This short list excludes in printing and in progress work. A detailed Curriculum Vitae is available here .
Table Of Contents
Automatic Dynamic Relevance Determination for Gaussian process regression with high-dimensional functional inputs
Submitted for publication - An article with a general framework for Gaussian process regression with functional inputs based on learning the relevance profile over the index space.
- Pre-print: 10.48550/arXiv.2209.00044
October 2022 - A talk at the NASA JPL Uncertainty Quantification for Remote Sensing Inverse Problems.
- Slides: to be posted
August 2022 - A talk at the Pacific Northwest National Laboratory - ISU workshop.
April 2022 - A talk at the SIAM Conference on Uncertainty Quantification.
- Slides: view online
Automatic Dynamic Relevance Determination for atmospheric states over vertical pressure grids for the MLS forward
October 2021 - A talk at the NASA JPL Uncertainty Quantification for Remote Sensing Inverse Problems.
The RITAS algorithm: a constructive yield monitor data processing algorithm
December 2020 - An article with a novel data-processing algorithm for irregular, misaligned, and overlapping spatial data recorded by yield monitor.
- Pre-print: 10.48550/arXiv.2209.11313
Emulation of Agricultural Production Systems sIMulator (APSIM)
September 2020 - A joint invited seminar with Jarad Niemi at Los Alamos National Laboratory.
- Slides: view online
BayesHMM: Full Bayesian Inference for Hidden Markov Models
April 2019 - A poster presented at the 44th Spring Lecture Series, University of Arkansas.
- Poster: view online .
bayesdfa: Bayesian Dynamic Factor Analysis (DFA) with ‘Stan’
September 2018 - An R Package available on CRAN.
- CRAN: view online .
BayesHMM: An R Package for Full Bayesian Inference for Hidden Markov Models
August 2018 - Google Summer of Code 2018 project.
Hierarchical Hidden Markov Models in High-Frequency Stock Markets
June 2018 - A full talk at the R/Finance 2018 Conference.
- Slides: view online .
Time Series (Master’s level course)
Abril 2018 - Lab slides for the Master’s level course in Time Series (UNR).
A Tutorial on Hidden Markov Models using Stan
January 2018 - Published in the proceedings of StanCon 2018.
- Article: view online .
- Files: view online .
Evaluating Forecast Accuracy of GARCH Volatility Models Applied to Daily Stock Prices in Argentina
October 2017 - Graduate thesis for the Master’s in Applied Statistics program.
- Thesis: view online .
- Slides: view online .
Daily Stock Price Forecasts in Argentina Using Hidden Markov Models
October 2017 - A lightning talk at the Inter-American Statistical Conference 2017.
- Slides: view online .
Bayesian Hierarchical Hidden Markov Models Applied to Financial Time Series
August 2017 - Google Summer of Code 2017 project.
- A brief technical introduction to Hidden Markov Models .
- Input-Output Hidden Markov Model applied to financial time series .
- Regime Switching and Technical Trading with Dynamic Bayesian Networks in High-Frequency Stock Markets .
A Quick Introduction to Hidden Markov Models Applied to Stock Volatility
May 2017 - A lightning talk at the R/Finance 2017 Conference.
- Slides: view repository , view online .
- Accompanying notebook: view repository , view online .