cv

Basics

Name Bob (Jue) Guo
Label Ph.D. Candidate in Computer Science
Email guoj1995@gmail.com
Url https://csragtoriches.com/
Summary Jue Guo is a Ph.D. candidate in Computer Science specializing in machine learning, with extensive experience teaching graduate-level courses such as Machine Learning, Deep Learning, and Algorithm Analysis and Design. His research expertise spans image classification and natural language processing. Skilled in Python, JavaScript, and frameworks including PyTorch and TensorFlow, Jue effectively translates complex algorithms into practical solutions. Jue currently holds a valid Employment Authorization Document (EAD) and does not require employer sponsorship. His permanent residency application is in progress.

Work

  • 2023.07 - Present
    Adjunct Faculty
    University at Buffalo – SUNY
    • Instructed 5 graduate-level CS courses, including AI, ML, and Deep Learning, to over 300 students, focusing on real-world applications and algorithmic problem-solving.
    • Designed and implemented course curriculum integrating theoretical ML concepts with hands-on labs using PyTorch and TensorFlow.
    • Mentored over 20 graduate students through thesis projects in machine learning and AI, providing technical feedback on model development and paper writing.
  • 2022.08 - 2023.05
    Graduate Teaching Assistant
    University at Buffalo – SUNY
    • Conducted weekly recitation sessions and 1-on-1 mentoring for 200+ students in Machine Learning and Deep Learning courses, using real-world case studies and frameworks like PyTorch to reinforce concepts.
    • Held weekly office hours to support student mastery of ML topics such as backpropagation, CNNs, LLMs, and optimization, contributing to increased student engagement and positive feedback.
  • 2019.06 - 2020.08
    Machine Learning Engineer
    Zhejiang University, Zhejiang Society for Mathematical Medicine
    • Developed a deep learning-based bone age detection system using CNNs to assist orthopedic diagnostics at Zhejiang No.1 People’s Hospital.
    • Collaborated with a team at Zhejiang University to implement machine learning algorithms for medical imaging analysis.
    • Applied image preprocessing, augmentation, and CNN-based feature extraction using PyTorch, resulting in more accurate and robust diagnostic outcomes.

Education

  • 2022.08 - Present

    Buffalo, NY

    PhD
    The State University of New York at Buffalo
    Computer Science
  • 2020.08 - 2022.06

    Buffalo, NY

    Master of Science
    The State University of New York at Buffalo
    Robotics and Artificial Intelligence
  • 2015.08 - 2019.05

    Winston-Salem, NC

    Bachelor of Science
    Wake Forest University
    Computer Science

Skills

Programming
Python
C++
Java
JavaScript
Machine Learning
PyTorch
TensorFlow
Scikit-learn
Data Analysis
NumPy
pandas
Matplotlib
Seaborn
DevOps & Tools
Git
Docker
Linux
Weights & Biases
Professional
Curriculum Design
Technical Writing
Research
STEM Teaching

Languages

Chinese
Native speaker
English
Fluent

Interests

Machine Learning
Continual Learning
Adversarial Learning
Graph Representation Learning