D. Sculley

Saint Louis University — Spain

Computer Science · Physical Sciences

31h-index8.1kcitations61works0.02yr avg
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Research Topics

Spam and Phishing Detection(11), Machine Learning and Algorithms(9), Machine Learning and Data Classification(7), Text and Document Classification Technologies(6), Explainable Artificial Intelligence (XAI)(6)

Publications61 total

Changing Dynamics in Liver Allocation: Donor and Recipient Traits Pre- and Post Acuity Circle Implementation
American Journal of Transplantation·2025Open Access
The Impact of a Merit Point Incentive System on the Willingness to Donate Among Non-Registered Individuals
American Journal of Transplantation·2025Open Access
Using deep learning to annotate the protein universe
Nature Biotechnology·2022· 297 cited
A Voice-Activated Switch for Persons with Motor and Speech Impairments: Isolated-Vowel Spotting Using Neural Networks
2021· 3 cited
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
arXiv (Cornell University)·2021· 31 citedOpen Access
Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology
The American Journal of Human Genetics·2021· 6 citedOpen Access
Underspecification Presents Challenges for Credibility in Modern Machine Learning
arXiv (Cornell University)·2020· 430 citedOpen Access
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift
arXiv (Cornell University)·2020· 95 citedOpen Access
Population-Based Black-Box Optimization for Biological Sequence Design
arXiv (Cornell University)·2020· 15 citedOpen Access
Fairness is not static
2020· 154 citedOpen Access
The Inclusive Images Competition
˜The œSpringer series on challenges in machine learning·2019· 12 cited
Fair treatment allocations in social networks
arXiv (Cornell University)·2019· 1 citedOpen Access
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
arXiv (Cornell University)·2019· 648 citedOpen Access
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift
arXiv (Cornell University)·2019· 367 citedOpen Access
Using Deep Learning to Annotate the Protein Universe
2019· 81 citedOpen Access
TensorFlow.js: Machine Learning for the Web and Beyond
arXiv (Cornell University)·2019· 8 citedOpen Access
AG: Imperative-style Coding with Graph-based Performance
Proceedings of Machine Learning and Systems·2019
Rapid Prediction of Electron–Ionization Mass Spectrometry Using Neural Networks
ACS Central Science·2019· 185 citedOpen Access
TensorFlow.js: Machine Learning for the Web and Beyond
arXiv (Cornell University)·2019· 132 citedOpen Access
AutoGraph: Imperative-style Coding with Graph-based Performance
2019· 12 cited
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Frequent Co-authors

Daniel Golovin(7), Zachary Nado(6), Jasper Snoek(6), Michael Young(5), Eric Breck(5), Shanqing Cai(5), Martin Wattenberg(4), Balaji Lakshminarayanan(4), David Soergel(4), Gary D. Holt(3), Dietmar Ebner(3), Todd Phillips(3), Eugene Davydov(3), Jie Ren(3), Alexander D’Amour(3), Lucy J. Colwell(3), Gabriel Wachman(3), David Belanger(3), Yoni Halpern(3), James Atwood(3)