CV
CV
Due to my keen interest in interdisciplinary subjects, I'm greatly looking forward to communicating and collaborating with you!
[ 2017.09 ] - [2023.06]
[ Tongji University, China ]
[ Ph.D. ]
Throughout this period, my research primarily centered on anomaly detection, prediction, and failure diagnosis for large-scale computing systems. I conducted automated diagnostics, applying a data analysis perspective to ensure the system's reliability.
[ 2023.09 ] - [ Now ]
[ Duke University, United States ]
[ Postdoctoral Associate ]
At this stage, I'm conducting research at Duke University, focusing on multi-omics and imaging data, aiming to leverage AI/ML methods to address challenging scientific questions in aging and cancer.
[ 2022. 09 ] - [ 2023. 01 ]
[ Data analysis ]
[ Graduate course ]
[ Tongji University ]
About the course: This course provides a comprehensive introduction to modern data analysis techniques for graduate-level research across the biological, social, and computational sciences. Students will learn how to design, conduct, and interpret data-driven analyses using real-world datasets. Emphasis is placed on statistical reasoning, reproducible workflows, and critical interpretation of analytical results. Topics include data wrangling and visualization, exploratory data analysis, hypothesis testing, regression modeling, dimensionality reduction, and basic machine learning principles.
What I did for this course: Supported instruction for a graduate-level course focused on statistical and computational methods for data analysis. The course covered data cleaning, visualization, regression modeling, and reproducible research practices using Python and R. Assisted students with coding exercises, project design, and interpretation of analytical results, emphasizing practical applications to real-world and research datasets.
[ 2022. 01 ] - [ 2022. 08 ]
[ Data collection and integration technology ]
[ Undergraduate course ]
[ Tongji University ]
About the course: This course introduces fundamental concepts, techniques, and tools for collecting, integrating, and managing data from diverse sources. Students learn methods for extracting, transforming, and loading (ETL) data to create unified and high-quality datasets suitable for analysis and application development. Topics include data acquisition, cleaning, transformation, schema mapping, API-based data retrieval, and database integration. Emphasis is placed on practical implementation, data quality assurance, and hands-on experience with modern data integration technologies.
What I did for this course: Assisted in teaching and supporting students in laboratory sessions focused on data extraction, transformation, and integration workflows. Helped design and grade assignments involving real-world data sources, provided guidance on ETL tool usage and database connectivity, and supported students in debugging code and improving data quality practices. Collaborated with the instructor to ensure students developed both conceptual understanding and practical technical skills in data integration.
[ 2021. 09 ] - [ 2022. 01 ]
[ Web technology basics ]
[ Undergraduate course ]
[ Tongji University ]
About the course: This course introduces the core principles and technologies underlying modern web development. Students learn the foundations of building and maintaining websites and web applications, including HTML, CSS, JavaScript, and client–server architecture. The course also covers web servers, development frameworks, and best practices for creating responsive, interactive, and efficient web-based systems.
What I did for this course: Supported instruction in both lectures and lab sessions on fundamental web development concepts. Assisted students in designing and implementing web pages and applications using HTML, CSS, and JavaScript. Guided debugging, version control, and deployment practices, and helped evaluate assignments and projects to reinforce practical understanding of web technologies.
[ 2018. 09 ] - [ 2019. 01 ]
[ Information security theory and technology ]
[ Undergraduate course ]
[ Tongji University ]
About this course: This course explores the foundational principles, methods, and technologies used to secure information systems against unauthorized access and cyber threats. Topics include cryptography, network and system security, access control, risk management, and security protocols. Through lectures and hands-on exercises, students gain a comprehensive understanding of how to design, implement, and evaluate secure information systems.
What I did for this course: Assisted in lectures and lab sessions focused on core security concepts and practical applications. Helped students understand cryptographic techniques, network defense mechanisms, and system vulnerability assessment. Supported assignment grading, lab supervision, and provided technical guidance to reinforce secure coding and risk management practices.
[ 2024.09 ] - Emerging Scholars in Genome Sciences Symposium
[ University of Virginia, Charlottesville, VA, USA]
Title: A Robust and Accurate Test for Cellular Pathway Activities
Abstract: Current single-cell pathway analysis methods often miss the topological structure of gene co-expression that underlies true pathway activity. We present xGATE, a graph-based approach that captures the “fingerprints” of gene co-expression networks—such as hubs and chains—to infer pathway activity in single-cell and spatial transcriptomics data with greater accuracy. xGATE outperforms existing methods across diverse datasets, from healthy liver and pancreas to early autoimmune diabetes and cancer tissues, revealing subtle and spatially resolved pathway dynamics. By integrating pathway topology into single-cell analysis, xGATE offers a powerful and robust framework for discovering context-specific biological processes
[ 2024.05 ] - CHSI Retreat Symposium
[ Duke University, Durham, NC, USA]
Title: Leveraging AI to Link Pathology Images with Genomic Data for Enhanced Clinical Insights
Abstract: Bridging pathology images with molecular insights remains a major challenge in translational research. While pathology captures tissue architecture and cellular morphology, and genomics reveals molecular characteristics, their integration into pathway-level understanding is still limited. Current image-based models rarely connect visual features to underlying biological pathways, hindering clinical interpretation. We present a lightweight framework that directly links pathology images to pathway activities, offering interpretable, clinically relevant insights into complex biological processes. This approach enables direct inference of pathway dysregulation from routine histopathology, opening new avenues for precision diagnosis and therapeutic discovery.
[ 2023.06 ]
[ The Chinese University of Hong Kong, Shenzhen, China ]
Title: AIOps and its Future
Abstract: Artificial Intelligence Operations (AIOps) involve the application of artificial intelligence to enhance and automate the operation and maintenance procedures. Its implementation spans various scenarios including IT systems, communication infrastructure, and software systems, among others. AIOps delves into analyzing operation and maintenance data such as logs, time series, and alarms to achieve system anomaly detection, early warnings, anomaly correlation analysis, and root cause identification. Building upon this foundation, it achieves automation and intelligence in the operation and maintenance processes. Specifically focused on log data analysis, methods for system operation and maintenance are developed with a structured approach involving log analysis, log feature extraction, log anomaly detection, intelligent early warning systems, and root cause analysis.
[ 2023 ] [ Outstanding Graduates of Shanghai ]
[ 2018 ] [ Social Activity Scholarship ]
[ 2017 ] [ Outstanding Doctoral Freshman Scholarship ]
[ 2017 ] [ Outstanding Graduate Award ]
[ 2016 ] [ Outstanding Student Award ]
[ 2015 ] [ Second Prize in the National English Competition for College Students ]
[ 2014 - 2015 ] [ National Scholarship Award (2 times) ]
[ 2013 - 2017 ] [ First Prize Scholarship (7 times) ]
Boot Camp for AI & AI Accelerated Medical Research (Duke University + Tianqi Chen Institute, 2025)
NIH Compass Training and Mentoring Program (Washington University School of Medicine in St. Louis, 2025)
CHSI Virtual Symposium (Duke CHSI, 2025)
NIH Career Symposium (NIH, 2025)
DCI Cancer Biology Retreat (Duke Cancer Institute, 2025)
2025 DCI Scientific Retreat (Duke Cancer Institute, 2025)
Trainee of DCI (Duke Cancer Institute, 2024-2025)
From Multiscale Immune Modeling to Medical Digital Twins virtual conference (Online, 2025)
DCI Immuno-Oncology (IO)-Radiation Oncology and Imaging (ROI) Joint Retreat (Duke, 2025)
AI Health Virtual Seminar Series (Duke University, 2025)
Panel Discussion on K99/R00 Grants in Statistical Genetics and Genomics (ASA SSGG, 2025)
SSGG webinar (StatsUpAI, 2025)
Pilot Award from CHSI (Duke, 2024)
Invited talk at CHSI retreat (Duke CHSI, 2024)
Emerging Scholars in Genome Sciences Symposium (University of Virginia, 2024)
International Conference on Learning Representations (ICLR 2024)
Conference on Statistics in Genomics and Genetics (STATGEN 2024)
AI+Science Summer School (University of Chicago, 2024)
Workshop: Accessible and Efficient Foundation Models for Biological Discovery (ICML, 2024)
Invited talk at The Chinese University of Hong Kong, Shenzhen (CUHK, 2023)