CV
CV
Due to my keen interest in interdisciplinary subjects, I'm greatly looking forward to communicating and collaborating with you!
[ 2023.09 ] - [ Now ]
[ Duke University, United States ]
[ Postdoctoral Associate ]
At this stage, I'm conducting research at Duke University, concentrating on Spatial Transcriptomics data and Visium data, aiming to leverage deep learning methods to address these challenging scenarios.
[ 2017.09 ] - [2023.06]
[ Tongji University, China ]
[ Ph.D. ]
Throughout this period, my research primarily centered on large-scale computing systems. I conducted automated diagnostic operations, employing a data analysis perspective to ensure the system's reliability.
[ 2022. 01 ] - [ 2022. 08 ]
[ Data collection and integration technology ]
[ Undergraduate courses ]
[ Tongji University ]
This course focuses on techniques and tools used to gather data from various sources and integrate it into a unified format for analysis or processing. It involves methods for extracting, transforming, and loading (ETL) data from disparate sources, ensuring data quality, and creating a unified view for analysis.
[ 2021. 09 ] - [ 2022. 01 ]
[ Web technology basics ]
[ Undergraduate courses ]
[ Tongji University ]
This course encompasses the fundamental concepts and technologies used in building and maintaining websites and web applications. It includes knowledge about HTML, CSS, JavaScript, web servers, client-server architecture, web development frameworks, and other related technologies used to create web-based systems.
[ 2018. 09 ] - [ 2019. 01 ]
[ Information security theory and technology ]
[ Undergraduate courses ]
[ Tongji University ]
This course involves studying the principles, methods, and practices to protect information and systems from unauthorized access, use, disclosure, disruption, modification, or destruction. It covers various aspects such as cryptography, network security, access control, risk management, and security protocols.
[ 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)