Ph.D. Student @
Jilin University
Deciphering battery secrets with Electrochemistry & Informatics.
Extracting precise physical and chemical parameters from experimental data to build accurate battery models.
Simulating internal battery states (concentration, potential) to understand degradation mechanisms at a microscopic level.
Leveraging machine learning and physics-based models to predict RUL (Remaining Useful Life) and optimize charging strategies.
# About Patrick
class Researcher:
university = "Jilin University"
major = "Electrochemistry"
interests = [
"Battery Informatics",
"Machine Learning"
]
def solve_energy_crisis(self):
return "Greener Future 🌿"
I bridge the gap between traditional electrochemistry and modern data science. My work focuses on unlocking the hidden patterns in battery data to make energy storage safer, longer-lasting, and more efficient.