Qun Tang | Drug Discovery and Development | Best Researcher Award

Qun Tang | Drug Discovery and Development | Best Researcher Award

Dr. Qun Tang, Nanchang university, China

Dr. Qun Tang earned his Ph.D. in Chemistry from USTC in 2005. Following postdoctoral research in South Korea and Sweden, he launched his independent lab at Nanchang University in 2010. His research focuses on Mn-based contrast agents 🧲, arsenic-derived anticancer drugs 💊, and innovative treatments for liver diseases using low phosphate stress (LPS) approaches 🧬. With 46 SCI papers, 1,489 citations 📚, and 3 authorized patents, Dr. Tang is a key contributor to pharmaceutical sciences. He is a Standing Committee Member of Jiangxi Pharmaceutical Society and collaborates with leading researchers to advance drug development globally.

Publication Profile 

Scopus

Education

Dr. Qun Tang earned his Ph.D. in January 2005 from the University of Science and Technology of China (USTC) 🎓. After postdoctoral collaborations in South Korea and Sweden 🌍, he returned to Nanchang University in March 2010 to begin his independent research career 🔬. His work has focused on manganese (Mn)-based materials for medical imaging contrast agents 🧲 and the development of novel arsenic-based anticancer drugs 💊. Currently, Dr. Tang is pioneering research on low phosphate (Pi) stress (LPS)-based strategies for the prevention and treatment of diseases, particularly targeting liver-related conditions 🧬. His contributions continue to shape pharmaceutical innovation globally.

Professional Memberships

Dr. Qun Tang holds a distinguished position as a Standing Committee Member of the Jiangxi Provincial Pharmaceutical Society 🏛️. This prestigious role reflects his commitment to advancing pharmaceutical sciences within the region and contributing to public health initiatives at the provincial level 📈. Through this membership, Dr. Tang actively engages in scientific discourse, policy guidance, and collaborative research opportunities with fellow experts across Jiangxi and beyond 🤝. His leadership within the society underscores his dedication to professional excellence and innovation in drug development and pharmaceutical research 💊🔬. This role further enhances his influence within China’s scientific and medical communities.

Research Focus

Dr. Qun Tang’s research squarely targets phosphate‑modulated liver oncology and theranostics 🧬🩺. He engineers inorganic‑phosphate binders and polymeric drug‑loading beads 🟤 to perform trans‑arterial embolization, simultaneously starving tumors and reshaping the micro‑environment 🎯. By blocking XPR1‑mediated phosphate efflux, his team triggers mitochondrial dysfunction in hepatocellular carcinoma cells ⚡️, while low‑Pi stress irreversibly repolarizes tumor‑associated macrophages 🛡️ and dampens angiogenesis 🌱. Tang also discovers how binders like sevelamer deactivate hepatic stellate cells to reverse fibrosis 🧫. Overall, his work fuses immunometabolism, interventional radiology, and targeted drug delivery to forge next‑gen therapies for liver cancer and chronic liver disease.

Publication Top Notes

  • Transarterial Embolization Using an Inorganic Phosphate Binder Modulates Immunity- and Angiogenesis-Related Factors in a Rat Model of Liver Cancer
  • Design and progress of drug-loading polymeric bead for tumor embolization
  • Inhibition of XPR1-dependent phosphate efflux induces mitochondrial dysfunction: A potential molecular target therapy for hepatocellular carcinoma?
  • Sevelamer reverses liver fibrosis by deactivation of hepatic stellate cells
  • Irreversible repolarization of tumour-associated macrophages by low-Pi stress inhibits the progression of hepatocellular carcinoma

Abdulilah Mayet | Neuropharmacology | Excellence in Research

Abdulilah Mayet | Neuropharmacology | Excellence in Research

Assoc. Prof. Dr. Abdulilah Mayet, King Khalid University, Saudi Arabia

Assoc. Prof. Dr. Abdulilah Mohammad Mayet is an accomplished expert in Electrical Engineering, currently serving at King Khalid University 🇸🇦. With a Ph.D. from KAUST 🎓, he has pioneered research in MEMS/NEMS, nanofabrication, and AI-integrated sensor systems 🤖. A prolific inventor with 8️⃣ patents and 28+ publications 📚, Dr. Mayet has collaborated with global institutions including UC Irvine 🇺🇸 and Cornell University. His leadership spans academia, industry, and innovation 🚀, notably as CEO of Qimam Abha Company and a Fulbright Scholar. Fluent in Arabic and English 🗣️, he inspires innovation across engineering and technology frontiers 🌍.

Publication Profile

Orcid

Education

Assoc. Prof. Dr. Abdulilah Mayet holds a distinguished academic background in Electrical and Electronics Engineering ⚡. He earned his Ph.D. in Electrical Engineering from King Abdullah University of Science and Technology (KAUST) in April 2016 📅, following his M.Sc. in Electrical Engineering from the same institution in June 2011 🧠. His academic journey began with a B.Sc. in Electrical and Electronics Engineering from King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia in June 1991 🏫. This strong educational foundation has powered his cutting-edge contributions to nanotechnology, MEMS/NEMS, and semiconductor innovation 🔬🚀.

Experience

Assoc. Prof. Dr. Abdulilah Mayet brings over 25 years of pioneering experience in nanotechnology, MEMS/NEMS, and VLSI design 💡. Currently, he serves as a Supervisor of the VLSI Design Group and a Visiting Professor at UC Irvine, while also being a Fulbright Scholar Fellow 🇺🇸. As an Associate Professor at King Khalid University, he leads initiatives in nanofabrication, AI-driven FPGA teaching, and research commercialization 🧪. Formerly CTO at SEMC, he managed a 4,000m² fab facility. His career spans innovations in NEM switches, amorphous metals, and MEMS platforms, with leadership roles at the Misk 2030 Leaders Program and Saudi Leadership Society 🌍🔬.

Awards

Assoc. Prof. Dr. Abdulilah Mayet has made remarkable contributions to science and engineering, notably by independently conceptualizing and demonstrating the first-ever fully amorphous metal fabricated in a CMOS fab 🧪🔬. He has published 28 journal papers (24 as first/corresponding author) and 7 conference papers 📝. His research has attracted over SAR 26 million in grants, supporting startups and lab establishments 💰. With 8 intellectual properties registered, he continues pushing innovation 🚀. Dr. Mayet has taught a wide range of advanced courses and mentored MSc students 🎓, while actively shaping curriculum development at both undergraduate and graduate levels 📖👨‍🏫.

Research Focus

Assoc. Prof. Dr. Abdulilah Mayet focuses on cutting-edge research in intelligent measurement systems, non-destructive testing (NDT), and sensor-based technologies within the realm of electrical and electronic engineering ⚡. His work integrates artificial intelligence 🤖, machine learning, and ANNs for enhanced precision in multiphase flow analysis, pipeline diagnostics, and material characterization. He also explores nanoelectronics, MEMS/NEMS, and gamma-ray-based detection systems for industrial and biomedical applications 🧠🏭. His multidisciplinary approach bridges engineering with sustainability, fluid mechanics, and healthcare innovation, making his contributions vital to the energy, oil & gas, and emerging technologies sectors 🌍💡.

Publication Top Notes

Multiphase Flow’s Volume Fractions Intelligent Measurement by a Compound Method Employing Cesium-137, Photon Attenuation Sensor, and Capacitance-Based Sensor

Combination of a Nondestructive Testing Method with Artificial Neural Network for Determining Thickness of Aluminum Sheets Regardless of Alloy’s Type

Application of the Fourier Transform to Improve the Accuracy of Gamma-Based Volume Percentage Detection System Independent of Scale Thickness

An Insight to the Outage Performance of Multi-Hop Mixed RF/FSO/UWOC System

Intelligent Measuring of the Volume Fraction Considering Temperature Changes and Independent Pressure Variations for a Two-Phase Homogeneous Fluid Using an 8-Electrode Sensor and an ANN

Proposing a Method Based on Artificial Neural Network for Predicting Alignment between the Saudi Nursing Workforce and the Gig Framework

The Role of Biocomposites and Nanocomposites in Eliminating Organic Contaminants from Effluents

An Intelligent Approach to Determine Component Volume Percentages in a Symmetrical Homogeneous Three-Phase Fluid in Scaled Pipe Conditions

Using Ant Colony Optimization as a Method for Selecting Features to Improve the Accuracy of Measuring the Thickness of Scale in an Intelligent Control System

Experimental Analysis to Detect Corona COVID-19 Virus Symptoms in Male Patients through Breath Pattern Using Machine Learning Algorithms

Application of Artificial Intelligence for Determining the Volume Percentages of a Stratified Regime’s Three-Phase Flow, Independent of the Oil Pipeline’s Scale Thickness