About Me

Growing up, my family and I lived in Korea, Taiwan, and India before settling down in Portland, Oregon the summer before I started high school. In 2018, I completed my Bachelor's degree at Oregon State University with a major in mechanical engineering and a minor in mathematics.

I am now a PhD candidate (5th year) at the University of Michigan pursuing a joint doctorate in Mechanical Engineering and Scientific Computing. I plan to defend my dissertation in August 2023.

My research interests focus on developing Bayesian uncertainty quantification methods in deep learning models and applying these methods on a variety of health and safety applications. Please see my "Research and Publications" section or my CV for more details!

I plan to pursue a research-oriented position as a data scientist / machine learning engineer, particularly in domains focusing on the ethical and responsible use of AI/ML in health, healthcare, and safety.

Research and Publications

Balance Training Assessment

Projected Variational Bayesian Inference for Convolutional Neural Networks in Precision Health Balance Training

Jeremiah Hauth, Jamie Ferris, Steven Teguhlaksana, Christopher DiCesare, Kathleen H. Sienko, and Xun Huan

USNCCM conference, July 2021, Presentation



Variational Bayesian Inference for Convolutional Neural Networks in Precision Health Balance Training

Jeremiah Hauth, Steven Teguhlaksana, Jamie Ferris, Christopher DiCesare, Kathleen H. Sienko, and Xun Huan

SIAM CSE conference, March 2021, Presentation

Loss of Balance

Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units

Jeremiah Hauth, Safa Jabri, Fahad Kamran, Eyoel W. Feleke, Kaleab Nigusie, Lauro V. Ojeda, Shirley Handelzalts, Linda Nyquist, Neil B. Alexander, Xun Huan, Jenna Wiens, Kathleen H. Sienko

Sensors 2021, July 2021

https://doi.org/10.3390/s21144661

Bayesian Tumor Segmentation

Lowering the Computational Barrier: Partially Bayesian Neural Networks for Transparency in Medical Imaging AI

Snehal Prabhudesai, Jeremiah Hauth*, Dingkun Guo, Arvind Rao, Nikola Banovic, Xun Huan.

Frontiers in Computer Science. Volume 5. No 2 (2023), pp 1071174. *co-first author.

https://doi.org/10.3389/fcomp.2023.1071174

Helicopter Icing Diagnostics

A Rotorcraft In-flight Ice Detection Framework Using Computational Aeroacoustics and Bayesian Neural Networks

Myles Morelli, Jeremiah Hauth*, Alberto Guardone, Xun Huan, Beckett Zhou.

Structural and Multidisciplinary Optimization. In review /accepted with revisions. (2023). *co-first author.



Real-Time In-Flight Ice Detection System via Computational Aeroacoustics and Bayesian Neural Networks

Beckett Y. Zhou, Nicolas R. Gauger, Myles Morelli, Alberto Guardone, Jeremiah Hauth, and Xun Huan

AIAA Scitech. January 2020. Presentation.



Correlation Effects in Bayesian Neural Networks for Computational Aeroacoustics Ice Detection

Jeremiah Hauth, Xun Huan, Beckett Y. Zhou, Nicolas R. Gauger, Myles Morelli, and Alberto Guardone

AIAA Scitech. January 2020. Presentation.