ICBET 2026          Full Paper Submission Deadline: 05 April, 2026     Conference Dates: 12th - 15th June 2026      Conference Place: Bali, Indonesia


CONFERENCE TO BE HELD IN

Bali, Indonesia


CO-SPONSORED BY

   

PATRONS




KEYNOTE SPEAKERS

 

 

Chair Prof. Ying Xu (AAAS Fellow and IEEE Fellow)

Southern University of Science and Technology, China

Ying Xu is a Chair Professor in the School of Medicine, Southern University of Science and Technology, China since January 2023. He is also a Cheungkong Scholar Chair Professor (2008 -) and Qianren Chair Professor (2012 -). Before that, he was a Regent Professor and the Georgia Research Alliance Eminent Scholar Chair in the Department of Biochemistry and Molecular Biology (2003 – 2022/12) and the Founding Director of the Institute of Bioinformatics, the University of Georgia, USA (2003-2011). He is an AAAS Fellow and an IEEE Fellow. He has been a computational biologist since 1993 when he joined the Oak Ridge National Laboratory to take part in the Human Genome Project, where he worked for ten years and moved up the career ladder from a research associate to a senior staff scientist and group leader. He has published over 400 research papers and five books, including the world's first monograph “Cancer Bioinformatics”. His H-Index is 73 with more than 21000 citations in scholar.google. He received his Ph.D. in theoretical computer science from the University of Colorado in 1991 and earlier degrees from Jilin University, China.

 

INVITED SPEAKERS

 

Prof. Nini Rao

University of Electronic Science and Technology of China, China

Professor Nini Rao received her B.A., M.S. and Ph.D. degrees from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 1983, 1989, and 2009 respectively. Since 1989, she has been engaged in teaching and research in UESTC, during which, she made academic visiting at University of Bradford in UK, National University of Singapore and University of Georgia in USA and Harvard Medical School/Massachusetts General Hospital in 1997-1998, 2006, 2008 and 2016 respectively. Prof. Rao was honored with the expert obtaining the special allowance of State Council, academic and technical leader in Sichuan province and outstanding expert with outstanding contribution to Sichuan province in 2024, 2021 and 2005 respectively. She received more than 30 research grants and published more than 170 papers, and acquired a third-class prize of progress of science and technology of Sichuan Province in 2012. Her current research interests include Biomedical signal/image processing and Bioinformatics.

Speech Title:"Recurrence and Survival Prediction of Postoperative Colorectal Cancer Liver Metastasis Patients based on Multimodal Data"

Abstract: Postoperative colorectal cancer liver metastasis (PCRLM) patients have high recurrence and low survival rates, severely affecting patient 's quality of life. Prediction of recurrence and survival will help doctors make treatment decisions and so will reduce the risk of death for PCRLM patients. This study is to develop non-invasive, multimodal data-driven methods for enhancing prognosis prediction accuracy in PCRLM patients. Methods: The mutual information, Spearman correlation, and recursive feature elimination technologies were used to screen recurrence-related clinical and radiomics features and then logistic regression classifier is used to construct a recurrence prediction model. Univariate and multivariate COX regression models are further applied to analyze long-term recurrence risk and survival risk, examining the relationship between recurrence risk and time. Results: The recurrence prediction model's AUCs in 1, 2, 3, and 5-year recurrence time surpass other related models. The recurrence risk analysis showed that high-risk patients commonly recurred within 2 years, whereas low-risk cases had extended recurrence times. The proposed survival risk model has a C-index outperformed the comparison methods. The extrahepatic diseases and the liver’s residual feature from CT images are two key recurrence and survival risk prediction factors.

 

Assoc. Prof. Md Nurunnabi

University of Mississippi, USA

Visiting Professor, Korea National University of Transportation, South Korea

Md Nurunnabi recently relocated to Korea with acceptance of Brain Pool Fellowship sponsored by NRF-Korea to join the College of Engineering at Korea National University of Transportation. Previously, he worked as an Assistant professor at University of Texas at El Paso, and as an Associate Professor at University of Mississippi. Prior to starting his faculty career in 2019, he has completed a postdoctoral training at Harvard and received his MS+PhD from Korea National University of Transportation. Prof. Nurunnabi has published over 100 peer-reviewed articles, and inventor of over 20 patents, that generated over 6000 citations with an H-index of 42. Currently he is in the editorial board of several journals including ACS Biomaterials Science & Engineering, ACS Applied Nano Materials, Journal of Controlled Release, and Drug Delivery and Translational Research. Over the years, he has generated more than US$ 10M research grants from federal, state and private sponsors, and led to form several biotech/biomed start-ups.

 

Dr. Neha

Kent State University, USA

Dr. Neha is an Instructor of Artificial Intelligence in the Department of Computer Science at Kent State University and holds a Ph.D. in Computer Science from Kent State University, USA. She has over seven years of experience in research, teaching, and academic service. Her work spans artificial intelligence, computer vision, biomedical image analysis, and data-driven healthcare. Her research focuses on deep learning and multimodal AI frameworks integrating CT radiology, radiomics, and pathology-derived features to improve diagnostic accuracy and interpretability for small renal masses and renal cell carcinoma (RCC) subtypes. She has developed pipelines for imaging–radiomics–pathology integration, multimodal fusion, graph-based tumor analysis, and explainable AI to support transparent clinical decision-making. Neha has published and presented in leading medical imaging and AI venues, earning multiple best paper and best presentation awards. She teaches undergraduate and graduate courses in Artificial Intelligence, Advanced Database System Design, Web Programming, and Data Structures. She is the author of the Springer book A Beginner’s Guide to Generative AI and actively contributes to the research community through journal reviewing and conference service. She is a member of IEEE, the IEEE Computer Society, ACM, and MICCAI.

 

 

 

 

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