Yezhou Yang

Assoc Professor, School of Computing and Augmented Intelligence

Dr. 'YZ' Yezhou Yang, is a tenured Associate professor in computer science and engineering in the School of Computing and Augmented Intelligence at Arizona State University. He earned his doctorate in computer science in 2016 from the University of Maryland at College Park. His dissertation research on computational tools and the underlying mechanisms of robotic manipulation actions has been featured in MIT Technology Review, IEEE Spectrum, Time magazine and the Washington Post. Yang’s research interests also include computer vision, autonomous intelligent robots and artificial intelligence.

ASU Search Email

Fall 2022

Benjamin Joseph L. Herrera

Computer science

VivyNet: A New Approach to Creating AI-Generated Music

Researching different machine learning training methods and techniques will allow non-musicians to compose classical compositions from poems.

Program: FURI

Manthan Chelenahalli Satish

Robotics and autonomous systems

Vehicle Speed Estimation from 3D Object Detection for Surveillance Cameras

Estimating the speed of vehicles from traffic cameras from a 3D perspective will be more accurate and efficient than using speed guns.

Program: MORE

Spring 2022

Himanshu Pahadia

Computer science

Monocular 3D Object Detection for Traffic Analysis

Developing a monocular 3D object detection system for traffic cameras will help provide an accurate trajectory estimation for vehicles.

Program: MORE

Benjamin Joseph L. Herrera

Computer science

VivyNet: A New Approach to Creating AI-Generated Music

Researching different machine learning training methods and techniques will allow non-musicians to compose classical compositions from poems.

Program: FURI

Fall 2021

Wei Wang

Engineering (electrical systems)

Automated Traffic Incident Detection and Driver Behavior Analysis

Using advanced computer vision algorithms and artificial intelligence to develop methods of road safety analysis with roadside traffic monitoring videos will improve road safety. intelligence.

Program: FURI

Summer 2021

Wei Wang

Engineering (electrical systems)

Automated Traffic Incident Detection and Driver Behavior Analysis

Using advanced computer vision algorithms and artificial intelligence to develop methods of road safety analysis with roadside traffic monitoring videos will improve road safety. intelligence.

Program: FURI

Spring 2021

Wei Wang

Engineering (electrical systems)

Traffic Analysis with Drone Videos

Developing a system for traffic analysis with drone videos and advanced computer vision will improve traffic monitoring.

Program: FURI

Sumedh Godbole

Computer science

Online Prediction for Vision-based Active Pursuit using a Domain Agnostic Offline Motion Model

Emulating the function of vision-related neurons in predators can enhance the ability of autonomous vehicles to navigate in rapidly changing environments.

Program: MORE

Prasanth Buddareddygari

Computer science

Adversarial Attacks on Autonomous Driving with Physically Realizable Patterns

Studying the behaviors of autonomous driving systems when encountering adversarial physical objects will help improve robustness and security.

Program: MORE

Clinton Major Brown

Computer science

Developing Robust Defenses for Deep Neural Networks

Developing defenses for machine learning algorithms in computer vision will keep people safe from manipulative attacks.

Program: FURI

Summer 2020

Mertay Dayanc

Computer science

Real Time Multimodal Classification for Social Media Notifications

Designing a model that can take either an image, text or both will help classify social media message into different categories in real time.

Program: FURI

Spring 2019

Shibin Zheng

Computer engineering

Active Binocular Vergence-Gaze Control for Visual SLAM

Enabling an active binocular system will help improve the mapping and navigation performance of a robot.

Program: MORE

Anshul Rai

Computer engineering

General Depth Estimation For Machine Vision Using Sparse Depths

Designing a depth estimation algorithm for single-camera systems will improve depth prediction performance.

Program: MORE