Xiangyu Gao

I obtained my Ph.D degree in the department of electrical & computer engineering at the University of Washington, under the supervision of Prof. Sumit Roy at FUNLAB.

The goal of my research is to foster new-generation radar perception and multi-sensor fusion in autonomous driving field.

I am happy to answer questions about dataset, code, or algorithms via email (xygao@uw.edu).

Selected highlights

CODE and SAMPLE DATASET for Radar Multiple Perspective Object Detection

Paper presented at IEEE Sensors Journal 2020
pdf code dataset

Raw ADC Data of 77GHz MMWave radar for Automotive Object Detection

Dataset, 2022
download readme link

Raw ADC Data of 2D-MIMO MMWave radar for Carry Object Detection

Dataset, 2022
download readme link

2022

Deformable Radar Polygon: A Lightweight and Predictable Occupancy Representation for Short-range Collision Avoidance
Xiangyu Gao, Sihao Ding, Karl Vanas, Harshavardhan Reddy Dasari, Henrik Soderlund
preprint 2022
pdf

Learning to Detect Open Carry and Concealed Object with 77GHz Radar
Xiangyu Gao, Hui Liu, Sumit Roy, Guanbin Xing, Ali Alansari, Youchen Luo
IEEE Journal of Selected Topics in Signal Processing 2022
pdf

2021

Towards Millimeter-wave Radar Signal Processing and Learning-Based Applications
Xiangyu Gao
General exam report 2021
pdf

Perception Through 2D-MIMO FMCW Automotive Radar Under Adverse Weather
Xiangyu Gao, Sumit Roy, Guanbin Xing, Sian Jin
IEEE International Conference on Autonomous Systems 2021
pdf

Cognition in Automotive Radars
Sian Jin, Xiangyu Gao, Sumit Roy
Next Generation Cognitive Radar Systems, IET Book 2021

MIMO-SAR: A Hierarchical High-resolution Imaging Algorithm for mmWave FMCW Radar in Autonomous Driving
Xiangyu Gao, Sumit Roy, Guanbin Xing
IEEE Transactions on Vehicular Technology 2021
pdf

2020

RAMP-CNN: A Novel Neural Network for Enhanced Automotive Radar Object Recognition
Xiangyu Gao, Guanbin Xing, Sumit Roy, Hui Liu
IEEE Sensors Journal 2020
pdf code

Rodnet: Radar object detection using cross-modal supervision
Yizhou Wang, Zhongyu Jiang, Xiangyu Gao, Jenq-Neng Hwang, Guanbin Xing, Hui Liu
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision 2020
pdf code

2019

Experiments with mmwave automotive radar test-bed
Xiangyu Gao, Guanbin Xing, Sumit Roy, Hui Liu
53rd Asilomar Conference on Signals, Systems, and Computers 2019
pdf code

Raw ADC Data of 77GHz MMWave radar for Automotive Object Detection
Xiangyu Gao, Youchen Luo, Guanbin Xing, Sumit Roy, Hui Liu
IEEE dataport 2022
download readme link

Raw ADC Data of 2D-MIMO MMWave radar for Carry Object Detection
Xiangyu Gao, Sumit Roy, Hui Liu, Youchen Luo, Guanbin Xing, 2022
download readme link

Radar Multiple Perspective Object Detection
Xiangyu Gao, 2020
pdf code sample data

MmWave Radar Signal Processing and micro-Doppler based Obejct Recognition
Xiangyu Gao, 2019
pdf code sample data

Xiangyu Gao is a machine learning engineer at Motional and he obtained his Ph.D. in the department of electrical & computer engineering at the University of Washington on August 2023, under the supervision of Prof. Sumit Roy at FUNLAB. His research advances next-generation radar perception and multi-sensor fusion methods through statistical signal processing and deep learning.

Xiangyu received a B.S. degree in communication engineering from Xidian University, Xi’an, China, in 2018, and an M.S. degree in electrical and computer engineering from the University of Washington, Seattle, WA, USA, in 2020. He also obtained a M.S. degree in Applied Mathematics at the University of Washington, in 2023.

Ph.D Candidate
Electrical and Computer Engineering
University of Washington

ECE building #307R
Paul Allen Center, 185 E Stevens Way NE AE100R
Box #352500
Seattle, WA 98195

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