboration with IEEE Microsystems & SMTA Boston Chapters
iMAPS New England
Announcement of Chapter Business Meeting & Election of Officers
in collaboration with IEEE Microsystems & SMTA Boston Chapters
“AI and Digital Twins for Microelectronics and Flexible Hybrid Electronics:
Design, Manufacturing, and Testing “
Presenter: Benyamin Davaji, Northeastern University
Design and manufacturing optimization in microelectronics and flexible hybrid
electronics (FHE) still relies heavily on costly, time-consuming trial-and-error
experimentation. We’ll introduce a physics-informed AI digital twin that predicts
device structure and electrical performance directly from fabrication parameters,
enabling virtual process development before fabrication. The framework
combines deep learning with physics-informed neural networks (PINNs) that
embed process-specific governing physics, improving accuracy, interpretability,
and generalization across recipes, materials, and substrates. Validated on DUV
photolithography, plasma etching, and printed FHE processes, the models predict geometry,
material properties, conductivity, and frequency response using quantitative metrology data.
Designed for bidirectional integration with EDA and TCAD workflows, the digital twin can be
inverted to identify fabrication recipes that meet target device specifications while prioritizing the
most informative experiments. The approach reduces development cycles and process exploration
costs, enabling a transition from empirical optimization to physics-guided, AI-driven design,
manufacturing, and testing.
Date and Time
Location
Hosts
Registration
-
Add Event to Calendar
- New England Die Company
- 96 Milk St
- Methuen, Massachusetts
- United States 01844
- Contact Event Host
- Co-sponsored by iMAPS New England
- Starts 21 September 2026 06:22 AM UTC
- Ends 25 September 2026 04:00 AM UTC
- No Admission Charge
Speakers
Ben of Northeastern University
AI and Digital Twins for Microelectronics and Flexible Hybrid Electronics
Design and manufacturing optimization in microelectronics and flexible hybrid
electronics (FHE) still relies heavily on costly, time-consuming trial-and-error
experimentation. We’ll introduce a physics-informed AI digital twin that predicts
device structure and electrical performance directly from fabrication parameters,
enabling virtual process development before fabrication. The framework
combines deep learning with physics-informed neural networks (PINNs) that
embed process-specific governing physics, improving accuracy, interpretability,
and generalization across recipes, materials, and substrates. Validated on DUV
photolithography, plasma etching, and printed FHE processes, the models predict geometry,
material properties, conductivity, and frequency response using quantitative metrology data.
Designed for bidirectional integration with EDA and TCAD workflows, the digital twin can be
inverted to identify fabrication recipes that meet target device specifications while prioritizing the
most informative experiments. The approach reduces development cycles and process exploration
costs, enabling a transition from empirical optimization to physics-guided, AI-driven design,
manufacturing, and testing.
Biography:
Benyamin Davaji is an Assistant Professor of Electrical and Computer Engineering at
Northeastern University, where his Autonomous Integrated MicroSystems (AIMS) Laboratory
works on acoustic and ultrasound microsystems, bio-interfaces, and AI-driven digital twins for
microsystem design and manufacturing. His research is supported by the NSF, DARPA, ARL, AFRL,
AFOSR, and SEMI. He is a 2026 Hilton Head Rising Star of Microsystems and a FlexTech FLEXI
Award recipient. He earned his Ph.D. from Marquette University and completed postdoctoral work
at Cornell University.
Agenda
5:30 PM Registration, Socializing, Networking, Casual Dinner
6:45 PM Matt Bracy, President - Chapter Business Meeting - Introduction of Chapter Elections
7:00 PM Dmitry Marchenko, Nominating Committee Chair - Election of Chapter Officers
The Chapter Nominating Committee Submits the following Candidates for Chapter Office for 2027:
President: Richard Koba - Onto Technologies
Vice President: Sunny Agarwal, ITW EAE
Treasurer: Michael Curley - TTM Technologies
7:15 PM Matt Bracy, President - Adjourn Business Meeting & Introduction of Presentation