Registration

  • KEYNOTE SPEAKERS

     

 

 

Keynote Speaker I

Prof. Yudong Zhang (Fellow of IET, EAI, and BCS, h-index: 81)

University of Leicester, UK

 

Prof. Yudong Zhang serves as a professor at the School of Computing and Mathematical Sciences, University of Leicester, UK. His research interests include deep learning and medical image analysis. He is the Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was the 2019 & 2021 recipient of Highly Cited Researcher by Clarivate. He has (co)authored over 400 peer-reviewed articles in the journals JAMA Psychiatry, Inf Fus, IEEE TFS, IEEE TII, IEEE TIP, IEEE TMI, IEEE IoTJ, Neural Networks, IEEE TITS, Pattern Recognition, IEEE TGRS, IEEE JBHI, IEEE TCSVT, IEEE TETCI, IEEE TCSS, IEEE JSTARS, IEEE TNSRE, IEEE SJ, ACM TKDD, ACM TOMM, IEEE/ACM TCBB, IEEE TCAS-II, IEEE JTEHM, ACM TMIS, etc. There are more than 50 ESI Highly Cited Papers and 5 ESI Hot Papers in his (co)authored publications. His citation reached 21143 in Google Scholar (h-index 81). He has conducted many successful industrial projects and academic grants from NIH, Royal Society, GCRF, EPSRC, MRC, Hope, British Council, and NSFC. He has given over 120 invited talks at international conferences, universities, and companies.

 

Speech Title: "AI Techniques for COVID-19 Diagnosis"

 

Abstract: COVID-19 is a pandemic disease that caused more than 6.41 million deaths until 4/Aug/2022. A CT scan is a medical imaging technique used in radiology to get detailed images of the body noninvasively for diagnostic purposes. Chest CT imaging can provide higher sensitivity diagnosis than real-time RT-PCR, so it is particularly useful for clinically suspected patients. This talk will discuss the recent AI models and techniques for chest CT-based COVID-19 diagnosis. Two other chest-related diseases: secondary pulmonary tuberculosis and community-acquired pneumonia, will be covered in this talk.

 

 

Keynote Speaker II

Prof. Stephen Kwok-Wing Tsui (h-index: 56)

The Chinese University of Hong Kong, Hong Kong

 

TSUI Kwok-Wing Stephen is currently a Professor and the Associate Director (Research) in the School of Biomedical Sciences. He is also the Director of Hong Kong Bioinformatics Centre in the Chinese University of Hong Kong (CUHK). In 1995, he received his PhD degree in Biochemistry at CUHK. He was then appointed as an Assistant Professor in the Biochemistry Department in 1997 and promoted to the professorship in 2004. He was also a former member of the International HapMap Consortium and worked on the single nucleotide polymorphisms of human chromosome 3p. During the SARS outbreak in 2003, his team was one of the earliest teams that cracked the complete genome of the SARS-coronavirus and facilitated the emergence of real-time PCR assay for the virus. Totally, he has published more than 240 scientific papers in international journals, including Nature, Nature Machine Intelligence, New England Journal of Medicine, Lancet, PNAS, Nucleic Acids Research, Genome Biology and Bioinformatics. His h-index is 56 and the citations of his publications are over 20,000. His major research interests are next generation sequencing, bioinformatics and metagenomics in human diseases.

 

Speech Title: "Genomics Study Reveals Insights into the Divergent Evolution and Comprehensive Allergen Profiles of Astigmatic Mites"

 

Abstract: Highly diversified astigmatic mites comprise many medically important human household pests such as house dust mites causing ∼1-2% of all allergic diseases globally. However, their evolutionary origin and diverse lifestyles have not been illustrated at the genomic level, which hampers allergy prevention and our exploration of these household pests. Using six high-quality assembled and annotated genomes, this study thoroughly explored the divergence of Acariformes and the diversification of astigmatic mites. Within astigmatic mites, a wide range of gene families rapidly expanded via tandem gene duplications. Gene diversification after tandem duplications provides many genetic resources for adaptation to sensing environmental signals, digestion, and detoxification in rapidly changing household environments. Throughout the evolution of Acariformes, massive horizontal gene transfer events occurred in gene families enable detoxification and digestive functions and provide perfect drug targets for pest control. This genomics study sheds light on the divergent evolution and quick adaptation to human household environments of astigmatic mites and provides insights into the genetic adaptations and even control of human household pests. Moreover, in this talk an innovative and efficient way to unveil the comprehensive allergen profiles of astigmatic mites will be described.

 

 

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INVITED SPEAKERS

 

Invited Speaker I

Assoc. Prof. Lin Meng

Tianjin University, China

 

Lin Meng received her Ph.D. degree from the Division of Biomedical Engineering, University of Glasgow, Glasgow, U.K., in 2016 and worked as a Research Associate at the Department of Biomedical Engineering, University of Strathclyde, Glasgow, UK from 2016 and 2018. Lin is currently an Associate Professor with Academy of Medical Engineering and Translational Medicine, Tianjin University, China. She has worked in multidisciplinary research involving neuroscience, robotic control, and human motor rehabilitation and published about 30 peer-reviewed articles on high impact international journals such as IEEE TBME, IEEE Sensors Journal, etc. Her current research interests include human motion analysis, neuro-motor control mechanism, lower-limb assistive and rehabilitation robot, human early detection of cognitive and motor decline based on wearable sensors.

 

Speech Title: "Intelligent Assessment Method and its Application in Motion Rehabilitation"

 

Abstract: Patients with neurological diseases would suffer motor dysfunctions which severely affect their activity living ability. Clinical rating scale methods are commonly used for motor assessment based on which the rehabilitation protocol is developed to help people regain their motor functions. However, the traditional methods lack of quantitative measurement resulting in low inter-assessor reliability and low sensitivity for patients' subtle changes. This talk will introdue intelligent motor assessment methods based on inertial sensors and electromyography and discuss the applications in early-stage Parkinson's disease identification and motor assessment in stroke.

 

Invited Speaker II

Assoc. Prof. Jie Luo

Shanghai Jiao Tong University, China

 

Jie Luo is a tenure-track associate professor at Shanghai Jiao Tong University. She received PhD in Chemistry from Washington University in St. Louis, and completed postdoctoral fellowships at Massachusetts Institute of Technology and Boston Children's Hospital. She is a Junior Fellow of the International Society for Magnetic Resonance in Medicine (ISMRM), and has received funding support from the National Science Foundation of China, and the Ministry of Technology and Sciences in China. Her research centers around metabolic and physiological imaging approaches, and fusion of multimodality data with clinical applications in neurological diseases, such as lesion detection and surgical outcome prediction for drug-resistant epilepsy.

 

Speech Title: "Multimodal Brain Imaging for Temporal Lobe Epilepsy using Integrated PET-MR"

 

Abstract: Temporal lobe epilepsy (TLE) is the most common in drug refractory epilepsy. Presurgical evaluations for TLE subjects is critical for successful treatment planning. Brain imaging has played a critical role in lesion detection and localization for epileptic brain for decades. With technical advances, we could map the whole brain not only in structural, but in functional and metabolic mappings. Here in this talk, we present our recent work on brain imaging for epilepsy patients with integrated PET/MR system. Synergies between PET and MR relaxometry, functional MRI, and MR spectroscopy, are discussed in the context of lesion detection for epilepsy. Improvements in diagnostic accuracy and disease progression prediction manifested via machine learning and multimodal brain imaging technologies.

 

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Keynote Speaker of ICBBE 2021

 

 

Keynote Speaker I

Prof. Nicola Mulder

University of Cape Town, South Africa

 

Prof Mulder heads the Computational Biology Division at the University of Cape Town (UCT), and is a full member of the Institute of Infectious Disease and Molecular Medicine. She leads H3ABioNet, a large Pan African Bioinformatics Network of 28 institutions in 17 countries, which aims to develop bioinformatics capacity to enable genomic data analysis on the continent. H3ABioNet has developed an extensive training program for African researchers. She also co-leads a Sickle Cell Disease Data Coordinating Centre and a Wellcome Trust Centre Data Integration Platform at UCT. She received her PhD in Medical Microbiology from the University of Cape Town and then worked for 8.5 years at the European Bioinformatics Institute in Cambridge, as a Team Leader. At UCT her research focuses on genetic determinants of susceptibility to disease, African genome variation, and microbial genomics and infectious diseases from both the host and pathogen perspectives. Her group provides bioinformatics services and training and develops new algorithms and resources for the analysis of complex African genetic data. Prof Mulder is actively involved in capacity development, including training, education and curriculum development in Bioinformatics. She also sits on a number of international scientific advisory boards.

 

Speech Title: "Leveraging Bioinformatics Capacity to Study African Genomics and Disease"

 

Abstract: African populations are known to harbour the greatest genetic diversity on earth. Studying African genetic diversity has the potential to improve our understanding of the genetic basis for many diseases not only in Africa, but for global populations. However, data from African populations is still relatively sparse, and the tools and skills for analyzing the data have been lacking on the continent. The H3Africa consortium, established more than 8 years ago, has changed the landscape of African genomics through the generation of large datasets to study the genetic and environmental basis for diseases. H3ABioNet, the consortium’s pan African bioinformatics network, has helped to build the capacity and tools to enable analysis of the data on the continent. This talk will discuss some of the challenges in studying African genomics, how these are being overcome, and some of the new tools being developed to interrogate the data. Analysis of an H3Africa dataset of whole genome sequences will be presented, along with a discussion on the potential health applications.

 

Keynote Speaker II

Prof. Dong Sun, Fellow of CAE, IEEE and HKIE

City University of Hong Kong, Hong Kong

 

Dr. Dong Sun is currently the head and Chair Professor of the Department of Biomedical Engineering and Director of the Center for Robotics and Automation, City University of Hong Kong. He is among the leading contributors worldwide in pioneering work in robotic manipulation of biological cells. His research has breakthrough in the use of combined robotics and various micro-engineering tools including optical tweezers, microneedles and electromagnetic devices to achieve cell manipulation, diagnosis and micro-surgery at the single cell level. He has published 20 books and book chapters, 440 papers in referred journals and conference proceedings, and holds 20 international patents. Dr. Sun organized several international flagship conferences including the world largest intelligent robot conference (IROS). Dr. Sun also actively participated in industrial activities, such as co-founding a high-tech company in the Hong Kong Science and Technology Park and winning Hong Kong Industry Awards. He is Fellow of the Canadian Academy of Engineering, and Fellow of IEEE and HKIE.

 

Speech Title: "Microrobotic Manipulation for Cell Therapy"

 

Abstract: The application of robot technology to achieve early diagnosis and treatment of diseases at the cellular level represents a new frontier in the development of contemporary medical robots. Microrobotic manipulation for cell therapy is an entirely new emerging theme that is enabled with specially designed automated micromanipulation tools to perform medical diagnosis and treatment on single cells at large scale. This talk will introduce our development of combining robotics technologies with micro-manipulation tools including optical tweezers, microneedles and electromagnetic devices, to accomplish various cell manipulation tasks. With this emerging technology, various cell surgical operations can be achieved, which include the use of magnetic microrobots to deliver cells in vivo. These inventions will permit many new unforeseen clinical applications previously thought impossible, and profoundly affect therapeutic treatment in precision medicine.