PROGRAM OVERVIEW

This program will equip students with solid theoretical and systematic professional knowledge in molecular medicine, biomedical engineering, and related fields. Graduates of this program will have the opportunity to undertake independent scientific research, allowing them to understand the current status and future trends of medicine/biomedical engineering, and write and communicate in English.

MAIN RESEARCH FIELDS:

1. Biomedical information

Apply biomedical engineering techniques and methods to collect, analyze and evaluate health-related biomedical information, establish disease risk prediction and early warning models, explore the underlying reasons of disease pathogenesis, and conduct intervention studies.

2. Cell and tissue engineering

Conduct research on various types of stem cell and bioscaffold materials, and learn how to apply tissue engineering and regeneration technologies to acute and chronic injuries and diseases; conduct research using cell engineering and nanomaterial labeling technologies based on modern gene technology; perform in vivo and in vitro cell tracing and monitoring; and develop new sources of stem cells for research and industrialization amplification technologies, including the development of 3D culture and amplification and bioreactor systems.

3. Systematic Biomedical:

Harness biophysical, biochemical, bioinformatic and systems biology approaches to study human aging and major diseases such as cancer, cardiovascular and cerebrovascular diseases, metabolic diseases, and infectious diseases; use cells, tissues, organs to conduct translational medicine research into human disease mechanisms at multiple levels, and develop personalized and precise diagnostic and treatment approaches.

CORE COURSES

Frontiers in Biomedical Engineering, Biomedical Image Analysis, Lecture on Pattern Recognition Front, Advanced Cell Biology and Disease, Biochemistry and Molecular Biology.

CAREER PROSPECTS

There is a wide spectrum of career paths that can follow from obtaining a PhD in Biomedical Engineering, including but not limited to:

Biomedical Scientist/ResearcherBiomedical scientists and researchers, in both clinical and/or research environments, conduct research that aims to improve human health by carrying out scientific tests to find solutions to medical/clinical problems. They research information that aids in the development of biomedical technology and test products so that they are safe and effective for consumers.

Biomaterials DeveloperBiomedical engineers may develop biomaterials based on either natural living tissue or artificial materials, for use in the human body. Tissue engineering, biomedical implant development, drug delivery and nano implants are all areas that a biomaterials developer may work in. Biomaterials can be used to either repair or replace lost function to the body, or to detect and image disease.

Biomedical Artificial Intelligent (AI) Researcher or Developer AI technology is rewiring many parts of society. How medical/clinical procedures and philosophies will be affected by AI is a thrilling frontier for exploration. A career in this field will involve you not only in science and technology, but also in areas of ethics, finance, and regulation.

Rehabilitation EngineerBiomedical engineers who work in a field dedicated to rehabilitation often work on diverse projects. These can range from mechanical equipment that helps patients regain the ability to walk, to virtual reality systems that aid in limb mobility. Rehabilitation engineers may also create custom solutions based on unique needs or research improvements that can form the basis of a novel rehabilitation technology.

Medical Device/Technology Developer

Medical technology can refer to the hardware and software that help manufacture medical devices, as well as to the technology that is an integral part of those devices. Medical technology professionals with biomedical engineering backgrounds may specialize in bioinstrumentation, or the use of bioelectronic/biomechanical/biochemical instruments to record or transmit physiological information in vivo and/or in vitro.

Consultation

Email:   [email protected]                

英文名

Chunqi Chang

聯系郵箱

[email protected]

中文簡介

特聘教授，博士生導師。2002-2012年歷任香港大學博士后、副研究員、助理教授、訪問教授，2012年-2015年任蘇州大學特聘教授，2015年入職深圳大學。目前任廣東省認知學會常務理事，深圳大學神經系統疾病臨床醫學研究中心副主任。主要使用多模態神經信息采集、神經調控、類腦模擬、機器學習等手段在細胞、動物、人類多個角度進行微觀、介觀、宏觀方面的腦科學基礎及臨床應用研究.在國際知名學術期刊及國際會議發表論文100余篇，SCI收錄80余篇。

英文簡介

Dr Chunqi Chang, PhD supervisor. He received the B.Eng. and M.Eng. degrees in electronic engineering from the University of Science and Technology of China, Hefei, China, in 1992 and 1995, respectively, and the Ph.D. degree in biomedical engineering from the University of Hong Kong, Hong Kong, in 2001. From 2002 to 2012, he was with the University of Hong Kong where he was a Post-Doctoral Fellow, a Research Associate, a Research Assistant Professor with the Department of Electrical and Electronic Engineering, and a Visiting Professor with the State Key Lab of Brain & Cognitive Sciences. From 2012 to 2015, he was a Professor in the School of Electronics and Information Engineering, Soochow University, Suzhou, China. Since 2015 he has been a Professor in School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China. His current interest is on basic brain science research on neuron networks (and brain organisms), animal models and human brains at micro-meso-macro scales using multi-modal neural information measurements, neural regulation, brain simulation, and machine learning techniques, with clinical applications. He has published more than 100 research papers (80+ SCI cited).

英文名

Gan Huang

聯系郵箱

huanggan@szu.edu.cn

中文簡介

黃淦，博士畢業于上海交通大學，比利時法語魯汶大學博士后。他的致力于發展運動、感受相關的魯棒神經信號解碼方法和精準神經調控技術，同時積極將研究成果應用于腦機接口，神經調控以及神經假肢等方面。個人主頁https://huanggan.site

l 在國內外高水平雜志 Neuroimage, Neural Network雜志發表論文40余篇，谷歌學術H指數為22；

l 擔任IEEE TNNLS, TNSRE, TBME, JNE, NeuroImage等多個期刊審稿人；

l 承擔國家自然科學基金2項，省市科研項目多項；

l 2021年獲教育部自然科學一等獎；

l 寫腦電信號處理軟件 Letswave7 (https://letswave.cn)。

英文簡介

Huang Gan, Ph.D., graduated from Shanghai Jiao Tong University and completed his postdoctoral fellowship at the University of Louvain in Belgium. Currently, he is an associate professor, distinguished researcher, in School of Biomedical Engineering, Health Science Center, Shenzhen University. Dr. Huang’s research primarily revolves around the development of robust neural signal decoding methods in the domains of motor and sensory functions, as well as precise neural modulation technologies. His areas of interest extend to the practical applications of scientific research, encompassing brain-computer interfaces, neural modulation, neural prosthetics, and related fields. More information could be seen in the website (https://huanggan.site)

Dr. Huang have published over 40 papers in high-impact journals both domestically and internationally, including Neuroimage and Neural Network, with an H-index of 22 on Google Scholar, and serve as a reviewer for various journals such as TNNLS, TNSRE, TBME,  JNE, and NeuroImage.

Additionally, Dr. Huang have been involved in multiple national and provincial research projects, having secured funding for two projects from the National Natural Science Foundation of China and various regional research programs. In 2021, he received the first prize in the Natural Science category from the Ministry of Education. Furthermore, he has authored the brainwave signal processing software, Letswave7 (https://letswave.cn).

英文名

Guanghui Yue

聯系郵箱

[email protected]

中文簡介

副教授，留學博士生導師。目前任廣東省醫學會人工智能分會委員。主要研究方向為3D圖像/視頻處理、圖像/視頻質量評價、醫學圖像分析、計算機視覺、機器學習及其應用等。截至目前，在領域內權威雜志/會議發表學術論文70多篇（含20多篇IEEE/ACM 匯刊文章）、授權國家發明專利16項。岳博士的谷歌學術引用1400次以上，H指數為23。他擔任二十余個國際頂級/知名期刊的學術審稿人，例如IEEE TMI/TIP/TMM/TCSVT/TII/TIE/TIM/TETCI/TNNLS/TCYB/SPL, Elsevier SP/DSP/NEUCOM/SPIC/JVCI, IET IP/EL。

英文簡介

Dr Guanghui Yue, Associate Professor. He researches broadly in the areas of 3D image/video processing, image/video quality assessment and enhancement, medical image analysis, computer vision, machine learning and its applications, etc. He has published 70+ papers in prestigious journals and conferences including 20+ papers in IEEE/ACM Transactions, and authorized 16 Chinese Invention Patents. His Google Scholar h-index is 23, and Google Scholar Citation is 1400+. Dr. Yue serves as an academic member of the artificial intelligence branch of Guangdong Medical Association. He also serves as the reviewer of many top-tier journals, such as IEEE TMI/TIP/TMM / TCSVT/TII/TIE/TIM/TETCI/TNNLS/TCYB/SPL, Elsevier SP/DSP/ NEUCOM/SPIC/JVCI, IET IP/EL.

英文名

Yu-Chao Jiang

聯系郵箱

y[email protected]

中文簡介

蔣宇超，從事人工智能和大數據、神經信息學、腦影像學與精神醫學的理工醫交叉研究，致力于神經影像技術和醫學轉化研究，基于海量生物醫學數據的大數據挖掘、統計和機器學習工具，開發基于時空概念的新型腦疾病建模方法，能夠在“時間”和“空間”兩個層面解析腦疾病的空間起源和時間進展軌跡，應用于多種腦疾病建模。以第一作者/通訊作者發表SCI論文20余篇，包括Nature Mental Health，Nature Communications，Science Advances等。

英文簡介

Dr. Jiang Yuchao is engaged in interdisciplinary research spanning artificial intelligence, big data, neuroinformatics, neuroimaging, and psychiatry. His work focuses on advancing neuroimaging technologies and translational medicine through the development of innovative modeling approaches for brain disorders, based on spatiotemporal concepts. Leveraging large-scale biomedical data, he applies big data mining, statistical techniques, and machine learning tools to analyze the spatial origins and temporal progression trajectories of brain disorders. These methods have been applied to the modeling of various brain diseases. Dr. Jiang has authored or co-authored over 20 SCI papers as the first or corresponding author, including publications in Nature Mental Health, Nature Communications, and Science Advances.

英文名

Dong Ni

聯系郵箱

[email protected]

中文簡介

倪東教授是深圳大學生物醫學工程學院教授，2010年創辦醫學超聲圖像計算（MUSIC）實驗室。發表論文200余篇，H指數49，引用次數超過1萬次。曾任MICCAI 2019分會主席，2020年至2023年擔任MICCAI董事會成員。倪教授長期從事智能超聲的研究、臨床應用及產業轉化，是全球最早將深度學習應用于超聲影像分析的學者之一（2015年）。在超聲圖像計算領域提出多項原創性理念，包括標準切面識別、影像質量控制、三維超聲圖像分割、基于深度學習的自由臂三維超聲重建等，帶領數百人研發團隊，開發十余款超聲AI軟件，軟件全球授權超過3萬套。

英文簡介

Professor Dong Ni is the full professor of School of Biomedical Engineering, Shenzhen University. He founded the Medical UltraSound Image Computing (MUSIC) Lab in 2010. He is also the founder and chief scientist of Shenzhen RayShape Medical Technology Co., Ltd., which has become the largest supplier of Ultrasound AI software in the world. He has published more than 200 papers, with an H-index of 49 and more than 10, 000 citations. He was the local Chair of MICCAI 2019 and has served as the Board member of MICCAI society from 2020 to 2023.

Professor Ni has been involved in the research, clinical application and industrial transformation of intelligent ultrasound for a long time. He is one of the first to apply deep learning to ultrasound imaging (2015). He has put forward many original ideas in the field of ultrasound image computing, including standard plane recognition, imaging quality control, 3D ultrasound image segmentation, freehand 3D ultrasound reconstruction based on deep learning, etc. He has led a R&D team of hundreds of people and developed more than 10 ultrasound AI software. The software has been authorized for more than 30,000 sets worldwide.

英文名

Jie Du

聯系郵箱

d[email protected]

中文簡介

助理教授、博士生導師。澳門大學計算機科學專業博士。主要研究方向為醫學圖像處理與機器學習。截至目前，已發表期刊/會議論文30余篇，包括在IEEE Transactions on Cybernetics，IEEE Transactions on Neural Networks and Learning Systems，Medical Image Analysis，IEEE Transactions on Medical Imaging等中科院一區Top期刊收錄論文近20篇。谷歌學術引用900余次，H指數16。擔任IEEE TIP/TNNLS/TCYB/TII/TMI/TETCI、Elsevier NN/ESWA/KBS/NEUCOM等十余個國際知名期刊的審稿人。目前，主持國自然面上項目、青年項目、廣東省基礎研究面上項目、廣東省教育廳-青年創新人才類項目等9項科研項目。

英文簡介

Jie Du received her Ph.D. in Computer Science from the University of Macau. Then she joined the Department of Biomedical Engineering at Shenzhen University as an assistant professor. Her research interests include medical image processing and machine learning. Her works have been published in IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, Medical Image Analysis, IEEE Transactions on Medical Imaging, et al. Her Google Scholar h-index is 16, and Google Scholar Citation is 900+. Dr. Du serves as the reviewer of many top-tier journals, such as IEEE TIP/TNNLS/TCYB/TII/TMI/TETCI and Elsevier NN/ESWA/KBS/NEUCOM.

英文名

Ruobing Huang

聯系郵箱

[email protected]

中文簡介

黃若冰，副教授，深圳市海外高層次人才C類。2014年本科畢業于北京理工大學，2018年在英國牛津大學獲得博士學位，導師為英國皇家科學院/工程院院士Alison Noble教授。2019年入職深圳大學生物醫學工程學院。研究方向為醫學圖像分析及深度學習應用，專注于智能超聲輔助診斷（甲乳癌癥診斷、胎兒產前早篩等）。發表期刊/會議論文40余篇，包括在Medical Image Analysis，IEEE Transactions on Medical Imaging，MICCAI等領域國際頂刊頂會等收錄論文10余篇。主持了國家自然科學基金面上項目、青年項目、廣東省基礎與應用基礎基金面上項目等課題。

英文簡介

Dr. Ruobing Huang is an associate professor and a Class C overseas high-level talent in Shenzhen. She graduated with a bachelor's degree from Beijing Institute of Technology in 2014 and obtained her PhD from the University of Oxford in 2018, under the supervision of Professor Alison Noble, OBE FREng FRS. In 2019, she joined the School of Biomedical Engineering at Shenzhen University. Her research focuses on medical image analysis and deep learning applications, particularly in intelligent ultrasound-assisted diagnosis, including breast/thyroid cancer diagnosis and prenatal screening. She has published over 40 journal and conference papers, including more than 10 in leading international journals and conferences such as Medical Image Analysis, IEEE Transactions on Medical Imaging, and MICCAI. She has led projects funded by the National Natural Science Foundation of China, and Guangdong Province’s Basic and Applied Basic research programs.