Electrical Engineering
Showing 121-140 of 350 Results
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Cassandra Huff
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioCassandra Huff is a PhD Candidate in Electrical Engineering working on developing cost-effective sensors for measuring biogenic, greenhouse gas emissions (GHGs). She is interested in the overlap of technology and environmental science, science and technology policy and ethics, and prototyping. Her PhD work is specifically focused on building a cost-effective, scalable, optical sensor to measure methane (CH4) emissions from wetland and rice paddies.
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Sydney Hunt
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioSydney Hunt (she/her), from Cornwall, New York, is a Knight-Hennessy Scholar pursuing a PhD in electrical engineering with a focus on brain-computer interfaces (BCI) at Stanford School of Engineering. She is advised by Paul Nuyujukian, MD, PhD in the Brain Interfacing Laboratory.
She currently serves as a Trustee on the Duke University Board of Trustees, Knight-Hennessy Scholar Ambassador, and on the Knight-Hennessy Scholar Experience Committee. She graduated with distinction from Duke University with bachelor’s degrees in electrical/computer engineering and computer science (concentration in artificial intelligence and machine learning), and a minor in gender, sexuality, and feminist studies.
An aspiring professor, Sydney passionately commits herself to STEM retention as a founding member of both the nonprofit CS Sidekicks and Duke’s S.P.I.R.E. Fellows Living Learning Community. She conducted and published her BCI research at Caltech (Richard Andersen’s lab) and MIT (Polina Anikeeva’s lab) through the WAVE Fellows and MIT SRP-Bio programs, respectively. She enjoys playing soccer, trying new food, and dad jokes. Sydney is certified in Mental Health First Aid and a recipient of Duke’s Reginaldo Howard Memorial Scholarship. -
Andrei Kanavalau
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioPhD candidate in Electrical Engineering at Stanford working across LLMs/Transformers, constrained optimization, and control.
