Cailong Hua

About Cailong Hua

I\'m currently completing my Ph.D. in Electrical Engineering with a minor in Computer Science at the University of Minnesota. My expertise spans machine learning, control systems, signal processing, large language models (LLMs), and data analysis.In one of my core projects, I developed a novel physics-augmented deep learning model for automating the classification of single-molecule force spectroscopy (SMFS) data. By incorporating protein unfolding physics, the model reduced manual analysis time from a full day to under an hour. I led collaboration across three labs for this project, which was recently accepted at ICML.I also designed a physics-aware deep clustering framework to uncover latent representations from protein unfolding data—representing the first reported effort to automate the identification of heterogeneous mechanical domains. This work has been submitted to another project, I created algorithms to quantify errors in non-equilibrium experiments under limited data conditions, and validated the theoretical results through both simulations and experimental data.Additionally, I have experience fine-tuning large language models using parameter-efficient techniques on internal datasets, and deploying a chatbot using AWS.

Experience

1. Applied Scientist

   Amazon

   Oct 2025 — Present · Seattle, WA, US

Education

• University of Minnesota

  Doctor of Philosophy - PhD, Electrical and Electronics Engineering

  2025

• Politecnico di Milano

  Bachelor's degree, Automation Engineering

  2015 — 2016

• Imperial College London

  MSc, Control Systems with Distinction

  2016 — 2017

• Tongji University

  Bachelor of Engineering - BE, Electronic Information and Engineering

  2012 — 2016