Zhaoyuan Yang Email & Phone Number

Mountain View, CA, US

Albany, New York, United States

• Computer Vision and Machine Learning
• Win and involve several research projects from DARPA, Army Research, etc.
• Implement and deploy multiple computer vision models related to industrial asset inspections on AWS.
• Work on model design, deployment, hardware and software inference acceleration.Federal Research Projects:DARPA - Geometries of Learning: Building robust and trustworthy computer vision models. Research on diffusion.

Albany, New York Area

Edison Engineer @ Machine Learning Lab @ Edge Computing Lab @ Computer Vision LabFocus on ML/CV model design and inference acceleration, robotics and edge computing.

Columbus, Ohio Area

• Thesis Research - Reinforcement Learning - Robotics - Cyber Physical System - Adversarial LearningGrant: National Science Foundation (NSF) CNS - 1565487
• Research of machine learning algorithms for autonomous vehicles and robotics.
• Design deep reinforcement learning algorithms using TensorFlow and PyTorch.
• Propose an adversarial training method to increase the stability of deep reinforcement learning.
• Analyze advantages and disadvantages of neural networks for function approximation.
• Design object detection and motion planning algorithms for drones using C++ and OpenCV.

Columbus, Ohio Area

• Machine Learning in Manufacturing & Digital Transformation:
• Designed a machine learning/computer vision application for process innovation.
• Analyzed data from manufacturing process and significantly reduced the manufacturing cost.
• Prototyped a computer vision fault detection algorithm for manufacturing systems.
• Wrote a POC document for use cases of Google Cloud Platform in the Science and Technology Center.
• Developed a live Twitter data analytics and content translation tool using Google Cloud Platform.

Greater Seattle Area

• Discover information of human cell with machine learning & computer vision:
• Designed automatic feature selection algorithms using R and Python.
• Built a cell structure prediction model from the selected features using XGBoost.
• Performed correlation, causal inference and association rule analysis for the features extracted from images of cells.
• Applied unsupervised learning algorithms and Facets for data visualization.

Columbus, Ohio Area

• Student Assistant for department of computer science and engineeringCourse - Foundation I: Discrete Structure (CSE2321).Responsibilities:
• Hold office hours answering questions related to the course.
• Grade homework.

• Student assistant for department of computer science and engineeringCourse - Software II: Software Development and Design (CSE2231). Responsibilities:
• Attend labs and hold office hours answering questions related to the course.
• Grade homework and projects.

Master'S Degree, Electrical And Computer Engineering, Gpa: 3.972

Thesis: Adversarial Reinforcement Learning for Control System Design: A Deep Reinforcement Learning Approach

Bachelor'S Degree, Electrical And Computer Engineering, Gpa: 3.962

Graduated with Summa Cum Laude Minor in Computer & Information Science (GPA: 4.0)

Physics, Grade: 88/100

Transferred to Ohio State in 2014.