Team
Meghana Kamineni
Co-mentored medical student with Dr. Pradeep Natarajan
Bio: Meghana is a medical student at Harvard Medical School. She is working on using machine learning techniques to identify splenic features in abdominal MRIs that are associated with increased risk for coronary artery disease. She holds a bachelor’s degree in Computer Science from MIT.
Xinyu Wang
Co-mentored graduate student with Dr. Ed Giovannucci
Bio: Xinyu is currently a master’s student in Department of Epidemiology, Harvard T.H. Chan School of Public Health. Her research focuses on integrating multi-omics data to explore the underlying mechanisms of cancers and cardiometabolic diseases. She is also passionate about translating epidemiological findings into clinical practice. She holds dual bachelor’s degrees in Medicine and Economics from Peking University.
Yixuan (Kathy) Liu
Co-mentored graduate student with Dr. Michael Honigberg
Bio: Kathy is a master’s student in Department of Biostatistics, Computational Biology and Quantitative Genetics, Harvard T.H. Chan School of Public Health. Her research leverages multi-omics approaches to investigate proteomic profiles and methylation patterns associated with somatic mutations in clonal hematopoiesis of indeterminate potential (CHIP) and cardiovascular disease (CVD). She holds a dual degree in Molecular Bioscience, Genetics and Genomics from Duke Kunshan University and Duke University.
Zhanqing (Anthea) Hua
Co-mentored graduate student with Dr. Vineet Raghu
Bio: Zhanqing (Anthea) Hua is a Master student in Genetic Epidemiology at the Harvard School of Public Health. Her research centers on integrating deep learning methodologies with genome-wide association studies (GWAS) to advance understanding of human disease. She is committed to exploring the associations between genomic factors and disease outcomes to inform risk prediction and potential interventions. She obtained her Bachelor of Science degree in Biological Sciences from Imperial College London.
Linke Li
Computational associate jointly with Dr. Michael Honigberg
Bio: Linke Li holds a Master’s degree in Biostatistics from Duke University. Her research focuses on integrating deep learning methodologies into statistical genetics to enhance disease risk prediction and identify at-risk populations. She is interested in comparing the disease prediction capabilities of deep learning methods with traditional approaches like genome-wide association studies (GWAS) and polygenic risk scores (PRS). By identifying novel genetic variations, she aims to improve risk prediction models and contribute to preventive healthcare for disease.
Shengxin Liang
Co-mentored graduate student with Dr. Akl Fahed
Bio: Shengxin is currently a Master student in Pharmacoepidemiology at the Harvard School of Public Health. Her research focuses on utilizing genetic epidemiology and pharmacoepidemiology methods to investigate cardiovascular drug efficiency and safety. She holds a bachelor’s degree in biology from McGill University. In her spare time, she is interested in wildlife conservation.
Yiru “Angelina” Jin
Co-mentored undergrad student with Dr. Vineet Raghu
Bio: Angelina is a sophomore at Boston University majoring in Biochemistry and Molecular Biology on a pre-dental track. She is currently studying the effects of environmental and nutritional stress on the mitochondrial pathway. Moving forward, she hopes to expand her knowledge of computational biology and explore machine learning techniques to enhance data analysis in biological research.
Cyril François
Visiting medical student
Bio: Cyril is a first-year master’s student in Medicine at KU Leuven University in Belgium. His research focuses on integrating machine learning with multi-omics data to study clonal hematopoiesis of indeterminate potential (CHIP) and its associations with disease outcomes, such as cardiovascular disease. He aims to strengthen his computational research expertise and contribute to future advances in precision medicine. He completed his Bachelor of Medicine at KU Leuven.
Wenxin Xiang
Co-mentored visiting Ph.D. student with Dr. Wenjie Ma
Bio: Wenxin is currently a Ph.D. student in Biomedical Engineering at Tsinghua University. Her research focuses on leveraging large language models to predict the risk and progression of Alzheimer’s disease and related dementias. She holds a Bachelor’s degree in biomedical engineering from Northeastern University (China).
Antony Tan
Graduate student
Bio: Antony is a master’s student in Computational Biology and Quantitative Genetics at Harvard. His research applies machine learning to large-scale proteomics for enhancing interpretation and cross-platform harmonization. He is broadly interested in representation learning that links molecular data to clinical/medical outcomes. He previously developed transformer models for astronomical time-series analysis, resulting in a NeurIPS ML4PS publication, and holds a bachelor’s degree in Computer Science from the University of Toronto.
Sylvia Deng
Co-mentored graduate student with Dr. Junwei Lu
Bio: Sylvia is a first-year master’s student in Health Data Science at the Harvard T.H. Chan School of Public Health. Her research focuses on applying large language models to peptide-level omics data to gain insights into cardiac diseases. She earned her Bachelor of Science degree in Mathematics of Computation and Statistics & Data Science from the University of California, Los Angeles (UCLA).
Yuan Tian
Co-mentored graduate student with Dr. Junwei Lu
Bio: Yuan is currently a master’s student in Biostatistics at the Harvard T.H. Chan School of Public Health. His research focuses on applying large language models to the analysis and interpretation of clinical data. Broadly, he is interested in leveraging deep learning–based approaches to integrate and analyze complex biomedical and clinical datasets. He holds a Bachelor’s degree in Biology and Biochemistry from Oberlin College.
Cuiqiyun (Linda) Yang
Graduate student
Bio: Linda is a master’s student in the Department of Biostatistics, Computational Biology and Quantitative Genetics, Harvard T.H. Chan School of Public Health. Her research focuses on developing and leveraging LLM and multi-omics approaches for cancer characterization. She holds a dual degree in Molecular Bioscience, Genetics and Genomics from Duke Kunshan University and Duke University.
Other
Lanyue Zhang
Thesis advisory committee member (advisor - Dr. Marios Georgakis)
Current: Ludwig Maximilian University of Munich