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Career

· Machine Learning Engineer, Google2024–
· Assistant Teaching Professor, Princeton University2023–2024
· Student Researcher, Google2021–2022
· Graduate Teaching Assistant, Carnegie Mellon University2019–2020
· Software Engineer Intern, Google2018–2018
· Master of Science - MS, Machine Learning, Carnegie Mellon University2017–2019
· PhD, Machine Learning, Carnegie Mellon University2017–2023
· Undergraduate Teaching Assistant, Universidad de Los Andes2013–2014
· Bachelor of Engineering - BE, Systems and Computing Engineering, Universidad de Los Andes2012–2016

Publications (10)

LEAF: A Benchmark for Federated Settings
arXiv.org · 2018
1,643
cited
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements
arXiv.org · 2018
501
cited
Differentially Private Meta-Learning
International Conference on Learning Representations · 2019
122
cited
Federated Kernelized Multi-Task Learning
2018
29
cited
A Case for Federated Learning: Enabling and Leveraging Inter-Hospital Collaboration
2020
3
cited
Understanding Clinical Collaborations Through Federated Classifier Selection
Machine Learning in Health Care · 2021
2
cited
Using Machine Learning to Support Transfer of Best Practices in Healthcare
American Medical Informatics Association Annual Symposium · 2021
2
cited
Learning Tokenization in Private Federated Learning with Sub-Word Model Sampling
2021
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract)
AAAI Conference on Artificial Intelligence · 2024
Unsupervised Risk Discovery for Child Welfare Screening
2019
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Sebastian Caldas | Researcher Profile | Sotabase | Sotabase