Elliot Maceda

Hello! I am a fourth year PhD candidate in the Department of Statistics at North Carolina State University (NC State) under the advisory of Dr. Brian J. Reich. I graduated from Miami Unversity with an M.S. in Statistics under the advisory of Stephen E. Wright in the Department of Statistics. I also have a B.S. from the University of Houston (UH) in Mathematics, with a Minor in Computer Science.

I am a member of UQ4Life, a Research Training Group (RTG) focusing on interdisciplinary research between statistics, mathematics, and life sciences. My background is in Statistics and Mathematics, but my projects are rooted in epidemiology, ecology, biology, and atmospheric science.

Complex differential equation models are extensively used in the life sciences to make predictions on our health or environment under various conditions. I use Bayesian parameter inference to calibrate these models with data to ensure they are realistic, producing accurate measurements of uncertainty to provide reliable information for scientists and decision makers. I also research AI and Machine Learning models, having coded many models to be fast and powerful data-driven predictors. My research explores how to improve the predictive power of these models by leveraging information from the Biological and Ecological models. Often my projects incorporate data from different sources to improve the performance of the inference in terms of accuracy and uncertainty quantification. Another theme of my research is developing scalable amortized inference methods, which can turn repeated expensive tasks into cheaper operations.

For more details regarding my research areas and applications, please check out the "Research and UQ4Life" tab above!

I am currently searching for postdoctoral research positions. If you are interested in collaboration, please don't hesitate to reach out! I prefer communication by email.

Research Interests

• Bayesian Simulation-Based Inference in Differential Equation Models
• Interdisciplinary Uncertainty Quantification Problems
• Amortized Inference with Bayesian Machine Learning
• Scalable High-Dimensional Inference
• Recursive Bayesian Estimation
• Computer Vision

Areas of Applications

• Environmental Applications
• Epidemiological Applications
• Biological Applications
• Atmospheric Chemistry Applications
• Healthcare Applications

News:

01-07-26:	My paper on variational assumptions in simulation-based inference has been officially accepted into Environmetrics!
12-11-25:	I am officially a PhD candidate after passing my Oral Prelim Exam! Special thanks to my committee members: Prof. Brian J. Reich, Prof. Ana-Maria Staicu, Prof. Mette S. Olufsen, Prof. Jonathan W. Stallrich, and Prof. Arvind K. Saibaba. I am expecting to graduate Summer 2026.
08-15-25:	I presented my work on murine pulmonary arterial networks and statistical shape analysis at the 10-year anniversary of the Comparative Medicine Institute in Raleigh. The poster can be found here! Email me if you are interested in joining our team!
08-03-25:	I gave my talk at JSM 2025 ENVR Student Paper Competition session in Nashville. The slides can be found here.
01-10-25:	I was named a winner on the JSM 2025 ENVR Student Paper Competition for my paper on Simulation-Based Inference! The preprint can be found here!