Minzhang Chen
LOS ANGELES,CA
Summary
Self-motivated researcher with over 5 years of academic training and hands-on experience in artificial intelligence and hardware systems. Adaptable and quick to integrate into new environments with strong cross-cultural communication skills and a deep understanding of global research dynamics. Recognized for composure under pressure, fast learning abilities, and adeptness in managing complex, multi-threaded tasks independently.
Overview
5
5
years of professional experience
Work History
Modeling Self-Organized Criticality using Graph Neural Networks
UCLA ECE
09.2020 - 09.2025
- Developed a simulation framework to study self-organized critical (SOC) behavior in complex systems using graph neural networks (GNNs), focusing on phase transitions, critical exponents, and chaotic dynamics.
- Constructed a discrete SOC system based on sandpile and stochastic models. Represented node states as high-dimensional vectors evolving over time, and used GCNs (Graph Convolutional Networks) to predict next-state transitions based on graph structure.
- Independently implemented a full-stack simulation pipeline in Python using PyTorch, PyTorch Geometric, and SciPy. Designed modular code structure supporting flexible parameter settings, data generation, and batch simulations over large-scale graphs.
- Evaluated SOC behavior through statistical measures including power-law distribution fitting, critical exponent estimation, and bifurcation detection. Used custom scripts to visualize system evolution, phase diagrams, and criticality zones.
- Framework supports plug-in extensions for other physical and non-physical networks (e.g., social dynamics, traffic models), enabling generalization to diverse complex systems.
FermiNet-based Simulation of Multi-Mass Subsystems
UCLA ECE
06.2024 - 09.2025
- Independently implemented core components of FermiNet for multi-body fermionic systems, including data generation pipelines, custom loss functions, and network training routines.
- Designed and simulated quantum systems based on Laughlin wavefunctions and BCS models, with a focus on ground-state energy estimation and excitation spectrum analysis.
- Built and maintained modular Python scripts for training control, evaluation metrics, and visualization; handled multi-task training and debugging on the Hoffman2 HPC cluster.
Neuromorphic Diffusion Modeling via Voltage-Controlled Magnetoelectric Memory (MeRAM)
UCLA ECE
06.2022 - 06.2024
- Modeled neuromorphic diffusion behavior using a voltage-controlled magnetic tunnel junction (VC-MTJ), incorporating a Markov chain-based state transition process.
- Developed simulation tools to evaluate switching probability evolution under VCMA control and benchmarked energy efficiency against pseudo-random number generation schemes.
- Collaborated on the design of stochastic noise generation strategies for hardware-based AI applications, enabling high-fidelity diffusion and random sampling mechanisms.
- Demonstrated potential for neuromorphic memory in AI chip architectures and stochastic control systems.
- Published in Nature Communications: https://www.nature.com/articles/s41467-025-58932-x
Teaching assistant
University of California, Los Angeles (UCLA)
09.2024 - 06.2025
- Participate in multiple undergraduate courses, including regular courses and cluster courses (Cluster Class). Independently responsible for the teaching, courseware design and evaluation of an entire class in the cluster curriculum.
- Teaching assistant experience:
- EC ENGR 112 - Introduction to Power Systems
- EC ENGR 123A - Fundamentals of Solid-State I
- 25S-CLUSTER-70CW - Special Topics in Life and Physical Sciences
Education
Engineer Degree - Electronic and Computer Engineering
University of California, Los Angeles (UCLA)
10.2025
Mster of Science - Electronic And Computer Engineering
University of California, Los Angeles (UCLA)
06.2022
Bachelor of Science - Physics
Lanzhou University
06.2020
Skills
- Python (proficient in PyTorch, JAX, NumPy, SciPy, Matplotlib)
- High-performance computing expertise
- SQL (proficient in structured queries and large-scale data analysis)
- Linux/Unix environment (shell scripting, remote computing)
- LaTeX
- Skilled in Advanced Design System (ADS) for integrated circuit modeling and RF simulation
- Friendly, positive attitude
- Skilled in portrait photography
- Independently designed and instructed curriculum in physics and electronics
- Licensed long-distance driver
- Teamwork and collaboration
Languages
English
Full Professional
Chinese (Mandarin)
Native or Bilingual
Timeline
Teaching assistant
University of California, Los Angeles (UCLA)
09.2024 - 06.2025
FermiNet-based Simulation of Multi-Mass Subsystems
UCLA ECE
06.2024 - 09.2025
Neuromorphic Diffusion Modeling via Voltage-Controlled Magnetoelectric Memory (MeRAM)
UCLA ECE
06.2022 - 06.2024
Modeling Self-Organized Criticality using Graph Neural Networks
UCLA ECE
09.2020 - 09.2025
Engineer Degree - Electronic and Computer Engineering
University of California, Los Angeles (UCLA)
Mster of Science - Electronic And Computer Engineering
University of California, Los Angeles (UCLA)
Bachelor of Science - Physics
Lanzhou University
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