Portfolio item number 1
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portfolio
Portfolio item number 2
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publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
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Paper Title Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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research
Synthesizing Knowledge From Science for Performance Management Decisions
Presented at UNC Charlotte's Summer Research Symposium, 2022
Contributed to the development of a data-driven decision-making system that integrates causal inference and machine learning to improve hospital performance management.
Machine Learning on Electric Vehicle Lithium-Ion Battery Cycling Data for Health Estimation
Presented at UNC Charlotte's Undergraduate Research Conference, 2023
Leveraging machine/deep learning techniques while engineering new input features to enhance lithium-ion battery health estimation in electric vehicles.
Profiling I/O Behavior of a Particle-Physics Distributed Deep Learning Workload on Supercomputers
Presented at Argonne National Laboratory's Learning on The Lawn Summer Research Conference, 2023
Utilizing profilers and tracers to analyze I/O and GPU activity in order to optimize large-scale deep learning model training on supercomputers.
Causal Machine Learning for Heterogeneous Treatment Effect Estimation in the 2008 Oregon Health Insurance Experiment
(Ongoing), Presenting at UNC Chapel Hill's Celebration of Undergraduate Research, 2026
Using causal machine learning methods to uncover heterogeneous treatment effects in the OHIE and develop policy targeting algorithms that maximize the impact of Medicaid expansion.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Causal Machine Learning Teaching Slides
Advanced undergraduate/graduate teaching material, UNC Chapel Hill, Department of Economics, 2025
As part of an advanced undergraduate independent study, I developed a set of teaching slides on Causal Machine Learning. These slides are designed to complement courses such as UNC’s ECON 573: Machine Learning and Econometrics or to support a seminar dedicated to causal ML.