Michael Glickman Email & Phone Number

Milpitas, California, United States

Hands-on leadership of electrical and firmware engineers in the rapid architecture, design and delivery of custom IoT solutions for external clients. Work with customers to define requirements and develop system architecture and actionable plan to bring concepts to reality. Design areas include audio, motion tracking with IMU sensors, E-ink drivers.

Milpitas, CA

• Lead five-person engineering team responsible for developing interconnect solutions that are stronger, faster, and more flexible. Identify and pilot solutions to expand interconnect applications: wearables and in-mold.
• Led an engineering team to bring physics-based In Mold Electronics design guidelines and processes to Flex with predictive modeling (FEA and machine learning) to provide rapid-feedback to engineers in the concept phase.
• Led international Substrate like PCB (SLP) team through the production of a test vehicle establishing state of the art PCB manufacturing capabilities, with a $2M budget. The SLP test vehicle demonstrated 200 micron BGA.
• Led team developing viscoelastic FEA PCB models to model via strain in 50-um vias for SLP
• Led team developing convolutional neural networks to predict effective CTE and modulus of arbitrary PCB designs using FEA as training data.
• Modeled, tested, and delivered meandered rigid-flex designs for a smart-shoe customer that increased reliability by 200x.

South San Francisco

• Responsible for the development and characterization of electrochromic windows for home and commercial applications.
• Successfully developed ellipsometry optical models to accurately measure complex multi-layer films. Verified model and data with FIB/SEM measurements and optical transmission data.
• Perform simulations of electrochromic window state changes using SPICE and COMSOL to model iris effect and develop gradients in transparent conductive oxide (TCO) to improve switching time.

• Key contributor in the development and characterization of voltage sensitive dielectric material to arrest ESD surges in circuit boards.
• Performed electrical, thermal, and mechanical simulations with COMSOL to model material behavior during a high power and high-speed event. Used Celery to perform distributed-computing Monte Carlo simulations of.
• Used statistical data analysis (JMP and Python) to identify design rules for significant yield improvements.
• Worked with high-volume international PCB manufacturers to diagnose failures and improve DFM process.
• Designed and built large dataset DOEs, rapid robotic test equipment with 3D movement, and new testing paradigms to characterize the electrical performance of proprietary polymer ESD absorptive layer embedded into PCBs.
• Worked with customers and industry partners to define and prototype new ESD protection applications and embedded ESD protection form factors, such as LED protection and HDMI interposer boards.

Newbury Park, CA

• Technology lead for the development of electrochemical sensors for in-situ process monitoring of electrodeposited alloy stoichiometry.
• Co-authored proposal for “The Integration of in-situ Electrochemical Microsensor Arrays to Enable the Reliable Electrodeposition of Complex Metal Alloys in Microsystems.” Proposal funded by government grant totaling.

• Used AutoCad, L-Edit, and Autodesk Inventor to design a high efficiency magnetic MEMS switch.
• Used 3D ANSYS to simulate and model switch performance. Also used MATLAB to develop analytical models for switch.
• Fabricated magnetic MEMS switch with integrated 3-D copper coils, ferromagnetic core, and gold contacts.

• Developed an automatic layout generator based on AutoDesk Inventor (using VBA scripting) to be incorporated with Stone Pillar, and connect to NSC standard pad layout.
• Used ANSYS to design and analyze MEMS switch design.

Ms, Electrical Engineering

Phd, Electrical Engineering

Bs, Electrical Engineering