2021 Eaton-Hachigian Fellowship Recipients
The College of Engineering and the Fung Institute for Engineering Leadership are pleased to announce the recipients of the 2020–21 Eaton-Hachigian Fellowships, awarded this year to two students pursuing Master of Engineering degrees at UC Berkeley. Selected by the Dean of the College of Engineering, the Eaton-Hachigian Fellows are engineering graduate students, pursuing studies in energy-efficient electrical and power hardware or software solutions, wireless communications and sensing devices, or specialty materials.
The Eaton-Hachigian Fellowship was established in 2008 by gifts from the Cooper Industries Foundation and from Berkeley alumnus and the former Chairman, President, and CEO of Cooper Industries, Kirk Hachigian, ’82. Cooper Industries became part of Eaton Corporation in 2012, and the name of the fellowship was changed in 2017 from the Cooper Fellowship to the Eaton-Hachigian Fellowship.
This year’s fellows are Sydney Holgado and Liaowang “Zoey” Zou.
Candidate for MEng in Civil & Environmental Engineering
- Undergraduate Degree: Conservation & Resource Studies — Water Resources, UC Berkeley
- Capstone Project: [Post Road Foundation] Electric grid modernization to support rural fiber-optic broadband
This project will assess the ability of residential electric load flexibility to help support the deployment of fiber-optic broadband to the 60% of the U.S. land area that lacks modern connectivity. In particular, the team is working with Post Road to estimate the potential cost savings/revenues from residential electric load flexibility and the CO2 emission reductions of such technology, which may motivate philanthropic investment.
Faculty advisor: Gabriel Gomes (ME)
Liaowang “Zoey” Zou
Candidate for MEng in Electrical Engineering & Computer Sciences
- Undergraduate Degree: Statistical Science, Duke University
- Capstone Project: Detection and Diagnosis of Incipient Diseases
This project is developing a new algorithm using active machine learning method to detect new incipient diseases (like COVID-19). The team focuses on developing an ensemble model selection approach from a large number of models for detection of incipient diseases. Ultimately, they’d like to explore a method that allows them to select (a subset of) models out of a large library of models created during hyper parameter tuning and architecture exploration, so as to 1) maximize detection performance 2) create satisfactory uncertainty estimates on out-of-distribution data and incipient anomalies.
Faculty advisor: Alberto Sangiovanni-Vincentelli (EECS)
Congrats to this year’s fellowship awardees!
Learn more about the Fung Institute at funginstitute.berkeley.edu/