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Career

· Doctoral Student, School of Computer Science, Carnegie Mellon University2022–
· PhD Student, Robotics Institute, Carnegie Mellon University2022–
· Robotics Institute Summer Scholars (RISS) Program Participant, Carnegie Mellon University2021–
· Research Assistant, Duquesne University2018–2022
· Citizen Science Lab Instructor, Carnegie Mellon University
· Project Lead, CMU RI Outreach Website Team, Carnegie Mellon University

Publications (14)

auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
Machine Learning in Health Care · 2022
33
cited
The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks
arXiv.org · 2021
33
cited
Graph Neural Networks for Improved El Niño Forecasting
arXiv.org · 2020
16
cited
Exploring Representations and Interventions in Time Series Foundation Models
International Conference on Machine Learning · 2024
8
cited
Implicit Reasoning in Deep Time Series Forecasting
arXiv.org · 2024
6
cited
Investigating Compositional Reasoning in Time Series Foundation Models
arXiv.org · 2025
5
cited
Towards Long-Context Time Series Foundation Models
arXiv.org · 2024
5
cited
A More Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models
2025
1
cited
Global Deep Forecasting with Patient-Specific Pharmacokinetics
ACM Conference on Health, Inference, and Learning · 2023
1
cited
Robust Rule Learning for Reliable and Interpretable Insight into Expertise Transfer Opportunities
AAAI Conference on Artificial Intelligence · 2022
1
cited
Forking-Sequences
arXiv.org · 2025
Graph Deep Learning for Long Range Forecasting
2021
Intraoperative Features Improve Model Risk Predictions After Coronary Artery Bypass Grafting
Annals of Thoracic Surgery Short Reports · 2024
Unveiling and Manipulating Concepts in Time Series Foundation Models
arXiv.org · 2024
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