Ryon Farhadi
Los Angeles, California, United States
923 followers
500+ connections
About
Electrical engineer focused on end-to-end hardware development, including circuit…
Experience
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Education
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University of Southern California
Activities and Societies: IEEE, Indoor & Beach Volleyball Clubs
Focus in Mixed-Signal IC Design
Research in MEMS Capacitive Strain Sensors -
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Courses
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Analog Integrated Circuits
EE 536a
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CMOS VLSI Circuit Design
EE 477L
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Electromagnetic Compatibility (EMC)
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Microelectromechanical Systems (MEMS)
EE 607
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Mixed-Signal Integrated Circuits
EE 631
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Power Electronics
EE 528
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Spacecraft System Design
ASTE 520
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Wireless Communication Systems
EE 467
Honors & Awards
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2020 & 2021 Annual Dean's List
University of Washington
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3x All-PIVA First Team
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Voted amongst players and coaches as the highest performing athlete for my position in the conference.
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Mukherjee, Animesh
Multi-Objective Optimization in PCB Manufacturing In PCB design, it’s never about one goal — you’re constantly balancing signal integrity, manufacturability, cost, and performance. That’s where multi-objective optimization (MOO) comes in — using algorithms (like Genetic Algorithms + AI) to explore trade-offs and find the best feasible designs, not just the fastest or cheapest ones. Think of it like nature’s evolution — every design generation learns what works and what doesn’t. Why it matters: Real manufacturing data already shows the value: Siemens Valor NPI → cut design re-spins by 57%. Phuntronix → slashed process-prep time by 50% using Siemens tools. Faraday Tech → reduced interconnect design time by 60% with Cadence OrbitIO. All these are examples of balancing multiple design goals — cost, yield, and manufacturability — through smarter optimization. What’s changing: As PCB layouts move into multi-sensor, multi-clock domains, optimization isn’t just about geometry anymore — it’s about learning systems that balance constraints continuously. EDA + AI + DFM + digital twins are making that “first-time-right” board closer than ever. So here’s a question — 👉 If you could teach your design tool one optimization priority (cost, yield, performance, or reliability), which would you choose first? https://lnkd.in/gqTSSQSh https://lnkd.in/g9wiET9R https://lnkd.in/gJebxGp5
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