About me

I am currently a Research Fellow at the subdivision of the non-profit organization Lovelace Biomedical Research Institute, with my focus on leveraging deep learning and large models to address challenges in Neuroscience. Before, I finished my Ph.D. in ECE at Purdue University, under the supervision of Prof. Qingxue Zhang. Prior to that, I finished my Computer Science master degree at The Unv. of Texas at Dallas. As my first stop in the US, Texas holds a special place in my heart. It is where I took my first fully English-taught course and experienced my first overseas stay beyond just being a tourist. Earlier, I spent 4 fruitful years at China's gorgeous capitial Beijing, and graduated from BISTU with unforgettable memories. Ahead of all of these stories, I was in Wuxi, a charming and sweet (we put more sugar than anywhere else) city in eastern China.

What i'm doing

  • AI icon

    AI Algorithms

    Transformer Models, Image Generation/Synthesis, Few-shot Learning, Deep/Reinforcement/Graph/Transfer/Machine Learning

  • Health icon

    Health

    Medical Images (MRI, CT), Physio-signal Processing (brain EEG/fNIRS, Eye EOG, Heart ECG, Body Motion EMG)

  • Cloud app icon

    Computing

    High Performance Computer (Message Passing Interface, Slurm, Slate, Module)
    Cloud Computing (AWS, Google Cloud)

  • App icon

    App Development

    Edge Computing Applications
    Web & Android Development

Resume

Experience

  1. Mind Research Network

    2023 — Now

    Research Fellow: Brain Neuro Imaging (Sex, Traumatic Brain Injury,Schizophrenia, Coginition)

  2. Purdue University

    2019 — 2023

    Doctor of Philosophy, Electrical Computer Engineering
    Thesis: "Wearable Big Data Harnessing with Deep Learning, Edge Computing and Efficiency Optimization"

  3. The University of Texas at Dallas

    2017 — 2019

    Master of Science, Computer Science
    Teaching Assistant, High School Course Mentor

  4. Beijing Information Science & Technology University

    2013 — 2017

    Bachelor of Engineering, Telecommunication Engineering
    Undergraduate Research Assistant: Simulation and Analysis of 3D Micro-Electromechanical Systems

Teaching

  1. Graduate Teaching Assistant (Purdue)

    2019 — 2023

    ECE 595 Efficient AI Theories and Designs

    Efficient Learning Theories, Patterns in the Data, Critical Pattern Learning, Computation Efficiency, Efficient Pattern Abstraction, Model Complexity, Efficient Model Execution, Learning Optimization, Efficient and Effective Inference, Learning Machine Deployment, Real-world System Design, Real-time Inference, etc.

    ECE 629 Neural Networks

    Artificial Neural Network, Backpropagation Learning, Optimization Problems, Feedforward and Multistage Networks, Recurrent Network, Backpropagation Through Time Learning, Convergence Analysis, Neural Activation Functions, Learning Theories, Supervised Neural Learning, Unsupervised Neural Learning, etc.

    ECE 662 Pattern Recognition and Decision Making

    Machine Learning Theories, Fundamental Learning Problems and Principles, Mathematical Optimization, Data Analysis, Feature Extraction, Statistical Analysis, Supervised Learning, Unsupervised Learning, Parametric Classifiers, Non-parametric Classifiers, Bayesian Decision Theory, etc.

  2. Undergraduate Teaching Assistant (UTD)

    2018

    CS 2305 Discrete Mathematics for Computing I

    Principles of counting. Boolean operations. Logic and proof methods. Recurrence relations. Sets, relations, functions. Elementary graph theory. Elementary number theory.

  3. CS Outreach Summer Campus Tutor (UTD)

    2018

    Instruct and help K-12 and high school students to make their personal software projects.

Portfolio

Gallery

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Contact Me

Jiadao Zou, Ph.D.
The Mind Research Network
1101 Yale Blvd NE
Albuquerque, NM 87106-4188

Working Email