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Stacy L. Tantum

Bell-Rhodes Associate Professor of the Practice of Electrical and Computer Engineering
Electrical and Computer Engineering
Box 90291, Durham, NC 27708-0291
3579 Fitzpatrick CIEMAS, Durham, NC 27708

Overview


Stacy Tantum received the B.S.E.E. degree in Electrical Engineering and Economics from Tufts University in 1994, and the M.S. and Ph.D. degrees in Electrical Engineering, both from Duke University in 1996 and 1998, respectively.  During the summer of 1996 she was a Summer Research Assistant at SACLANT Undersea Research Center in La Spezia, Italy, where she collaborated on her PhD research on passive sonar with an international team of research scientists. Dr. Tantum is currently an Associate Professor of the Practice in Electrical and Computer Engineering at Duke University, where she is also the Faculty Director of the 360 Coaching Program for first-year advising in the Pratt School of Engineering.

Her current research interests are in the areas of domain-informed data science and context-aware machine learning, in which notions of privacy, bias, and making data science and machine learning decisions understandable and interpretable are at the forefront. She translates these interests to her efforts to improve student educational experiences by incorporating mindset-aware learning and neuroscience-informed teaching practices, such as metacognition and cognitive load, into the learning experiences she designs.

Current Appointments & Affiliations


Bell-Rhodes Associate Professor of the Practice of Electrical and Computer Engineering · 2018 - Present Electrical and Computer Engineering, Pratt School of Engineering
Associate Professor of the Practice in the Department of Electrical and Computer Engineering · 2016 - Present Electrical and Computer Engineering, Pratt School of Engineering

In the News


Published December 2, 2021
KEEN Teaching: Duke Engineering Faculty Engage with National Education Network

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Recent Publications


Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT.

Journal Article Artif Intell Med · February 2025 In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predictions ... Full text Link to item Cite

Work in Progress: Evaluation of 360 Coaching to Support Whole-Student Advising in the First-Year

Conference ASEE Annual Conference and Exposition Conference Proceedings · June 25, 2023 Cite

WIP - 360 Coaching to Support Whole-Student Advising in the First-Year

Conference ASEE Annual Conference and Exposition Conference Proceedings · August 23, 2022 Cite
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Recent Grants


Statistical Signal Processing for Remote Sensing of Targets: Proposal for Terrestrial Science Program

ResearchAssistant Research Professor · Awarded by Army Research Office · 2009 - 2013

Statistical Signal Processing for Robust Automated UXO Classification

ResearchCo Investigator · Awarded by Strategic Environmental Research & Development Program · 2010 - 2011

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Education, Training & Certifications


Duke University · 1998 Ph.D.
Duke University · 1996 M.S.
Tufts University · 1994 B.S.E.E.