Lab

Dr. Hongshan Liu Dr. Hongshan Liu earned her Ph.D. in Biomedical Engineering from Stevens Institute of Technology. Currently, she is developing AI methods to advance brain science and medical informatics. Looking ahead, she aims to design interpretable methodologies that uncover deeper insights across these domains.
Dr. Krishnendu Chandra Dr. Krishnendu Chandra received his M.Phil. and Ph.D. in Biostatistics from Columbia University. He recently completed a postdoctoral research appointment in the Department of Statistics at Texas A&M University, where he worked on developing hierarchical Bayesian modeling methods that integrate diverse imaging data and quantify prediction uncertainty, with a focus on brain images related to neurocognitive disorders. Aiming to contribute to a better understanding of neurodegenerative diseases, he plans to develop deep learning frameworks for analyzing multi-object data that exploit object topology while leveraging linkages among objects to enable inference, clustering, and prediction—thus empowering developmental neuroscientists to take full advantage of existing multimodal imaging datasets.
Theyanesh Jayaprakash Theyanesh Jayaprakash is pursuing a master’s degree in Data Science at Indiana University Bloomington. Previously, he worked as a Senior Software Engineer at Optum, part of UnitedHealth Group, where he gained extensive experience in healthcare data analytics—focusing on data modeling, ETL processes, data warehousing, and visualization to support business-specific client reporting. As a research assistant, he is developing deep learning models to study Alzheimer’s disease, specifically analyzing atrophy patterns and disease progression. He aspires to contribute to mental health research and early cancer detection through sentiment analysis, emotion recognition, and anomaly detection. He received 2025 AAIC conference fellowship award.
Connor Cornelison Connor Cornelison is a second-year M.S. student in Data Science at Indiana University Bloomington, holding a B.S. in Computer Science from Indiana University South Bend. He is currently researching sex-specific imaging biomarkers for Alzheimer’s disease, using the ABC model. He plans to pursue a career in scientific computing, with a focus on AI-powered data processing. He received INGEN4DS fellowship.
Huairui Wang Huairui Wang has a background in statistics, with a B.Sc. from the University of Nottingham, and is currently pursuing his M.S. in Applied Statistics at NYU. He is currently involved in research applying statistical network models to study age-related changes in brain connectivity across the human lifespan. In the future, he plans to pursue a Ph.D. in statistics or biostatistics and continue conducting research at the intersection of health and high-dimensional data analysis.
Luling Zou Luling Zou is a second-year M.S. student in Biostatistics at Indiana University Bloomington, holding a B.S. in Applied Mathematics from Shanghai University. She is currently studying the spread of tau pathology across functional brain networks in Alzheimer’s disease by integrating PET imaging data with functional connectivity fMRI matrices, using co-evolution models to explore these interactions. She hopes to apply mathematical and statistical modeling—particularly subgraph detection techniques—to problems in health research, with a focus on Alzheimer’s disease and autism spectrum disorders, and plans to pursue a career in academia.
Yumeng Chen Yumeng Chen has a background in biomedical engineering, with research experience spanning neural interfaces, medical imaging, and computational biology. She is working on brain connectivity modeling and AI-based medical analysis. In the future, she hopes to pursue a Ph.D. and develop intelligent medical technologies that support early diagnosis and personalized treatment for neurological and psychiatric disorders.
Anastasija Naumoski Anastasija Naumoski holds a Bachelor of Science in Human Biology from Indiana University Bloomington and is currently entering her second year as a master’s student in Bioinformatics at Indiana University Indianapolis. After completing her graduate studies, she plans to pursue a career as a clinical bioinformatician, where she can apply her training to support precision medicine and improve patient outcomes.
Ash Sharma Ash Sharma has a background in computer science, with a bachelor's degree in the field and prior experience in several computational and data-focused internships, including a machine learning internship at Adsynthetica, where he developed an end-to-end synthetic data pipeline. He is currently a second-year master's student in statistics at UIUC, working as a research assistant with Indiana University on modeling the reliability of neuroimaging data using a latent variable framework. Looking ahead, he plans to deepen his research experience in interdisciplinary, data-intensive problems as he pursues a Ph.D. in biostatistics or data science.