Todd Karin

Vice President of Technology at Kiwa Pvel

Based in Berkeley, United States

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Seniority

Vp

Department

Information Technology

Location

Berkeley

Industry

Renewable Energy Semiconductor Manufacturing

Company size

39

Contact information

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Email

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t•••••••@kiwa.com

Phone

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Background

About Todd Karin

Dr. Todd Karin is VP of Technical Operations at Kiwa PVEL. He leads a team to execute Kiwa PVEL’s product qualification program, which assesses the reliability and bankability of commercial PV modules. He also leads the special projects division, overseeing research projects focused on PV reliability. Prior to joining PVEL, Dr. Karin studied PV module reliability at Lawrence Berkeley National Lab. There he developed novel methods for studying anti-reflection coating degradation and developed software libraries for analyzing PV module degradation using only the typically available DC data. While at PARC, Dr. Karin developed online monitoring systems using fiber Bragg gratings for monitoring the state-of-health of power transformers for grid applications. In his PhD, he investigated quantum optical properties of semiconductor defects and developed novel optical super-resolution microscopy methods. He has expertise in photovoltaics, power electronics, electrical design, optical systems, semiconductor physics, quantum optics, and semiconductor devices. Dr. Karin holds a Ph.D. in Physics from University of Washington and a B.A. in Physics from UC Berkeley. He received a National Science Foundation Graduate Research Fellowship and a University of Washington Clean Energy Institute fellowship. Skills • Highly motivated to work on enabling the energy transition. • Broad base of experience in solar energy including advanced data analysis of PV data, energy yield modeling, PV plant optimization, module degradation, next-generation inverter functionality and system performance. • Experienced with analog and digital electronics, instrument communication. • Expert in characterizing semiconductors using optical techniques. • Fast learner, fast execution • Expert in complicated data analysis, model fitting and error estimation. • Excellent communication skills. • Experienced in pinpointing when scientific bias clouds judgement. • Committed to diverse issues, e.g. how implicit bias affects workplace culture.

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