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CONFERENCE TO BE HELD IN
Bali, Indonesia
CO-SPONSORED BY
PATRONS
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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.
Prof. Qiang Li
Shenzhen University General Hospital, China
Prof. Qiang Li is a Professor, Chief
Physician, MD, doctoral supervisor, and post-doctoral
supervisor, serving as Director of the Department of
Internal Medicine and Director of the Department of
Endocrine and Metabolic Diseases. He has served as an
editorial board member or deputy editor-in-chief of 12
national planning textbooks, including undergraduate
Internal Medicine (8th–10th editions), eight-year Internal
Medicine (3rd–4th editions), graduate Endocrine Internal
Medicine (2nd–3rd editions), and resident physician
Endocrine Division of Internal Medicine. He is the lead
author of 3 expert consensus or guidelines and has
participated in 20 guidelines or expert consensus documents.
He has led and completed 12 National Natural Science
Foundation projects as well as provincial and
ministerial-level projects. He was awarded the first batch
of second-level professors in Heilongjiang Province and has
trained 116 postdoctoral, doctoral, and master's degree
holders. He has also served as Vice President of the
Endocrine Metabolism Branch of the Chinese Geriatrics
Association, Vice Chairman of the Diabetes Professional
Committee of the Chinese Medical Education Association, the
10th Standing Committee Member of the Endocrine Society of
the Chinese Medical Association, and Standing Committee
Member (1st–4th sessions) of the Endocrine Metabolism Branch
of the Chinese Medical Doctor Association. He has been
honored as an Excellent Teacher in Guangdong, Good Doctor in
Guangdong, Famous Doctor of Lingnan, and Famous Doctor of
Heilongjiang.
Speech Title: "Breakthrough in
Continuous Glucose Monitoring (CGM) from 14 to 21 Days:
Results of a Multicenter Clinical Trial"
Abstract: Objective: To evaluate the
accuracy and safety of the 21-day continuous glucose
monitoring system for dynamic glucose monitoring using venous
blood glucose levels as the reference standard. Methods: A
prospective, multicenter, single-arm target value clinical
trial was carried out at three Chinese research centers.
Diabetic subjects wore the TX-21 system, and venous blood
glucose measured by an EKF glucose/lactate analyzer was the
reference. Primary efficacy endpoints included 20/20%
concordance rate, Clarke and Consensus Error Grid Analysis
(A+B proportions), and mean absolute relative difference
(MARD). Secondary endpoints covered other concordance rates,
alarm accuracy, sensor performance, repeatability, lifespan,
usability; safety endpoints were adverse events and device
deficiencies. Results: 70 diabetic subjects (75.36% type 1,
24.64% type 2 diabetes) were enrolled, with 2173 valid CGM-EKF
pairs collected. For primary efficacy endpoints, the 20/20%
concordance rate with the reference value was 93.79% (95% CI
lower limit: 92.69%), Clarke Error Grid Analysis A+B
proportion 99.40% (95% CI lower limit: 98.98%), Consensus
Error Grid Analysis A+B proportion 100% (95% CI lower limit:
99.83%), and MARD 8.225±2.493% (95% CI upper limit: 8.824%);
all met the predefined target values. Secondary endpoints
showed strong performance in concordance rates, hyperglycemia
(99.26%) and hypoglycemia (96.41%) detection. The sensor was
stable for 21 days (median lifespan) with 6.43% cumulative
failure rate and good repeatability (PARD 7.590±8.761%);
usability was rated good. 5 adverse events (5.71% incidence)
occurred in 4 subjects, all unrelated to the device; no
serious adverse events or device deficiencies were reported.
Conclusion: The 21-day continuous glucose monitoring system
TX-21 demonstrates favorable accuracy, stable performance, and
reliable safety, with broad applicability across different
types of diabetes and various blood glucose ranges.
Prof. Gang Liu
Huazhong University of Science and
Technology, China (AIMBE Fellow)
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. Wenjun Hu
Huazhong University of Science and Technology,
China
Dr. Wenjun Hu, Associate Professor and
Doctoral Supervisor at the School of Life Science and
Technology, Huazhong University of Science and Technology
(HUST). Dr. Hu received his Ph.D. from Kyoto University,
Japan. He serves as an Academic Committee Member of the
Advanced Sensor Professional Committee of the Chinese Society
for Optical Engineering (CSOE), and as an Executive Committee
Member of the Hubei Provincial Biomarkers Committee. Research
Focus: Dr. Hu's primary research interests include: (1)
Metasurface plasmonic imaging principles; and (2) Development
of high-end instrumentation and medical equipment. His work
specifically focuses on analyzing biomolecular and cellular
interactions on plasmon resonance three-dimensional
biomolecular nano-fused array sensors by integrating
bright-field microscopic color imaging, digital dynamic image
processing, and AI-powered machine learning image analysis.
Dr. Hu has published dozens of SCI-indexed papers as first
author or corresponding author in high-impact international
journals including Advanced Functional Materials, PNAS, and
Biosensors & Bioelectronics. He has led 2 projects funded by
the National Natural Science Foundation of China (NSFC) and
participated in multiple major research programs including the
National Basic Research Program of China (973 Program). Dr. Hu
currently serves as a Project Review Expert for the NSFC, and
as a Young Editorial Board Member for The Innovation and other
SCI-indexed journals.
Speech Title:"Development and
Application of Metasurface-Based Plasmonic Biosensing Chips"
Abstract: Optical metasurfaces are
typically composed of arrays of miniaturized units, with both
their dimensions and the inter-unit spacing being
significantly smaller than the incident wavelengths.
Scientists can manipulate the propagation of transmitted or
reflected waves by exploiting the phase variations generated
by these units along the plane of the metasurface. We
currently focuse on metasurface plasmon resonance (Meta-SPR)
array sensors, employing an integrated approach that combines
spectral analysis or bright-field microscopic color imaging
with digital dynamic image processing and AI-powered machine
learning image analysis to detect disease biomarker molecules.
This enables the development of portable detection devices
with sensitivities reaching picograms per milliliter (pg/mL)
or even femtograms per milliliter (fg/mL). In recent years, we
have also expanded into novel Meta-SPR metasurface analytical
scenarios, such as cell membrane surface affinity analysis and
cell adhesion mechanics analysis. These tools and
methodologies allow us to better observe the membrane
biological and mechanical characteristics of cells.
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.
Asst. Prof. Arathyram Ramachandra Kurup
Sasikala
University of Bradford, UK
Dr. Arathyram Ramachandra Kurup Sasikala is
an Assistant Professor in Formulation Science at the
University of Bradford, UK, and a UKRI Future Leaders Fellow.
She obtained her PhD in Bionanosystem Engineering from Jeonbuk
National University, South Korea, in 2016, where she developed
advanced nanoformulations for cancer theranostics integrating
magnetic hyperthermia, stimuli-responsive drug delivery, and
magnetic resonance imaging. Following her PhD, she was awarded
the Young Investigator Award from the National Research
Foundation of Korea to develop a self-powered smart stent for
cardiovascular applications. In 2020, she joined the
University of Birmingham as a Marie Skłodowska-Curie Fellow,
where she developed nanoparticle-based strategies for the
non-invasive modulation of the blood–brain barrier to enhance
therapeutic delivery to the brain. She subsequently
established her independent research programme at the
University of Bradford, securing over £2.9M in competitive
funding, including the UKRI Future Leaders Fellowship, EPSRC,
and Royal Society grants. Her research now focuses on
pioneering the emerging field of piezoelectroceutics,
developing self-powered biomaterials and nanotherapeutic
platforms for regenerative medicine, cancer treatment, and
bioelectronic healthcare applications. Dr. Sasikala has
published in leading journals, including Advanced Functional
Materials, Nano Energy, and Acta Biomaterialia (h-index 19;
>1,500 citations), and has developed translational
technologies that have been patented and licensed to industry.
She leads an interdisciplinary research group working at the
interface of materials science, engineering, and biology, with
a focus on translating advanced materials into clinically
relevant healthcare solutions.
Speech Title:"Designing Smart
Nanomaterials for Advanced Therapeutic Applications"
Abstract: The rapid advancement of
nanomaterials science and engineering has driven the emergence
of smart materials with multifunctional capabilities for
disease diagnosis, prevention, and therapy. By integrating
advanced nanoformulation strategies and precise surface
functionalisation, we have engineered nanomaterial platforms
with finely tuned physicochemical, electrical, and biological
properties, enabling highly controlled therapeutic
performance. In this talk, I will present our latest work on
the rational design of smart nanomaterials for cancer
theranostics and regenerative medicine, highlighting how
stimuli-responsive systems, targeted delivery, and
non-invasive activation strategies can overcome key biological
barriers and enhance therapeutic precision. I will also
discuss emerging concepts in self-powered and externally
controlled therapeutic platforms, and their potential to
transform next-generation healthcare technologies.
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