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Research Areas
While I respect and appreciate all organs (and have done research across several different ones), I have grown particularly fond of kidneys. Specifically, I enjoy using the following statistical methodologies for the following kidney-related applications:
Application areas
Renal histopathology
Kidney transplant/allograft outcomes
Kidney disease outcomes
Favorite statistical tools
High-dimensional regression
Machine learning including random forests, XGBoost, and ensemble learning
Variable/feature selection approaches
Active and Completed Projects
Check out the projects in progress or completed by my trainees (or Starlings as I sometimes call them to keep with the theme of the lab acronym - Starlings listed in order of contributions to each project and * indicates honors are shared)!
Active Projects
Feature Selection with FDR Control in Scalar-on-Matrix Regression (Starling(s): Aneesh)
Scalar-on-Tensor Regression with Unbalanced Tensor Predictors (Starling(s): Alec)
Integrating Tubule-Level Procurement Biopsy Pathomics and Clinical Factors for Machine Learning Prediction of Delayed Graft Function (Starling(s): Huiqian)
Scalar-on-matrix Logistic Regression for Unbalanced Feature Matrices (Starling(s): Hedwig)
Adapting Machine Learning Models Using Multisite Histopathology Data for Predicting Kidney Function (Starling(s): Ritesh, Advay, Raymond, Janelle)
Flexible Ensemble Learning-based Classification of Post-Transplant Kidney Function Outcomes (Starling(s): Chris)
Creating Interpretable User Interfaces for Machine Learning Predictions of Post-Transplant Kidney Function Outcomes with Donor Renal Histopathology and Clinical Data (Starling(s): Kenny*, Abby*)
Completed Projects
A Pathomic-Ensemble Strategy for Exploring Histological Signatures of eGFR Decline in IgAN (Starling(s): Connie, Lylybell, Huiqian)
A Pathomics-Integrated Approach Toward Improved Prediction of Kidney Survivability Up to 5 Years Post-Biopsy in IgA Nephropathy Patients (Starling(s): Lylybell, Connie)
Please reach out if you are interested in working with us! - you could be featured on this page!
Lab membership comes with your own custom Pokémon avatar (see below for Pokémon avatars submitted by trainees or ones I made of collaborators)!
Lab Members/Starlings
Jeremy Rubin, Lab Director and Self-Appointed Pun Expert
Clinical Assistant Professor of Biostatistics, University of Maryland, College Park
Email: jrub@umd.edu
X/Bluesky: @super_jrub
Jeremy Rubin, PhD is a Clinical Assistant Professor of Biostatistics at the University of Maryland, College Park. He received his undergraduate degrees in Statistics and Mathematics from the University of Maryland, Baltimore County before matriculating to the University of Pennsylvania, where he completed his PhD in Biostatistics. Jeremy's main research focuses are the development and application of statistical methods for renal histopathology and kidney transplantation data, but he also previously done research in application areas including computed tomography angiography (CTA) imaging, structural magnetic resonance imaging (MRI), wearable device data, kidney disease (including patient-reported outcomes, autosomal recessive polycystic kidney disease), and inflammatory bowel disease. While Jeremy believes that most problems can be solved with a high-dimensional regression model (especially lasso-based approaches), he also worked with statistical techniques including random forests, survival analysis, mixed models, linear/logistic regression analyses, and conformal prediction. Besides research, Jeremy is also passionate about finding coffee, playing badminton, making puns, as well as watching and performing stand-up comedy!
Huiqian Hu, Badminton Player with Great Taste in Racket Specs
PhD candidate in Molecular Pharmaceutics, University of Utah
Email: huiqian.hu@utah.edu
Huiqian Hu, currently a PhD candidate in Molecular Pharmaceutics at University of Utah, is interested in statistical and machine learning methods for high-dimensional biological data analysis. His research focuses on developing random forest and XGBoost frameworks for predictive modeling in precision medicine, with expertise in multi-omics integration and computational biology. He is excited to collaborate with the STARAPTOR Lab as a trainee under the supervision of Dr. Rubin to explore novel statistical approaches—particularly conformal prediction and high-dimensional regression methods—for improving model reliability in clinical applications.
Connie Gao, The Long-Range Predictor
Medical Student, University of South Florida Morsani College of Medicine
Email: conniegao@usf.edu
Connie Gao, currently a medical student at the University of South Florida Morsani College of Medicine. She got her undergraduate degree in Biomedical Engineering at the University of Michigan and is passionate about advancing the intersection of technology and medicine!
Lylybell Zhou, Acronym and Pun Second-in-Command
Medical Student, University of South Florida Morsani College of Medicine
Email: lylybell@usf.edu
Lylybell is a second-year medical student at the University of South Florida. She graduated from the University of Florida with a degree in Medical Geography. Her research interests are wide-ranging, but she is overall interested in projects bridging her experiences in the basic, translational, and clinical sciences. She is excited to work with the STARAPTOR and CMIL labs this summer (and perhaps beyond)!
Hedwig Nordlinder, If there's a will then there's a theorem for that!
MSc Mathematical Statistics student at Stockholm University
Email: hedwignordlinder@gmail.com
Biostatistical Research Assistant, Karolinska Institute. Voting member Swedish Society of Actuaries. Research interests include high dimensional statistics, Bayesian inference, MCMC, Phylogenetics and generative machine learning models.
Abby Sun, She'll be there in a dash(board)!
Research Associate, Institute for Asthma & Allergy
Email: abbyjsun@gmail.com
Abby Sun is currently a Research Associate at the Institute for Asthma & Allergy, where she specializes in flow cytometry and supports clinical and validation studies in immunotherapies and immunological diagnostics. A recent MSPH graduate in Global Disease Epidemiology and Control from Johns Hopkins Bloomberg School of Public Health and an UMD alumni, she is passionate about applying evidence-based and translational approaches to advance clinical health outcomes for underserved and vulnerable populations. Her past research has focused on infectious disease epidemiology, vaccine science, and clinical immunology, including coordinating a respiratory disease surveillance study in rural Zambia and contributing to vaccine coverage and serosurveillance research. She is excited to join the STARAPTOR Lab to further explore machine learning and statistical approaches for modeling and improving clinical insights. Outside of academia, Abby enjoys traveling, hiking, and playing Pokémon Go.
Ritesh Reddy Thipparthi, Don't sleep on his models!
Undergraduate Student in Computer Science, University of Maryland, College Park
Email: rthippar@umd.edu
Ritesh is a junior CS major at UMD with interests in machine learning for biomedical and clinical applications. Before joining the STARAPTOR Lab, he built real-time systems for EEG focus tracking and voice-driven systems, which convinced him that nothing is more exciting than a pipeline that actually works. In the lab, he studies pathomic features from donor biopsies to predict kidney transplant outcomes, and hopes his models won’t be as overfit as his sleep schedule. Outside of his work, you can find him at hackathons, experimenting with side projects, or playing soccer.
Chris Wu, The Match Point Converter
Undergraduate Student in Computer Science, University of Maryland, College Park
Email: cwu12314@terpmail.umd.edu
Chris Wu is currently an undergraduate studying Computer Science at the University of Maryland - College Park, pursuing a concentration in Machine Learning. He enjoys learning and talking about all things related to software and ML, and you can often find him on a badminton court or on a run in his free time. He is eager to start his work at and contribute to the STARAPTOR lab!
Advay Monga, Always working in harmony with others!
Undergraduate Student, University of Maryland, College Park
Email: amonga@terpmail.umd.edu
Advay is an undergraduate student at the University of Maryland, College Park. Before joining the lab, he has had some experience in computational biology and has done some personal projects in machine learning. He is interested in and enjoys learning about machine learning and math in applications to immune biology. In his free time, he likes playing badminton or volleyball with friends and trying new foods.
Raymond Chen, A master of his domain!
Undergraduate Student in Computer Science, University of Maryland, College Park
Email: rchen989@terpmail.umd.edu
Raymond is a third-year student studying computer science at the University of Maryland. He is interested in all things ML, but particularly in machine vision and perception. Outside of the lab, you can find him either at the gym, outside skateboarding, or helping out at his family's restaurant! His other fun facts include that he's in a professional technology fraternity (KTP), has a terrible sleep schedule, plays a lot of TFT and League of Legends as well volleyball and badminton recreationally.
Janelle Vo, If there's a difference, she'll find it!
Undergraduate Student in Public Health Science, University of Maryland, College Park
Email: jvo9@terpmail.umd.edu
Janelle is an undergraduate student studying public health at the University of Maryland. She is particularly interested in using her background in biology to analyze and interpret biological data. She aims to create and interpret data visualizations while applying statistical methods, such as hypothesis testing, to support clinical outcomes and build her data analysis skills. In her free time, Janelle enjoys playing Roblox, dabbling in arts and crafts, traveling, and collecting trinkets!
Kenny Akinnuoye, The Dashboard Deputy
Data Analyst, American Clean Power
Email: kaa154@georgetown.edu
Kenny Akinnuoye is a data analyst collaborating with the Rubin Lab on kidney donor biopsy research, focusing on DGF and eGFR modeling, logistic regression workflows, and predictive analytics.
Aneesh Krishna Rao Chepuri, he's got it under control!
MS Student in Data Science at University of Maryland, College Park
Email: achepuri@umd.edu
Alec Zhang, he thrives under pressure, even when things get a little tens(or)!
Undergraduate Student in Computer Science, University of Maryland, College Park
Email: achepuri@umd.edu
Collaborators
Jarcy Zee, Assistant Professor of Biostatistics at the University of Pennsylvania (and was my PhD adviser!)
Pinaki Sarder, Associate Professor of AI in the Section of Quantitative Health of the Department of Medicine and Associate Director for Imaging in the Intelligent Critical Care Center at the University of Florida
Anindya S. Paul, Assistant Scientist in the Computational Microscopy Imaging Laboratory and Intelligent Clinical Care Center (IC3) in the Department of Medicine at the University of Florida
Luís Rodrigues, Nephrologist at Centro Hospitalar and Universitário of Coimbra PhD Student
Robert Moy, Fellow with the Division of Nephrology at the Children's Hospital of Philadelphia
James E. Wiseman, Assistant Professor of Surgery in the Division of Trauma, Surgical Critical Care, and Acute Care Surgery, University of Maryland School of Medicine
Cher Dallal, Associate Professor of Epidemiology at the University of Maryland School of Public Health, College Park
Michael Tran, University of Maryland School of Public Health, College Park MPH in Epidemiology Graduate and Expert Starling Recruiter
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