I am a Ph.D. candidate in the interdisciplinary Computational Science and Engineering program at Georgia Tech, advised by Prof. Cassie S. Mitchell in the Laboratory for Pathology Dynamics. I previously earned my M.S. in the same program under the joint supervision of Prof. B. Aditya Prakash and Prof. Lauren N. Steimle, focusing on WiFi networks, mobility data, and COVID-19 modeling. I hold a B.S. in Economics and Mathematics from Presbyterian College (South Carolina, USA). During my Ph.D., I interned at Amazon, Tesla, and Berkeley Lab.
I am actively looking for a full time position in Machine Learning Scientist/Engineer beginning in early 2026 after graduation.
Research Interests
A central theme of my research is bridging modern generative models with physical or network systems under perturbations. Examples include the pathology dynamics of diseases, logistics networks, and human mobility. Recently, I have been exploring generative diffusion/flow models, stochastic optimal control, and network science.
Bio-mechanistic Generative Models
- Variational autoencoder–style approaches for generating brain connectomes under neurological diseases (IJMS 2025).
- Dynamic Brain Connectome Vulnerability in Neurodegeneration via Score-based Network Diffusion (coming soon!).
- Diffusion Bridge Sampler and Stochastic Optimal Control (title removed for review anonymization).
Additional Work
- Source-robust, non-parametric reconstruction of epidemic-like event-based network diffusion processes with online data (coming soon!)
- Augmenting Bayesian topic models using online confirmations from community-driven apps (BuildSys 2023)
- Representative deep-gray thermodynamic models of residential buildings (Energy & Buildings 2024)
- Empirical WiFi datasets for localizing COVID-19 interventions (Frontiers in Digital Health 2023)
Outside of research, I am a dreamer, reader, and enthusiastic audience member of musicals, sports, and concerts (🖤🩷).
Contact
- Email: jxie@gatech.edu
- Resume: Download PDF (Updated Aug 2025)