Portrait of Pengxiang Tang

Pengxiang Tang

MPhil student in Biological Sciences

School of Medicine

The Chinese University of Hong Kong, Shenzhen

Stay passionate.
Seek the truth.

I study pharmacy and biology, and use mathematical modeling to solve practical problems across disciplines.

Education Experience

Sept. 2020 — Jun. 2024

Jilin Medical University & Konyang University

Bachelor of Engineering in Biopharmaceuticals

China–Korea Cooperative Program · School of Pharmacy

Training in biopharmaceutical sciences, molecular biology, and quantitative approaches to scientific problems.

Ranked 1st / 442022-2023 Chinese National Scholarship

Sept. 2025 — Present

The Chinese University of Hong Kong, Shenzhen

Master of Philosophy in Biological Sciences

School of Medicine

Investigate the molecular mechanisms of ferroptosis-protective compounds using cell-based assays and animal models.

MPhil StudentRanked 3rd / 19

Beyond research, building community.
Building spaces for ideas to grow.

JILIN MEDICAL UNIVERSITY

The Hongzhi Program

Student Mentor · Founding Cohort

I founded and implemented the inaugural Hongzhi Program with faculty members, supporting outstanding first-year students through academic mentorship, learning strategies, and early research training. The first cohort went on to earn academic honors and develop preliminary research outcomes.

CUHK-SHENZHEN

Graduate Student Union

Vice Minister · Academic Department

I helped establish the union’s academic service framework, supported university seminars and academic events, and represented the GSU in external academic exchanges. Through student–faculty communication and peer support, I helped graduate students navigate academic challenges.

TEACHING & LEARNING

General Biology

Teaching Assistant · BIO1001 · CUHK-Shenzhen

I supported undergraduate biology teaching and a faculty-led education reform project, contributing to diagnostic assessments, retrieval practice, adaptive tutorials, and progressive inquiry-based activities that develop conceptual understanding and independent scientific thinking.

Questions first.
Disciplines follow.

I follow scientific questions across disciplinary boundaries, combining experimental biology with quantitative reasoning.

Life Sciences

2025

Natural products
& redox biology

Investigating how fucoxanthin modulates oxidative stress, inflammatory signaling, and cellular senescence in experimental models of renal aging.

Renal aging research ↗

2026

Drug development
& human-relevant models

Investigating the role of organ-on-a-chip technologies in drug discovery, efficacy assessment, toxicity testing, and translation toward human-relevant pharmacology.

Organ-on-a-chip study ↗

CURRENT FOCUS

Ferroptosis mechanisms
& pharmacology

Investigating small-molecule protection against ferroptosis and the redox mechanisms linking antioxidant systems, lipid peroxidation, and cell survival.

Research in progress

Mathematical Modeling

2022

Prediction
& planning

Developing quantitative forecasting models for elderly-care bed demand to support capacity planning and resource allocation in pension services.

Elderly care bed demand study ↗

2023

Process
optimization

Building data-driven process models and optimization frameworks to determine effective catalyst–temperature combinations under practical constraints.

Catalytic process study ↗

2026

Compositional data
& classification

Using compositional differences and weathering effects in ancient glass data to propose new methods for identifying and classifying glass artifacts.

Glass classification study ↗

Selected research.
Across disciplines.

Life Sciences
Original PDF first page: Fucoxanthin alleviates renal aging by regulating the oxidative stress process and the inflammatory response in vitro and in vivo models
ORIGINAL ARTICLE

Redox Report · 2025

Fucoxanthin alleviates renal aging by regulating the oxidative stress process and the inflammatory response in vitro and in vivo models

Zhang X, Qiang W, Guo Y, Gong J, Yu H, Wu D, Tang P, Yidan M, Zhang H, Sun X.

I explored whether fucoxanthin, a natural marine compound, could counter kidney aging associated with oxidative stress and inflammation. Working with my co-authors, we examined cellular senescence and aged-animal models using protein analysis, immunoassays, fluorescence imaging, and tissue staining. We found that fucoxanthin alleviated senescence and fibrosis alongside improvements in oxidative stress and inflammatory responses. These preclinical findings support further investigation of natural products as modulators of age-related kidney damage and connect redox biology with mechanism-oriented pharmacological research.

Life Sciences
Original PDF first page: Organ-on-a-chip as a next-generation tool in drug development: A bibliometric and patent analysis
ORIGINAL ARTICLE

Cell Transplantation · 2026

Organ-on-a-chip as a next-generation tool in drug development: A bibliometric and patent analysis

Du Y, Xu Y, Tang P, Meng G.

I asked how organ-on-a-chip research is evolving, and where scientific advances are becoming practical technologies for drug development. With my co-authors, we combined CiteSpace-based bibliometric mapping with patent analysis to examine influential work, research clusters, and emerging themes. We identified a growing emphasis on multi-organ integration, disease modeling, and drug screening, alongside expanding technological activity. For me, the study provides a map of the field’s development and highlights multi-organ systems, biomaterials, and clinical translation as priorities for future research.

Life Sciences
Original PDF first page: Enhancing experimental teaching of β-interferon synthesis through a virtual simulation platform: Application and effectiveness analysis
ORIGINAL ARTICLE

Education for Chemical Engineers · 2025

Enhancing experimental teaching of β-interferon synthesis through a virtual simulation platform: Application and effectiveness analysis

Tang P, Zhang C, Du Y, Xu Y, Wang M, Yu H, Zhang X, Gong J, Zhang H, Sun X.

I asked how students could gain more accessible and engaging experience with protein synthesis when conventional laboratory teaching faces practical constraints. With my co-authors, we designed and implemented a virtual platform for β-interferon synthesis, then compared it with conventional teaching through standardized assessments and student surveys. The evaluation indicated improved learning outcomes and greater student satisfaction. I see the platform as a scalable approach to blended biopharmaceutical education, helping connect theoretical knowledge with experimental learning.

Mathematical Modeling
Original PDF first page: A mathematical model of catalyst combination design and temperature control in the preparation of C4 olefins through ethanol coupling
ORIGINAL ARTICLE

RSC Advances · 2023

A mathematical model of catalyst combination design and temperature control in the preparation of C4 olefins through ethanol coupling

Tang P, Li H, Zhang X, Sun X.

I investigated how catalyst combinations and reaction temperature jointly shape the production of C₄ olefins from ethanol. With my co-authors, we used nonlinear fitting and analysis of variance to examine conversion and selectivity, then combined multivariable regression with constrained optimization to identify favorable operating conditions. The models linked experimental observations to actionable choices about catalysts and temperature. I see the contribution as a quantitative decision framework for planning catalytic experiments and improving process yield within the conditions represented by the data.

Mathematical Modeling
Original PDF first page: Ancient Chinese glass heritage classification based on compositional data and machine learning
ORIGINAL ARTICLE

npj Heritage Science · 2026

Ancient Chinese glass heritage classification based on compositional data and machine learning

Tang P, Gan X, Tang J.

I asked how ancient glass can be classified reliably when weathering alters its chemistry and composition measurements are constrained proportions. With my co-authors, we used centered log-ratio transformation and statistical tests to examine compositional patterns, then compared machine-learning classifiers and explored subgroups through clustering. Our models distinguished high-potassium from lead–barium glass and supported a reproducible classification framework. The broader lesson I draw is that useful prediction begins with respecting the structure of the data, creating a stronger bridge between quantitative methods and cultural heritage research.

More questions ahead…
More to discover…

Research is an ongoing process of asking better questions,
testing new ideas, and following evidence wherever it leads.