Lab

Current Members

Postdoctoral Fellow

Dr. Jaeyoung Lee Dr. Jaeyoung Lee is a postdoctoral fellow in the lab. He received his doctoral training in Statistics at Virginia Tech, where his dissertation focused on supervised variational autoencoder frameworks for predictive modeling and association analysis. His research interests include heterogeneous data learning, deep generative models, variational inference, Bayesian methods, latent space models, dimension reduction, and statistical machine learning. In the lab, he develops statistical and machine learning methods for high-dimensional biomedical and neuroimaging data.

Ph.D. Students

Renhao Li Renhao Li is a Ph.D. student working with our team. His research focuses on statistical and computational methods for high-dimensional biomedical data, with interests in network modeling, machine learning, and neuroimaging applications.

Luling Altan Luling Altan is a Ph.D. student in SWLab. Her research focuses on developing Bayesian methodology for complex networks, particularly brain and protein networks. She suspects that much of what we observe is a projection from a much higher-dimensional space, and that the most interesting part of a dataset often lies in its latent structure rather than the features we directly measure. With a background in mathematics, she is drawn to graph theory and its applications in neuroscience for this reason. In her spare time, she loves rock climbing, researching the art of raising cats, reading about Vedic astrology, photographing nebulae and galaxies, and predicting people's destinies with star charts. Presentations: ENAR 2026 Spring Meeting poster: Bayesian latent space co-evolution model to explain AD progression · SMI 2026: Alzheimer's Disease Subtype Identification from Spatial Tau-PET Heterogeneity Using Self-Supervised Deep Learning · 20th International Joint Conference on Computational and Financial Econometrics (IJCFE, December 2026)

INGEN4DS Fellow / Research Assistant

Luke Hawthorn Luke Hawthorn is an INGEN4DS Fellow and research assistant working with our team. His research interests include computational and quantitative approaches to complex biomedical data. Through the INGEN4DS fellowship, he is gaining interdisciplinary research experience at the intersection of data science, genomics, and biomedical research.

Research Assistants

Ash Sharma Ash Sharma has a background in computer science and statistics. His research focuses on statistical and machine learning methods for high-dimensional neuroimaging and biological data, including latent-variable approaches to neuroimaging reliability and proteomic signatures of brain microstructural integrity. He presented the first-author poster Proteomics signature of whole-brain microstructural integrity of white matter using LatentSNA at the 2026 Alzheimer's Association International Conference (AAIC). This abstract was accepted for publication in Alzheimer's & Dementia in December 2026: Sharma et al. (2026). He also contributed code fixes to the LatentSNA package, including ensuring the Sutheta prior is positive-definite, proper initialization before the MCMC loop, and error handling.

Alumni

Dr. Krishnendu Chandra — Postdoctoral researcher in the lab from 2025–2026, working on statistical and deep learning methods for neuroimaging and Alzheimer's disease. He is now a Lecturer at Texas A&M University. Presentations: Indiana University Mathematics Department seminar (May 2026)

Theyanesh Jayaprakash — Graduate research assistant from 2024–2026, working on deep learning methods for tau-PET heterogeneity and Alzheimer's disease subtyping. He received the 2025 AAIC Conference Fellowship Award and is now an AI Engineer at Plutus. Publications: Jayaprakash et al. (2025) Alzheimer's & Dementia 21: e109949 (Abstract) (first author) · Powla et al. (2025) Alzheimer's & Dementia 21: e100019 (Abstract) · Cornelison et al. (2025) Alzheimer's & Dementia 21: e103077 (Abstract) Presentations: AAIC 2025 · ENAR 2026 Spring Meeting · SMI 2026 Software: Contributed code to the ABCModel package.

Connor Cornelison — Graduate research assistant from 2024–2026, studying imaging and molecular biomarkers of Alzheimer's disease. He received the INGEN4DS Fellowship and is now a software developer supporting high-performance computing at Indiana University. Publications: Cornelison et al. (2026) Alzheimer's & Dementia (Abstract; accepted for publication, December 2026) (first author) · Cornelison et al. (2025) Alzheimer's & Dementia 21: e103077 (Abstract) (first author) · Jayaprakash et al. (2025) Alzheimer's & Dementia 21: e109949 (Abstract) Presentations: AAIC 2025 · ENAR 2026 Spring Meeting · National Human Genome Research Institute Research Training Conference (2026) Software: Built and maintained the ABCModel package — tutorial, code updates, and simulated example data.

Huairui Wang — Graduate research assistant from 2025–2026, working on statistical network modeling and high-dimensional brain connectivity analysis. He is now pursuing his Ph.D. at Michigan State University.

Yumeng Chen — Graduate research assistant from 2025–2026, working on brain connectivity modeling and computational neuroimaging. She is now pursuing her Ph.D. in Biomedical Engineering at Case Western Reserve University.

Gertrude Osei — Graduate research assistant from 2025–2026, studying psychometric evaluation of cognitive measures in Alzheimer's disease. She is now pursuing her Ph.D. in Educational Measurement at James Madison University. Publications: Osei et al. (2026) Alzheimer's & Dementia (Abstract; accepted for publication, December 2026) (first author) Presentations: AAIC 2026

Anastasija Naumoski — DataWiz intern with the lab in Summer 2025, with interests in bioinformatics, computational biology, and precision medicine.

Plamena Powla — Worked with the lab from 2024–2025 on Alzheimer's disease research involving tau pathology and functional brain networks. She published a first-author abstract with the team. Publications: Powla et al. (2025) Alzheimer's & Dementia 21: e100019 (Abstract) (first author) · Cornelison et al. (2025) Alzheimer's & Dementia 21: e103077 (Abstract) · Jayaprakash et al. (2025) Alzheimer's & Dementia 21: e109949 (Abstract)

Yunhe Liu — Graduate research assistant at Yale from 2023–2024 and co-author of a manuscript with the lab. Yunhe went on to pursue a Ph.D. in Statistics at Texas A&M University. Publications: Wang et al. (2026) Nature Methods 23(1): 225–235 Presentations: ENAR Spring Meeting 2024 · Neuroscience Track Brunch and Poster Sessions (February 2024)

Yiting Wang — Graduate research assistant at Yale from 2023–2025 and co-author of two manuscripts with the lab. Yiting went on to pursue a Ph.D. in Statistics at the University of Virginia. Publications: Wang, S. et al. (2025) Medical Image Analysis 99: 103309 · Wang, S. et al. (2024) Alzheimer's & Dementia 20(12): 8387–8401 Presentations: AAIC 2024 · SMI 2023 · OHBM 2023

Xinzhi Zhang — Graduate research assistant at Yale from 2023–2025 who published first- and co-authored work with the lab. She went on to pursue a Ph.D. in Biostatistics at New York University. Publications: Zhang et al. (2025) Human Brain Mapping 46(9): e70260 (first author) · Wang et al. (2026) Nature Methods 23(1): 225–235 Presentations: Neuroscience Track Brunch and Poster Sessions (February 2024) Software: Contributed example files and tutorial content to the LatentSNA package.