Welcome to my website! I’m Xin Ma, a fifth-year Ph.D. student in the Department of Biostatistics at the University of Florida, with research involvement in bioinformatics at the Center for Advanced Spatial Biomolecule Research (CASBR). I’m fortunate to be advised by Dr. Li Chen and Dr. Ramon C Sun. Before my Ph.D. journey, I earned a Master of Science in Statistics from George Washington University with a 2-year Dean’s Fellowship and completed my Bachelor’s degree in Actuarial Science at the Southwestern University of Finance and Economics, China.
My research interests revolve around leveraging statistical learning and deep learning methods to explore various domains within biostatistics. This includes spatial multi-omics (Spatial Transcriptomics and Spatial Metabolomics), genomics (single-cell sequencing data), genetics (GWAS), and (bio)medical images (MALDI, MRI and H&E). By employing advanced computational techniques, I aim to uncover insights into complex biological systems, ultimately contributing to advancements in healthcare and biomedical research.
🚀 News
Aug 2026
💼 After an amazing summer, I've concluded my internship as an AI Discovery Data Science Intern in the Advanced Intelligence (AI) department at Eli Lilly and Company — grateful for the projects, mentorship, and growth this experience brought.
Jun 2026
📄 My first author paper
"Machine learning-based prediction of clinical outcomes in gliomas using glycomics features" is published in
Computational and Structural Biotechnology Journal.
DOIJun 2026
📄 My first author paper
"Reference-informed spatial domain detection using weak supervision for spatial transcriptomics" is published in
Genome Research.
DOIMay 2026
💼 I've officially started my summer internship as an AI Discovery Data Science Intern in the Advanced Intelligence (AI) department at Eli Lilly and Company.
Apr 2026
🏅 I won the department PhD Student Travel Award for my presentation at ENAR 2026.
Mar 2026
🎤 I presented "Reference-Informed Spatial Domain Detection Using Weak Supervision for Spatial Transcriptomics" and served as session chair for "Machine Learning and Causal Inference for Clinical and Genomic Studies" at the ENAR 2026 Spring Meeting in Indianapolis, IN.
Earlier news
Feb 2026
📰 Honored to be featured by University of Florida PHHP and to share my story.
Read itJan 2026
💼 I'm excited to share that I will be joining Eli Lilly and Company as an AI Drug Discovery summer intern (2026) in Indianapolis, Indiana.
May 2025
📄 My co-first author paper
"Spatial mapping of the brain metabolome lipidome and glycome" is published in
Nature Communications.
DOIMar 2025
🎤 I presented "A Semi-Supervised Multi-Modal Model for Domain Detection in Spatial Transcriptomics" at the ENAR 2025 Spring Meeting in New Orleans, LA.
Mar 2025
📄 My first author paper
"AI-driven Framework to Map the Brain Metabolome in 3D" is published in
Nature Metabolism.
DOIFeb 2025
📍 I attended the Winter Conference on Brain Research 2025 in Lake Tahoe, CA.
Aug 2024
📄 My first author paper
"Deep5hmC: Predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model" is published in
Bioinformatics.
DOIMay 2024
🏅 I won the MCBIOS 2024 Travel Fellowship.
Mar 2024
🎤 I presented "Deep5hmC" at ASA Florida Chapter 2024 in Tallahassee, FL.
Mar 2024
🎤 I presented "Deep5hmC" at MCBIOS 2024 in Atlanta, GA.
Nov 2023
🏅 I won the Mark C. K. Yang Student Presentation Award.
Aug 2023
🎓 I passed the written qualifying exam.
Jul 2023
🎤 I presented "Spatial Metabolome Lipidome Glycome Analyses from a Single Tissue Section" at ICIBM 2023 in Tampa, FL.
