Projects
Current work & explorations
Research projects focused on advancing time series forecasting and evaluating modern ML architectures at scale.
Active ResearchIn Progress
LSGT-PFN
Exploring Bayesian time series and Probabilistic Forecasting utilizing Prior-Data Fitted Networks. Pushing the boundaries of how we model uncertainty in temporal data.
PythonPyTorchBayesian MLHPC
BenchmarkingIn Progress
GIFT-Eval Benchmark
Running foundational models and formatting datasets for the GIFT-Eval benchmark. Systematically evaluating model performance across diverse time series tasks.
PythonRSLURMData Engineering