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Course-based Research Project

National University of Singapore (NUS), Yong Loo Lin School of Medicine

Machine Learning-Based Biomarker Discovery for Suicide Risk in Depression using RNA-seq data.

• Psychiatric biomarker discovery using RNA-seq and imbalanced learning
• Cross-cohort validation and reproducible ML workflows
• Pathway-based interpretation and clinical relevance analysis
• Supervisor: A/Prof. Caroline Lee (Vice Dean & Programme Director, NUS Graduate School)

Research Assistant

TUM-CREATE (NRF Singapore research centre, collaborating with TUM, NUS and NTU)

Developing reproducible ML pipelines for wearable spectral data analysis with focus on circadian health digital phenotyping.

• Multi-sensor fusion and feature engineering for wearable spectral data
• Circadian health digital phenotyping and biomarker discovery
• Reproducible ML pipelines with audit-ready workflows
• Supervisor: Prof. Dr. Manuel Spitschan (Technical University of Munich)

Front-End Engineer (Intern)

SEECEN TECHNOLOGY CO., LTD.

Front-end web development with focus on cross-browser compatibility.

• Front-end web development and cross-browser compatibility

Research Assistant

Key Laboratory of Non-Destructive Testing, Ministry of Education, China

Diverse research projects spanning wearable sensors, signal processing, and medical imaging.

• Wearable optical sweat analytics with microfluidics and colourimetry
• ECG & EEG real-time signal detection systems
• U-Net segmentation for dermatology imaging
• Intelligent tunnel multi-parameter monitoring systems
• Signal processing, computer vision, and embedded systems development

Master of Science

National University of Singapore (NUS)

Precision Health and Medicine

• AI & Machine Learning
• Applied Statistics
• High-Performance Computing
• Human Genomics
• Proteomics and Metabolomics
• Precision Biomarker
• Precision Diagnosis

Bachelor of Engineering

Nanchang Hangkong University (NCHU)

Biomedical Engineering

• Biomedical Digital Signal Processing
• Medical Ultrasound
• Medical Electronics
• Foundation of Medical Software
• Medical Imaging Technology
• Principle of Medical Instrumentation Design

Precision Health & Medicine Scholarship (PRECISE, Singapore)

National University of Singapore

Competitive scholarship for MSc program in Precision Health and Medicine

Third Prize, 10th National Student Optoelectronic Design Competition

China National Student Optoelectronic Design Competition

Awarded for Wearable Optical Sweat Analytics project

Second Prize, 8th National Student Optoelectronic Design Competition

China National Student Optoelectronic Design Competition

Awarded for Intelligent Tunnel Multi-Parameter Monitoring System project

Silver Award, 12th "Challenge Cup" Jiangxi Student Entrepreneurship Competition

Jiangxi Provincial Education Department

Awarded for Tunnel Monitoring project

Wearable tesla valve-based sweat collection device for sweat colorimetric analysis

Talanta

Huanhuan Shi, Yu Cao, Yining Zeng, Yanuo Zhou, et al. Peer-reviewed, high-impact journal publication on wearable sweat analytics technology.

Development and Application of Microfluidic Concentration Gradient Chip

Chinese Journal of Medical Physics

Shi, H., Cao, Y., Zhou, Y., et al. Publication on microfluidic device development for drug susceptibility analysis.

AI-Driven Light Exposure Classification

ML framework for circadian health phenotyping from wearable sensors. MSc Capstone project achieving 88.1% accuracy (AUC 0.938) in distinguishing natural from artificial light.

• 88.1% accuracy (AUC 0.938) for natural vs. artificial light classification
• 288-configuration grid search with participant-wise generalization
• Spectral shape prioritization over absolute intensity
• L2 normalization with hour-medoid aggregation
• Reproducible pipeline with fixed seeds and environment hashes
• Transparent negative evidence reporting (PCA, SMOTE-Tomek limitations)

Machine Learning Biomarkers for Suicide Risk Assessment in Depression

Course-based research identifying psychiatric biomarkers (NR3C1a, HSPA1B) from RNA-seq with cross-cohort validation and imbalanced learning.

• NR3C1a, HSPA1B as top biomarkers for suicide risk in depression
• Cross-cohort validation (primary + 3 external cohorts)
• Imbalanced learning with SMOTE-Tomek
• KEGG pathway enrichment analysis
• 4-class to binary mapping for clinical relevance
• Reproducible ML workflow with audit-ready artifacts

PrimeKG-RGCN Drug-Disease Link Prediction

Graph neural networks for computational drug discovery. Independent research implementing RGCN for drug repurposing on PrimeKG knowledge graph.

• 0.978 AUC-ROC for drug-disease link prediction on PrimeKG
• RGCN on 30,926 nodes (6,282 drugs, 5,593 diseases, 19,051 genes) with 849,456 edges
• 3 relation types: drug-gene, gene-gene, gene-disease interactions
• Complete pipeline: preprocessing → training → evaluation → validation
• Hits@10: 0.041, MRR: 0.019 ranking metrics
• GPU-accelerated with PyTorch Geometric (NVIDIA GTX 1070)

Wearable Optical Sweat Analytics

Microfluidics and RGB colorimetry for biomarker detection. National innovation project with Talanta publication and competition awards.

• 3rd Prize (10th National Student Optoelectronic Design Competition, 2022)
• Talanta Q1 journal publication (2022, co-author)
• Tesla valve-based sweat collection optimization
• RGB colorimetry signal processing
• NCHU 'Three Small Projects' award
• Funded by Outstanding Young Scientist Project (20192BCB23011)

Android Sleep Quality Monitoring System

BEng thesis achieving 80% accurate sleep quality monitoring using phone sensors with volunteer validation. No external devices required.

• 80% sleep quality classification accuracy
• Kotlin-based Android implementation
• 3-axis accelerometer, illumination, microphone sensor fusion
• Volunteer cohort validation
• Minimal resource consumption
• Comparable performance to commercial wearables

Multi-Parameter Physiological Monitoring System

Real-time monitoring of ECG, SpO2, respiration, temperature, and blood pressure with Qt/QML desktop and web interfaces.

• 5-parameter monitoring (ECG, SpO2, respiration, temperature, BP)
• STM32 hardware acquisition
• Real-time signal conditioning and filtering
• Qt/QML + HTML/JavaScript dashboards
• Sub-50ms latency
• Cross-platform deployment

U-Net for Skin Lesion Segmentation

Complete implementation with LabelMe annotation, model training, validation, and PyQt5 GUI for dermatological image analysis.

• U-Net architecture implementation
• LabelMe manual annotation workflow
• Class-specific IoU breakdown
• Data augmentation for limited datasets
• PyQt5 GUI for inference
• Medical imaging preprocessing pipeline

Fluorescence-Based Fire Safety Monitoring System

Smart monitoring system using fluorescence sensing for temperature, humidity, and fire detection in buildings and tunnels.

• Silver Award (12th 'Challenge Cup' Jiangxi Student Entrepreneurship, 2020)
• 2nd Prize (8th National Student Optoelectronic Design Competition, 2020)
• 6 patents filed and published
• Distributed optical fiber network integration
• Multi-parameter sensing (temperature, humidity, trend analysis)
• Electromagnetic interference immunity

Microfluidic Concentration Gradient Chip for Drug Susceptibility

Dean vortex secondary flow mixing for high-throughput biochemical applications. 2 patents and journal publication.

• 1 invention patent + 1 utility model patent
• Published in Chinese Journal of Medical Physics (2021)
• Dean vortex secondary flow optimization
• Gradient-based drug susceptibility testing
• High-throughput biochemical analysis
• Funded by PhD Research Startup Fund (EA202008205)

Thermal Cycling Device for Fluorescence Quantitative PCR

Research project on thermal cycling system design for qPCR instrumentation with precision temperature control.

• Successful Participant (2021 National Undergraduate BME Innovation Design Competition)
• Thermal control optimization
• PCR instrumentation design
• Precision temperature management
• System integration and testing

Quantitative Investment Strategies in Cryptocurrency Markets

Research on profitability of different investment strategies in cryptocurrency trading with backtesting and risk analysis.

• 4 quantitative strategies implemented and compared
• Backtesting framework development
• Risk-return optimization analysis
• Market dynamics understanding
• Strategy adaptation importance demonstrated
• Portfolio performance evaluation