Latest News

2026 3 news
2026-01
One paper was accepted by Modelling and Simulation in Materials Science and Engineering (SCI, JCR Q2)! Congrats to Haiyang Tang
2026-01
One paper was accepted by Biomedical Signal Processing and Control (SCI, JCR Q2)! Congrats to Jiajun Cai
2026-01
One paper was accepted by Journal of Applied Geophysics (SCI, JCR Q2)! Congrats to Dr. Quan Zhang

Biography

Bo Peng received his B.E. degree in Computer Science from Southwest Petroleum University (SWPU), Chengdu, China, in 2003, followed by an M.S. in 2007 and a Ph.D. in 2014, both from Sichuan University, Chengdu, China, under the supervision of Prof. Dong C. Liu. He joined the School of Computer Science and Software Engineering at SWPU in 2007 and was promoted to Professor of Computer Science in 2021.

Between 2015 and 2017, he pursued post-doctoral research in the Department of Biomedical Engineering at Michigan Technological University, Houghton, USA, under the supervision of Prof. Jingfeng Jiang. From 2020 to 2021, he was a Visiting Scholar at the Medical Ultrasound Engineering (MUSE) Lab in the Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China, working with Prof. Jianwen Luo (Chang Jiang Scholar Chair Professor).

Research Focus: AI-driven medical imaging and intelligent computing. Core expertise includes deep learning for ultrasound beamforming, ultrasound elastography, and ultrasound localization microscopy; AI-powered medical image analysis; and GPU-accelerated computing. Recent work extends to computer vision for low-altitude technology (petroleum industry and aerodynamics), large language model (LLM) quantization, and multimodal AI for healthcare applications.

Research Interests

AI for Medical Ultrasound Imaging

  • AI-powered Ultrasound Elastography: Deep learning for motion tracking, strain estimation, and unsupervised speckle tracking
  • Ultrasound Localization Microscopy (ULM): Complex-valued networks for tissue clutter filtering, microbubble localization, and super-resolution imaging
  • Deep Learning for Ultrasound Beamforming: Neural network-based beamforming and signal processing
  • Knowledge Distillation: Resource-efficient ultrasound elastography with curriculum learning

AI-Powered Medical Image Analysis

  • Cardiac Image Analysis: Multi-view echocardiography classification, hypertrophic cardiomyopathy and cardiac amyloidosis diagnosis
  • Neurological Disorders: Alzheimer's disease early diagnosis with multimodal fusion, fMRI-based chronic insomnia classification
  • Vascular Imaging: Intracranial aneurysm detection and segmentation using geometric topological analysis networks
  • Multimodal AI: ECG-text fusion, contrastive learning for medical diagnosis

GPU-Accelerated Computing

  • 3D Ultrasound Elastography: GPU-accelerated coupled subsample estimation for volumetric breast imaging
  • Real-time Processing: High-performance computing for real-time ultrasound signal processing and image reconstruction
  • CUDA Optimization: Parallel algorithm design and performance optimization for medical imaging

Computer Vision for Low-Altitude Technology & Energy

  • Aerodynamics: Deep learning for iced airfoil prediction, wind tunnel ice crystal analysis, 3D point cloud processing
  • Petroleum Industry: Seismic data processing, drilling condition recognition, bubble segmentation in gas-liquid flow
  • Video Analysis: Video anomaly detection, infrared small target detection with contrast-enhanced networks
  • Traffic Prediction: Multi-scale information fusion networks for long-term traffic forecasting

Efficient AI & Large Language Models

  • LLM Quantization: Gradient-aware LoRA fine-tuning, efficient LLM deployment (GA-LoftQ)
  • Knowledge Graph + LLM: Entity similarity RAG for precise knowledge retrieval
  • Model Compression: Knowledge distillation, dynamic pruning for resource-efficient AI
  • Efficient Deep Learning: Curriculum learning, lightweight network design

Selected Publications

An Automated Heart Shunt Recognition Pipeline Using Deep Neural Networks
W. Wang, H. Zhang, Y. Li, Y. Wang, Q. Zhang, G. Ding, L. Yin, J. Tang and B. Peng
Journal of Digital Imaging, Informatics in Medicine, 2024
JCR Q1SCI
Convolutional Neural Network-based Speckle Tracking for Ultrasound Strain Elastography: An Unsupervised Learning Approach
S. Wen, B. Peng, X. Wei, J. Luo and J. Jiang
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol.70, No.5, pp. 354-367, May 2023
JCR Q1SCI
A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography
B. Peng, Y. Wang, T. J. Hall and J. Jiang
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 64, No. 4, pp. 694-705, April 2017
JCR Q1SCI
Relative Elastic Modulus Imaging Using Sector Ultrasound Data for Abdominal Applications
B. Peng, Y. Wang, W. Yang, T. Varghese and J. Jiang
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 63, No. 9, pp. 1432-1440, Sept. 2016
JCR Q1SCI
Building an open-source simulation platform of acoustic radiation force-based breast elastography
Y. Wang, B. Peng, J. Jiang
Physics in Medicine & Biology, 2017, 62(5): 1949-1969
JCR Q1SCI
Neural Network-based Motion Tracking for Breast Ultrasound Strain Elastography
B. Peng, Y. Xian, Q. Zhang and J. Jiang
Ultrasonic Imaging, 2020, 42(2): 74-91
JCR Q3SCI
基于光线追踪的实时超声模拟与虚拟现实的集成
彭博, 汪强, 青芮冰，尹立雪，姜劲枫
系统仿真学报，2022, 34(11): 2425-2436
CSCD 核心

View all publications on Google Scholar

Journal Reviewer

IEEE Transactions on Medical Imaging
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Pattern Recognition
Medical Physics
Ultrasonics
Computational and Mathematical Methods in Medicine
Journal of Healthcare Engineering
Medical & Biological Engineering & Computing

Students

Ph.D. and Master's Opportunities

Ph.D. Program

Discipline: Low-Altitude Technology and Engineering

Research Directions:

  • Computer Vision for Low-Altitude Technology & Energy
  • GPU-Accelerated Computing
  • Efficient AI & Large Language Models

Master's Programs

Disciplines: Computer Science and Technology, Software Engineering, Low-Altitude Technology and Engineering

Research Directions:

  • AI for Medical Ultrasound Imaging
  • AI-Powered Medical Image Analysis
  • GPU-Accelerated Computing
  • Computer Vision for Low-Altitude Technology & Energy
  • Efficient AI & Large Language Models

How to Apply: Interested students are encouraged to send your CV, transcripts, and a brief research statement to [Click to reveal email]

What We're Looking For

  • Strong background in computer science, mathematics, or related fields
  • Programming skills in Python, C++, or similar languages
  • Interest in medical imaging, deep learning, or low-altitude technology
  • Good English communication skills for academic writing
  • Self-motivated and able to work independently
Recent Graduates (2024-2026) 14 students
2025Jiajun Cai
Ph.D. @ 重庆大学
2025Wenzhao Han
Ph.D. @ Nagoya University
2025Tianqiang Xiang
@ 四川银行总行
2025Yihong Zhu
@ 中国空气动力研究与发展中心
2025Xiaofeng Li
@ 绵阳师范学院
2025Yuting Zhang
@ 深圳中科飞测股份有限公司
2025Xinyue Zhang
@ 成都天奥测控技术有限公司
2025Zhiyong Chen
@ 深圳中科飞测科技股份有限公司
2025Yuhao Xia
@ 成都天奥信息科技有限公司
2025Xinyu Li
@ 熊谷加世电器有限公司
2024Yaqiong Xiao
@ 中信银行成都软件开发中心
2024Yuqi Jiang
@ 西华师范大学网络与信息化管理中心
2024Weidong Wang
@ 烜翊数智（上海）科技有限公司
2024Weikang Hou
Ph.D. @ Kobe University

Undergraduate Students

2021Zeying Liu
University of Birmingham, UK
2021Ziyuan Cao
Tokyo Metropolitan University, Japan