I’m a versatile, organized, and collaborative ML scientist and engineer, actively seeking new opportunities in wearables, health, biotech, or a similar domain. I’m eager to join an experienced and like-minded team.
In recent projects, I’ve led model design and development efforts and engineered scalable training and experiment tracking pipelines for both time series modeling and computer vision.
My dissertation research at Georgia Tech developed models and training techniques for biological neural activity, with applications in brain-computer interfaces and computational neuroscience.
I studied biomedical and electrical engineering at Clemson University after attending the SC Governor’s School for Science and Math in Hartsville, SC. In my free time I enjoy cooking, strength training, travel, and spending time outdoors.
- lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systemsarXiv 2023
- Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through timeAdvances in Neural Information Processing Systems 2021
- A large-scale neural network training framework for generalized estimation of single-trial population dynamicsNature Methods 2022