Solange Peters | Oncology | Research Excellence Award

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Prof. Solange Peters | Oncology | Research Excellence Award

Lausanne University | Switzerland

Dr. Solange Peters is an internationally recognized medical oncologist and academic leader specializing in thoracic oncology. She serves as Director of the Oncology Department at Lausanne University Hospital and is a Full Professor at the University of Lausanne. Dr. Peters is widely known for her expertise in lung cancer, immunotherapy, and precision oncology, with a strong focus on clinical research and translational medicine. She has led and coordinated numerous international multicenter clinical trials and has contributed significantly to advancing treatment standards for thoracic malignancies. With extensive experience in medical education, she is actively involved in training oncology professionals worldwide. Dr. Peters has authored more than 500 peer-reviewed scientific publications and serves in key editorial roles for leading oncology journals. She has held prominent leadership positions in major international oncology organizations and is a strong advocate for multidisciplinary cancer care, innovation in clinical research, and the advancement of women in oncology.

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Featured Publications


Regulation of laboratory-developed tests and in-house in vitro diagnostic medical devices in the United States and the European Union—a comparative overview

– Review Article (Open Access)

Quality improvement report: Investigating barriers in HIV testing oncology patients to optimize HIV testing practice

– HIV Medicine

Tumor immune dynamics and long-term clinical outcome of stage IIIA NSCLC patients treated with neoadjuvant chemoimmunotherapy

– Nature Communications

Brief Report: Post Hoc Validation of Platinum Ineligibility in NSCLC From the Phase III IPSOS Study

– Journal of Thoracic Oncology

Transcriptome analysis of archived tumors by Visium, GeoMx DSP, and Chromium reveals patient heterogeneity

– Nature Communications

Xuan Feng | Forecasting | Research Excellence Award

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Dr. Xuan Feng | Forecasting | Research Excellence Award

EDHEC Business School | Hungary

Xuan Feng is a finance researcher and practitioner specializing in asset pricing, fixed income, investment strategies, portfolio construction, ESG, and machine learning applications in finance. He is pursuing doctoral research in finance at EDHEC Business School, focusing on risk premia, yield curve dynamics, and advanced quantitative methods. His academic background spans finance, management, international business, and engineering mechanics, providing a strong interdisciplinary foundation. Xuan’s research includes innovative work on cross-currency carry strategies, correlation forecasting in yield curves using PCA-based models, and the integration of responsible AI in financial markets. His scholarly contributions have been published in leading international journals covering financial analysis, green finance, forecasting, and applied machine learning. Alongside research, he has extensive teaching experience in portfolio management, quantitative finance, statistics, financial econometrics, and data analysis at master’s and undergraduate levels across international institutions. Professionally, he works in model risk management at a global investment bank, applying quantitative rigor to real-world financial models. Xuan also brings entrepreneurial experience from founding ventures in online education and fashion. He holds multiple global professional certifications and is proficient in advanced programming, data science, and financial modeling tools, with fluency in Chinese, English, and French.

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Featured Publications


The impact of ESG performances on analyst report readability: Evidence from China

– International Review of Financial Analysis

Machine learning approaches to predicting energy price correlation: From a responsible AI perspective

– Technological Forecasting and Social Change

Predicting Corporate Financial Risk Using Artificial Bee Colony–Attention–Gated Recurrent Unit Model

– Journal of Organizational and End User Computing

Do US Government and Commercial Media Concern Similar Topics? A Text-mining (NLP) Approach

– BOHR International Journal of Computer Science

The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode

– Journal of Global Information Management

Yasunori Aoki | Electroencephalography | Research Excellence Award

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Dr. Yasunori Aoki | Electroencephalography | Research Excellence Award

Nippon Life Hospital | Japan

Dr. Yasunori Aoki, MD, PhD, is a physician–scientist specializing in psychiatry and clinical neuroscience, currently affiliated with the Department of Psychiatry at Osaka University Graduate School of Medicine, Japan. With a strong interdisciplinary foundation, he was initially trained in physics before completing his medical education and advanced clinical neuroscience training, allowing him to integrate quantitative scientific approaches into clinical research. His academic and professional work centers on the clinical application of neurophysiological methods, particularly electroencephalography and magnetoencephalography, to better understand brain function and dysfunction. Dr. Aoki’s doctoral research focused on advanced EEG and neuronal activity topography analyses to predict treatment outcomes in neurological and psychiatric disorders, reflecting his commitment to translational research that bridges neuroscience and patient care. His research interests span psychiatry, cognitive neuroscience, and clinical neurophysiology, with particular emphasis on schizophrenia, dementia, epilepsy, autism, depression, and neurodevelopmental and neurodegenerative conditions. He is especially interested in brain oscillations, endophenotypes, resting-state networks, event-related potentials, and neuromodulation techniques such as transcranial magnetic stimulation. Through his work, Dr. Aoki aims to advance objective biomarkers and neurophysiological tools to improve diagnosis, prognosis, and therapeutic strategies in psychiatry and neurology.

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PyCaret machine learning library with three preprocessing steps after eLORETA source estimation predicts Alzheimer’s disease

– NeuroImage: Reports

EEG Oscillatory Activity and Resting-State Networks Associated with Neurocognitive Function in Mild Traumatic Brain Injury

– Clinical EEG and Neuroscience

Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

– JMIR AI

Normalized Power Variance: A New Field Orthogonal to Power in EEG Analysis

– Clinical EEG and Neuroscience

Cortical electrical activity changes in healthy aging using EEG-eLORETA analysis

– NeuroImage: Reports

Chanyuan Jin | Regeneration | Research Excellence Award

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Prof. Chanyuan Jin | Regeneration | Research Excellence Award

Peking University School and Hospital for Stomatology | China

Dr. Chanyuan Jin is an Associate Research Fellow at the Peking University School and Hospital for Stomatology, with advanced expertise in prosthodontics, stem cell biology, and regenerative medicine. She is widely recognized as a young scientific talent at both national and regional levels and leads cutting-edge research on stem cell osteogenic differentiation and bone tissue regeneration. Her work focuses on developing innovative biomaterials and tissue engineering strategies for hard and soft tissue repair, with strong translational relevance to dental and orthopedic applications. Dr. Jin has secured multiple highly competitive research grants and has authored more than 20 peer-reviewed scientific publications, along with contributions to academic book chapters. Her research excellence has been acknowledged through prestigious awards, including international recognition in tissue engineering. In addition to her academic achievements, she actively bridges industry and academia through collaborative training and research programs with leading biomedical companies, guiding postdoctoral researchers in translational and product-oriented studies. Dr. Jin also holds several patents related to medical imaging analysis, biomaterials, and regenerative technologies. She serves on editorial boards of respected international and national journals and contributes to scientific peer review and academic leadership. Through her interdisciplinary approach, clinical insight, and mentorship, Dr. Jin continues to make significant contributions to advancing regenerative dentistry and craniofacial rehabilitation.

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Dual-responsive nanoparticle system for enhanced blood-brain barrier crossing and glioblastoma penetration

– Biomaterials

Optimizing hydrogen peroxide shock treatment frequencies for dental unit waterlines contamination control: a pilot study

– BMC Oral Health

Fast response cathodic electrochemiluminescence sensor based on closed bipolar electrode for point-of-care blood glucose testing

– Talanta

High-Entropy Environments Enable Metal Surface-Catalyzed Nucleophilic Electrooxidation

– Angew Chem Int Ed Engl

Integrated trilayer nanofiber membrane with tailored antibacterial, antioxidant, and mechanical properties for accelerated infected wound healing

– Nano Research

Yifan Dai | Petroleum Engineering | Research Excellence Award

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Mr. Yifan Dai | Petroleum Engineering | Research Excellence Award

China University of Petroleum-Beijing at Karamay | China

Dr. Yifan Dai is a lecturer at the Karamay Campus of China University of Petroleum–Beijing, specializing in petroleum engineering with a strong focus on rock mechanics and unconventional reservoir development. His academic training spans bachelor’s, master’s, and doctoral studies in petroleum engineering, providing him with a solid theoretical foundation and advanced research expertise. Dr. Dai’s research centers on hydraulic fracturing, multi-physics field numerical simulation, phase-field methods, and crack propagation mechanisms in complex geological media. He has made significant contributions to understanding fracture initiation and evolution in basalt, carbonate, and volcanic reservoirs, with particular emphasis on thermal–hydraulic–mechanical–chemical coupling processes. His work integrates numerical modeling, experimental investigation, and engineering application to improve stimulation efficiency and reservoir connectivity. Dr. Dai has authored multiple peer-reviewed journal articles and conference papers in leading international venues, and he has contributed to a scholarly book in his field. He is actively involved in key laboratory research projects focused on carbon-efficient utilization and subsurface storage technologies. In addition, he serves on a young academic committee of a professional journal, reflecting his engagement with the broader research community. Through his research and teaching, Dr. Dai continues to advance innovative methodologies for fracture modeling and sustainable development of oil and gas resource

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Featured Publications


A Thermal–Hydraulic–Mechanical–Chemical Coupling Model for Acid Fracture Propagation Based on a Phase-Field Method

– Rock Mechanics and Rock Engineering

Experimental Study on Evaluation of Propped Fracture Conductivity of Conglomerate Reservoir in Baikouquan Formation of Ma-A Well Area of Xinjiang Oilfield

– SSRN

Influencing Factors of Acid Etching Fracture Conductivity of Tuff Reservoir in Northeastern Sichuan Block

– U.S. Rock Mechanics/Geomechanics Symposium

Numerical Simulation of Pores Connection by Acid Fracturing Based on Phase Field Method

– Acta Petrolei Sinica

Hydraulic Fracturing Fracture Propagation in Tight Sandstone Reservoir

– IOP Conference Series: Earth and Environmental Science

Chao Wang | Hepatobiliary | Research Excellence Award

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Dr. Chao Wang | Hepatobiliary | Research Excellence Award

Hangzhou First People’s Hospital | China

Dr. Chao Wang is a surgeon specializing in hepato-pancreato-biliary surgery and liver transplantation at The Affiliated Hangzhou First People’s Hospital of Zhejiang University, where he is actively involved in advanced clinical care, research, and surgical innovation. He received comprehensive medical training in general surgery and has developed strong expertise in liver transplantation, hepatobiliary malignancies, and pancreatic diseases. His clinical practice focuses on complex surgical management and post-transplant outcomes, integrating precision medicine into patient care. Dr. Wang’s research centers on the molecular and genetic mechanisms influencing liver transplantation outcomes, hepatocellular carcinoma recurrence, graft fibrosis, and metabolic complications following transplantation. He has authored multiple peer-reviewed publications in internationally recognized journals, addressing donor gene polymorphisms, tumor recurrence prediction models, coagulation biomarkers, non-coding RNA regulatory networks, and immunosuppressive strategies. His work demonstrates a strong translational approach, bridging molecular research with clinical application to improve prognostic accuracy and therapeutic decision-making in liver transplantation and hepatobiliary surgery. In addition to his research contributions, Dr. Wang actively participates in funded scientific projects, contributing to studies on liver fibrosis, exosome-mediated regulation, and liver injury mechanisms. His combined clinical expertise, research productivity, and commitment to improving transplant outcomes position him as a dedicated and impactful physician-scientist in the field of hepatobiliary and transplant surgery.

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Donor One-Carbon Metabolism Gene Single Nucleotide Polymorphisms Predict the Susceptibility of Cancer Recurrence after Liver Transplantation

– Gene

The MTHFR Polymorphism Affects the Susceptibility of Hepatocellular Carcinoma and the Prognosis of HCC Liver Transplantation

– Clinical and Translational Oncology

A Model Integrating Donor Gene Polymorphisms Predicts Fibrosis after Liver Transplantation

– Aging

Identification and Verification of a Novel MAGI2-AS3/miRNA-374-5p/FOXO1 Network Associated with HBV-Related Hepatocellular Carcinoma

– Cells

An Integrated Model of Fibrinogen and D-Dimer for Predicting Hepatocellular Carcinoma Recurrence Following Liver Transplantation: A Multicentre Study

– American Journal of Translational Research

Ruokun Li | Medical Imaging | Research Excellence Award | China

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Dr. Ruokun Li | Medical Imaging | Research Excellence Award

Ruijin Hospital, Shanghai Jiao Tong University School of Medicine | China

Dr. Ruokun Li is a Professor and Chief Physician in the Department of Radiology at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, and a leading expert in advanced medical imaging. He holds a PhD in Imaging and Nuclear Medicine and specializes in liver imaging, with particular expertise in magnetic resonance elastography, quantitative MRI, and artificial intelligence–driven imaging analysis. He has led numerous nationally and provincially funded research projects and has authored more than 40 peer-reviewed SCI-indexed publications, achieving a strong citation impact. His research integrates imaging physics, biomechanics, radiomics, and explainable deep learning to enable noninvasive diagnosis, risk stratification, and prognosis of liver diseases, including hepatocellular carcinoma. Actively engaged in academic–industry collaboration, he has contributed to the development of intelligent imaging platforms, digital twin systems for imaging education, and simulation-based solutions with national recognition. Dr. Li has edited, co-edited, or translated over 15 academic books in radiology and MRI technology and holds multiple invention patents in multimodal image segmentation, low-dose imaging, and predictive AI models. He serves on editorial boards of several radiology journals and holds leadership roles in international and national professional societies related to magnetic resonance and radiology, fostering global collaboration and clinical translation of innovative imaging technologies.

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An Explainable Deep Learning Model for Focal Liver Lesion Diagnosis Using Multiparametric MRI

– Radiology: Artificial Intelligence 

Preoperative Multifrequency MR Elastography for Stratifying Wnt/β-Catenin Pathway and Microvascular Invasion Phenotypes in Hepatocellular Carcinoma

– Journal of Magnetic Resonance Imaging

A Biphasic Nanoplatform with Switchable Biochemical Programs for Combined Organelle-Specific Cancer Therapy

– Chemical Engineering Journal

Blood Markers for Type-1, -2, and -3 Inflammation Are Associated with Severity of Acutely Decompensated Cirrhosis

– Journal of Hepatology ·

A Nanoplatform for Reversing the Tumor Immunosuppressive Microenvironment Based on NIR-II Gold Hollow Nanorods for the Treatment of Hepatocellular Carcinoma

– Small 

Tao Cai | System Architecture | Research Excellence Award

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Prof. Dr. Tao Cai | System Architecture | Research Excellence Award

Jiangsu University | China

Professor Tao Cai is a distinguished academic in computer science with extensive expertise in storage systems, big data, and artificial intelligence. He is affiliated with the School of Computer Science and Communication Engineering at Jiangsu University, China, where he has progressed through academic roles from teaching assistant and lecturer to associate professor and professor, reflecting a long-standing commitment to education and research excellence. He holds bachelor’s, master’s, and doctoral degrees in computer science from Jiangsu University and has developed a strong teaching portfolio that includes operating systems, big data technologies, and cloud computing. Professor Cai is an accomplished researcher, having authored more than thirty scholarly articles and secured six patents, demonstrating both theoretical and applied contributions to his field. His academic influence extends internationally through visiting scholar appointments at leading institutions, where he engaged in advanced research collaboration. He is an active member of the China Computer Society and the Jiangsu Province Computer Society, serving on professional committees related to information storage technology as well as network and distributed computing. In addition, he contributes to the academic community as an editor and reviewer for well-regarded scientific journals, supporting the advancement of high-quality research in data science and computing.

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A Stable Self-Organized Spatial Pooling Algorithm for Hierarchical Temporal Memory

– Review Paper

Heterogeneous Graph-Based HTM Temporal Memory Algorithm

– Conference Paper

CSTformer: Cross Spatio-Temporal Transformer for Multivariate Time Series Forecasting

– Conference Paper

A Hierarchical Heterogeneous IoT Time Series Data Index for NVM

– Conference Paper

A Cache Friendly LSM Tree Based on Extendible Hash

– Concurrency and Computation: Practice and Experience (Journal Article)

Rajesh Suman | Medical pharmacology | Research Excellence Award

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Prof. Dr. Rajesh Suman | Medical pharmacology | Research Excellence Award

Hind Institute of Medical Sciences, Sitapur | India

Dr. Rajesh Kumar Suman is a distinguished Professor of Pharmacology with an extensive academic, teaching, and research background in medical sciences. He has over a decade of experience teaching pharmacology to medical, dental, paramedical, and nursing students, and is widely recognized for his commitment to quality education and curriculum development. An accomplished researcher, he has authored more than forty publications in reputed indexed journals and has actively contributed to national and international scientific conferences through invited lectures and oral presentations. His research interests primarily focus on diabetes, metabolic syndrome, cardiovascular pharmacology, and natural DPP-IV inhibitors. Dr. Suman has received prestigious recognition for excellence in scientific presentation and research contributions and has been honored for outstanding original research articles. He is also a prolific author of academic textbooks, having written multiple books and practical manuals in pharmacology for undergraduate and dental students, published by leading national and international publishers. In addition, he has contributed scholarly book chapters with global publishing houses. Dr. Suman has successfully completed certified training in medical education technology and curriculum implementation, reflecting his dedication to innovative teaching practices. He has been actively involved in research projects related to drug utilization, prescription patterns, cost-effectiveness, and rational use of medicines, including funded academic research initiatives.

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Arjuna (Terminalia arjuna), the Natural Dipeptidyl Peptidase IV Inhibitor, Offers Cardiometabolic Protection

– Book Chapter

Natural dipeptidyl peptidase-IV inhibitor mangiferin mitigates diabetes- and metabolic syndrome-induced changes in experimental rats

– Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy (Journal Article)

Satoru Kondo | Fruit Tree Science | Environmental Engineering Impact Award

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Prof. Dr. Satoru Kondo | Fruit Tree Science | Environmental Engineering Impact Award

Mae Fah Luang university | Thailand

Satoru Kondo is a distinguished researcher in fruit tree science, internationally recognized for his expertise in plant physiology and growth regulation. He earned his doctoral degree from the University of Tsukuba, Japan, and has built a highly impactful academic career through appointments at leading research and higher education institutions, including the Akita Fruit Tree Research Station, Hiroshima Prefectural University, and the Graduate School of Horticulture at Chiba University. He currently serves as a faculty member in the School of Agro-Industry at Mae Fah Luang University, Thailand, where he contributes to teaching, research, and academic leadership in horticultural sciences. Dr. Kondo has played a significant role in advancing the global horticultural research community through his editorial and leadership positions, including serving as Editor-in-Chief of the Journal of the Japanese Society for Horticultural Science, Chair of the ISHS Symposium on Plant Bioregulators in Fruit Production, and Editor-in-Chief of Scientia Horticulturae, where he continues to contribute as an Associate Editor. His scholarly work encompasses a broad range of topics related to fruit tree growth, development, and regulation, with a strong emphasis on applied and physiological approaches. With approximately 200 published research papers, Dr. Kondo has made enduring contributions to the scientific understanding and practical advancement of fruit tree production systems worldwide.

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Impact of ethanol treatment on fresh-cut jackfruits (Artocarpus heterophyllus Lam.): enhancing quality and metabolite dynamics during storage

– Food Chemistry

How Does Abscisic Acid Control Fruit Quality as a Plant Bioregulator?

– Review Article (Open Access)

Impact of high-voltage electrostatic field on physiological changes and cell wall-degrading enzymes in postharvest avocado fruit (Persea americana Mill.)

– Journal of the Science of Food and Agriculture

Inhibitors of abscisic acid synthesis or signaling affect anthocyanin synthesis and photoreceptors in grape berries

– Scientia Horticulturae

Effects of blue-light irradiation on abscisic acid signaling and sugar translocation in Vitis labruscana L.H. Bailey grapevines

– Plant Growth Regulation