Epidemiology · Biostatistics · Health Informatics
MSc in Health Informatics · Karolinska Institutet & Stockholm University
MSc student at Karolinska Institutet, recently getting into proteomics and applied statistics for large-scale biomedical data analysis. Still very much learning.
Seeking PhD positions — Epidemiology & Biostatistics, expected start 2027
Open to OffersPaper published in Neural Networks (IF 6.3) — MIEF-Net
PublicationJoined Pereira Research Group, Karolinska Institutet — CSF proteomics / ADNI
Research AssistantGraduated with Outstanding Thesis Award — Sun Yat-sen University
AwardAbout
How can high-dimensional proteomic and genomic data be leveraged to identify early molecular signatures of neurodegeneration — and how do population-level risk factors causally shape disease trajectories?
I am a research student in Health Informatics at Karolinska Institutet & Stockholm University, working at the intersection of computational proteomics, genomic epidemiology, and clinical AI. My current research focuses on high-throughput CSF proteomics for Alzheimer's disease biomarker discovery, using the SOMAscan aptamer-based platform with data from the ADNI cohort, with a particular emphasis on mitochondrial protein signatures.
With a foundation in preventive medicine and training in epidemiological methods — including Mendelian randomization and GBD-based disease burden analysis — I bridge population-level insights with molecular data. I also have prior experience in transformer-based fall risk prediction and multimodal wearable sensor fusion, which informs my broader interest in intelligent clinical decision support.
My published work includes first-author papers in Neural Networks (IF 6.3) and IEEE Internet of Things Journal (IF 10.6), as well as global disease burden analyses published in the Journal of Global Health. I have served as Principal Investigator on a nationally-funded research project on gait-based risk identification in the elderly.
Education
Sep 2025 — Jun 2027 (Expected)
Master of Science in Health Informatics
Dept. of Learning, Informatics, Management and Ethics (LIME) · Joint Master's Programme · 120 ECTS credits
Key Courses
Epidemiology & Biostatistics · Health Data Science
· Clinical Decision Support · Medical Informatics · Research Methods in Health Informatics
Sep 2020 — Jun 2025
Bachelor of Medicine · Preventive Medicine
School of Public Health · Shenzhen Campus
GPA 3.4 / 4.0Thesis
"Gait Anomaly Detection Based on Deep Learning and Motion
Sensor Technology Fusion" · University-Level Outstanding Thesis Award, 2025
Key Courses
Epidemiology · Biostatistics · Preventive Medicine ·
Clinical Medicine · Medical Statistics · Toxicology · Nutrition & Food Hygiene
Publications
MIEF-Net: Multimodal Image-Enhanced Fusion Network for Intelligent Fall Risk Prediction
Neural Networks, vol. 195, article 108260, Oct. 30, 2025.
MSS-Former: Multi-Scale Skeletal Transformer for Intelligent Fall Risk Prediction in Older Adults
IEEE Internet of Things Journal, vol. 11, pp. 33040–33052, Jun. 28, 2024.
Assessing and projecting the global burden of thyroid cancer, 1990–2030: Analysis of the Global Burden of Disease Study
Journal of Global Health, vol. 14, article 04090, Apr. 5, 2024.
MIEFP-Net: A Multimodal Image-Enhanced Network for Fall Prediction Using IMU Data
The 15th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 2024. (Poster)
Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters
BMC Geriatrics, published Feb. 1, 2024.
Enhancing City-Level Influenza Nowcasting on Island Terrain with Graph Neural Networks: Spatial Feature Insights
Intelligent Systems Conference. Cham: Springer Nature Switzerland, August 2024.
Research
Sep 2025 — Present
Karolinska Institutet · Pereira Research Group
Research AssistantContributing to high-throughput proteomic profiling of cerebrospinal fluid (CSF) samples from the ADNI cohort using the SOMAscan aptamer-based platform. Current analyses centre on mitochondrial protein signatures and their associations with Alzheimer's disease progression, incorporating bioinformatic pipelines for differential expression and pathway-level interpretation.
Mar 2022 — Jun 2025
Sun Yat-sen University School of Public Health (Shenzhen) · A.P. Yang Zhao Research Group
PI & Team MemberDeveloped predictive models for personalized health management and elderly care using machine learning and deep learning. Concentrated on sensor-based health monitoring — integrating motion recognition technologies, spectral analysis (FFT/GAF), and spatial-temporal skeletal transformers (MSS-Former) — for early detection and risk stratification of geriatric fall risk. This work produced 5 peer-reviewed publications including in Neural Networks (IF 6.3) and IEEE IoT Journal (IF 10.6).
Dec 2022 — Dec 2023 | Funded Jan 2024 — Dec 2024
Innovation & Entrepreneurship Training Program 2023 · Shenzhen Medical Research Fund (A2301041)
Project Leader / Principal InvestigatorLed the development of a real-time gait risk identification model for elderly individuals using inertial measurement units (IMU). Applied Gramian Angular Field (GAF) image encoding and multi-branch ResNet architecture to convert 6-axis IMU signals into RGB feature images for fall prediction. The innovation project received the highest school review rating of "Excellent". The subsequent national grant (¥50,000, SMRF) extended this work into an intelligent intervention system combining large deep learning models with deep imaging data.
Jul 2023 — Jun 2025
Sun Yat-sen University School of Public Health (Shenzhen) · Prof. Yiqiang Zhan Research Group
Team MemberInvestigating epidemiological characteristics and survival outcomes of neurodegenerative diseases using advanced statistical methodologies. Applied Mendelian randomization techniques to examine causal relationships in genetic epidemiology; leveraged large-scale databases (UK Biobank, NHANES, GBD) for comprehensive data mining. Published global disease burden analysis on thyroid cancer in Journal of Global Health (IF 7.66). Two additional manuscripts on diabetes and neurodegenerative disease burden are currently under review.
Dec 2021 — Nov 2022
Innovation & Entrepreneurship Training Program 2022 · Sun Yat-sen University
Team MemberEstablished an early predictive model for Alzheimer's Disease risk using meta-analyses of modifiable risk factors. Identified key early-stage AD risk factors and trained six machine learning classifiers (Logistic Regression, SVM, Random Forest, XGBoost, etc.) achieving high predictive accuracy. The project was awarded "Excellent" rating for innovation and practical utility.
Skills
Awards & Funding
Personal
This is how I decompress. I cook mostly to share — and the real reward is watching someone genuinely enjoy something I made.
Contact
I am open to research collaborations and academic discussions across health informatics, epidemiology, and computational biology. I am actively seeking PhD positions, particularly in epidemiology and biostatistics, with an expected start in 2027. Please don't hesitate to reach out.