Meet the Teams
Indiana University
Suranga Kasthurirathne, Primary Faculty Advisor, is a Research Scientist with the Regenstrief Institute and an Assistant Professor of Pediatrics at Indiana University School of Medicine. A computer scientist and health and biomedical informatician by training, his interests involve the application of AI to enable better access to care, as well as the generalizability and fairness of analytical methods.
Shun Grannis, Faculty Advisor, is Vice President, Data and Analytics, at the Regenstrief Institute, and Professor of Family Medicine, Indiana University School of Medicine. His research interests include improving discovery and decision support by developing, testing, and implementing innovative approaches for data integration, patient matching, and predictive modeling. He is interested in developing population health data frameworks that fuse social determinants with clinical data, and leveraging machine learning to improve decision support.
Kun Huang, Faculty Advisor, is a Professor at the Department of Medicine, Indiana University School of Medicine, and Director of Data Science and Informatics, Precision Health Initiative, Indiana University. He is a leader in bioinformatics and computational pathology. He applies his expertise to the Indiana University “Grand Challenge” Precision Health Initiative.
Joshua Choi is an internal medicine physician and a fellow of clinical informatics at Indiana University. His interests include using machine learning to improve medical education, and the visual presentation of patient data to clinicians. He also has expertise in application computer programming, data structures and algorithms, and user interface and visual design.
Ben Duggan is a medical student at the Indiana University School of Medicine. He is interested in the intersection of computing and medicine and is interested in creating new algorithms to improve patient outcomes while lowering health care costs by using bioinformatics, AI, and traditional medical techniques.
Tongxin Wang is a Computer Science PhD candidate at Indiana University. His research interest is in biomedical informatics, where he utilizes machine learning algorithms to solve biomedical problems. His main focus is on omics data analysis and medical imaging data analysis. He is interested in developing deep learning algorithms to understand omics data and to effectively extract biological insights.
Ziyu Liu is a doctoral student in statistics at Purdue University, Lafayette, Indiana.
MSU MIDI Lab, Michigan State University
Sameed Khan is an undergraduate student with dual majors in Human Biology and Computer Science. His research focuses on creating image analysis workflows that generate quantitative measures for 3D confocal volumes of endometrial glands.
Arth Patel is an osteopathic medical student with an undergraduate degree in biology. HIs research is focused on quality assurance for radiologists in aiding to detect vertebral fractures on thoraco-abdominal CT images.
Ethan Tu is a biomedical engineering graduate student who received undergraduate degrees in biomedical engineering and computer science. His master’s degree research focus was on biosensors. Currently, his thesis work involves improving image processing techniques for magnetic particle imaging.
David Filipovic is a PhD candidate in Biomedical Engineering and Computational Mathematics, Science, and Engineering. His thesis work focuses on computational prediction of transcription factor – DNA binding and its effects on gene expression.
Muneeza Azmat is a Computational Mathematics, Science, and Engineering graduate student. She is studying blood tissue exchange models and methods for uncertainty quantification of machine learning methods applied to heterogeneous data.
Nate Kauffman is an MD/PhD student in the College of Human Medicine and Comparative Medicine and Integrative Biology programs. His thesis work focuses on inducing immune responses in breast cancer using internal fractionated radiotherapy.
Adam Alessio, Faculty Advisor, is a professor in the departments of Computational Mathematics, Science, and Engineering, Biomedical Engineering, and Radiology. His research focus is on noninvasive quantification of disease through AI-inspired algorithms. His research group solves clinically motivated research problems at the intersection of imaging and medical decision making.
Northwestern University
Yikuan Li is a PhD candidate in the Health Sciences Integrated PhD Program at Northwestern University. His research focuses on integrating informatics into healthcare to deliver better treatment and improve population outcomes. His is working on applying natural language processing and machine learning to build predictive models with electronic health record data.
Adovich Rivera is a PhD candidate in the Health Sciences Integrated PhD Program at Northwestern University. He researches the role of social determinants of health on cardiovascular risk in people with HIV. He collaborates with clinician-researchers using real-world data to investigate predictors of clinical outcomes and compare treatment effectiveness.
Hanyin Wang is a PhD candidate in the Driskill Graduate Program at Northwestern University Feinberg School of Medicine. She researches biomedical informatics with concentrations in natural language processing and image processing. Her thesis work focuses on using computer vision and deep learning to detect critical findings in head CTs for intracerebral hemorrhage. She is also working on integrating social media data for healthcare research.
Yuyang Yang is an MD/PhD student at Northwestern University Feinberg School of Medicine, focusing on health informatics. His research interest is in using electronic health record data to build creative tools to improve patient safety and clinical contact tracing. He has worked on translational projects and has a background in basic science research.
Jingzhi Yu is a PhD student at Northwestern University Feinberg School of Medicine. His research interests are cardiovascular disease risk prediction using machine learning, and mobile health interventions to improve cardiovascular health. He has worked as a data analyst, focusing on health informatics studies of cardiovascular disease outcomes in underserved communities, supporting several large research networks.
Lindsay Zimmerman is a PhD candidate at Northwestern University. She has collaborated on developing informatics strategies to improve equity, including engaging patients to become partners, building informatics tools for efficient research and data visualization, and designing methods to understand the relationship between social determinants and health outcomes.
Yuan Luo, Primary Faculty Advisor, is a data scientist at Northwestern University. His research interests include machine learning, natural language processing, time series analysis, integrative genomic analysis, and big data analytics, with a focus on medical and clinical applications. He is associate professor, Department of Preventive Medicine, and Chief AI Officer, Northwestern University Clinical and Translational Sciences Institute (NUCATS) and I.AIM.
Faraz Ahmad, Faculty Advisor, is assistant professor of medicine-cardiology and faculty member, Center for Health Information Partnerships, Northwestern University Feinberg School of Medicine. He researches the development of technologies to collect, analyze, and apply electronic health data to improve clinical care, conduct trials, and generate real-world evidence.
Ike Okwuosa, Faculty Advisor, is assistant professor of medicine-cardiology and assistant dean of medical education at Feinberg School of Medicine. His research interests are in heart failure, pregnancy and cardiovascular disease, and chemotherapy-induced heart failure. He has published on disparities in cardiovascular disease and depression and cardiovascular outcomes.
Penn State
Junie Liang is a PhD candidate at the AI Research Laboratory. He received his master’s in computer science from South China University of Technology. He researches building predictive models for longitudinal data, and is experienced in machine learning and applications for large-scale, non-IID (independent and identically distributed) data. He is also interested in recommendation systems, fraud detection, and reinforcement learning.
Alyssa Tuan is a medical student at Penn State College of Medicine. She previously worked at the National Cancer Institute’s Surveillance Research Program establishing a virtual tissue repository linked to SEER data. She is involved in health policy with the Pennsylvania Medical Society Medical Student Section, and previously worked in the US Congress.
Neha Gupta is a medical student at Penn State College of Medicine. She co-founded State of Youth in 2019, along with Kids Rights and Facebook, a platform for young changemakers and social entrepreneurs to address the UN’s Sustainable Development Goals. Her research focus is on the utilization of innovative technologies such as Project ECHO, telehealth, and AI to address healthcare disparities.
Christian Park is a diagnostic radiology/nuclear medicine resident in the Department of Radiology at Penn State Milton S. Hershey Medical Center, where he is Head of AI for the Clinical Radiology Research Group. He is an MBA candidate at the Penn State Smeal College of Business, and is a member of the Trainee Editorial Board for Radiology: Artificial Intelligence. His research interests include AI, nanoparticle imaging, and data analytics.
David Foley is a PhD candidate at Penn State’s College of Information Sciences and Technology and has been a member of the AI Research Laboratory for three years. He has collaborated on cross-disciplinary research projects, including applying machine learning to cancer prognosis, and using causal analysis to assess algorithmic fairness. He has been a trainee in Penn State’s interdisciplinary Biomedical Big Data to Knowledge program for three years.
Nathan Cannon is a medical student at the Penn State College of Medicine. His research interests include intraocular lens power calculation formulas for cataract surgery, organ-on-a-chip engineering, and quality improvement in international pharmaceutical regulation. He is passionate about meeting needs and eliminating disparities for underserved populations.
Ravi Shah is a cardiovascular disease fellow at the Penn State College of Medicine. He is co-founder of the Health Policy Fellowship Initiative and the AMA-Medical Student Section Public Health Case Competition. His research focuses on using neural networks to predict cardiovascular disease outcomes. He is an MBA candidate at the UMass Amherst Isenberg School of Management.
Jennifer Kraschnewski, Faculty Advisor, is Professor of Medicine, Pediatrics, and Public Health Sciences. She researches behavioral interventions to promote healthy lifestyles in clinical and community settings. She is principal investigator for CDC REACH (Racial and Ethnic Approaches to Community Health), which provides Hispanic communities in Central Pennsylvania with tools to improve health, prevent diseases, and reduce disparities. She directs Penn State’s Project ECHO.
University of Illinois
Chaoqi Yang is an incoming PhD student at the University of Illinois Urbana-Champaign. His research goal is to build interpretable models for extracting information from large (unlabeled) health data. His recent work includes tensor completion for spatio-temporal COVID data, self-supervised learning on EEG signals, and deep learning for drug recommendations.
Yaroslav Daniel Bodnar, graduated from the Uniformed Services University of the Health Sciences F. Edward Hébert School of Medicine in 2017. He specializes in internal medicine and internal medicine/pediatrics, and is affiliated with OSF Saint Francis Medical Center.
Junyi Gao is a PhD student at University of Illinois Urbana-Champaign. His work focuses on developing machine learning and deep learning models for real-world healthcare challenges. His primary research interest is deep computational phenotyping for electronic health records, clinical trials, and population-level disease prediction.
Jason Kang is an incoming masters student at University of Illinois Urbana-Champaign. He graduated from UC Berkeley with degree in EECS (electrical engineering and computer science). He is interested in developing new machine learning techniques to tackle large-scale problems in healthcare.
Daniel Najafali is an incoming MD student at Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign. He is interested in developing machine learning and deep learning models to improve patient outcomes and to address healthcare challenges.
Jimeng Sun, Faculty Advisor, is a Health Innovation Professor at the Computer Science Department and the Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign. His research focuses on AI for healthcare, including deep learning for drug discovery, clinical trial optimization, computational phenotyping, clinical predictive modeling, treatment recommendation, and health monitoring.
Mary Stapel, Faculty Advisor, is Clinical Assistant Professor, University of Illinois College of Medicine Peoria. She is the Course Director for the Global Rural Med-Peds Residency Track and is Co-Director of the Innovation Rural Global Medicine Program at the University of Illinois College of Medicine Peoria. She is Assistant Program Director for the Internal Medicine-Pediatrics Residency Program, with a focus on global, rural, community, and population health.
Adam Cross, Faculty Advisor, is a pediatrician, pediatric hospitalist, and clinical informaticist who was recently appointed as the leader of the new Maximizing Opportunities for Children’s Healthcare Innovation (MOCHI) Lab at the Jump Trading Simulation and Education Center at OSF Healthcare. Over the past four years, he has provided care to underserved populations in New Mexico and Arizona, including Indigenous populations, refugees, and immigrants.
Scott Barrows, Faculty Advisor, is Clinical Assistant Professor, Emergency Medicine, University of Illinois College of Medicine Peoria, and Biomedical Visualization, University of Illinois at Chicago. He is also the director of Design Lab at Jump Trading Simulation and Education Center at OSF Healthcare.
GOLDEN GOPHERS, University of Minnesota
Anthony (Tony) Prisco is a Cardiovascular Diseases fellow in the Department of Medicine and a physician-scientist with experience in advanced mathematical techniques. During his internal medicine residency, he completed computational studies investigating the mechanisms of blood flow within left ventricle assist devices. His research also focuses on arterial waveform analysis using machine learning.
Alex Deakyne is a research scientist and graduate student at the University of Minnesota. He is pursuing a PhD in Bioinformatics and Computational Biology with a focus on deep learning and virtual reality for medical imaging. His research interests include rapid implementation of patient imaging to allow clinical interaction with 3D imaging, and using AI to automatically segment 3D imaging. His work has been published in the Journal of Applied Sciences.
Weston Upchurch is a research scientist and PhD candidate at the University of Minnesota. His research interests include translation muscle physiology, machine learning, and computational biomechanics. His PhD work focuses on in vitro assessments of contractile properties of biological (healthy and diseased ) tissues. His work has been published in Biomimetics.
Alex Dayton is an Internal Medicine resident in the Department of Medicine and is a physician-scientist with a focus on Bayesian graphical network modeling. As part of his PhD thesis, he has published studies on elucidating the mechanisms of salt-sensitive hypertension.
Myana Anderson is a graduate student at the University of Minnesota. She is pursuing her PhD in Bioinformatics and Computational Biology and conducts translational studies focusing on the physiology of black bear hibernation. She worked at Raytheon Technologies as a systems engineer focusing on tracking technologies. She has also helped develop a program for cooperative cognition for human-machine co-pilots.
University of Nebraska
John Windle, Faculty Advisor, is the Director of the Center for Intelligent Health Care at the University of Nebraska Medical Center. He is a Professor of Internal Medicine and a Holland Distinguished Chair in Cardiovascular Sciences.
Quinn Nelson is a medical student at the University of Nebraska Medical Center. He received a master’s degree in Translational Biomedical Research and undergraduate degrees in IT Innovation and Bioinformatics. His thesis research focused on big data applied physiology using the Medical Information Mart for Intensive Care database.
Mrinal Rawool is a PhD student at the University of Nebraska-Lincoln. She is interested in AI research, specifically, natural language processing, deep learning, Bayesian networks, and explainable AI.
Garrett Wirka is a PhD student at the University of Nebraska-Lincoln. He is interested in machine learning applications and implementation barriers, including model explainability and interpretability, causality, and knowledge modeling.
Thomas Windle is a Clinical Applications Programmer Analyst at the University of Nebraska Medical Center. He works at the Center for Intelligent Health Care and is well-versed in clinical informatics. He spent several years working on the classification of cardiovascular drugs based on the standardized nomenclature for clinical drugs (RxNorm) from the US Pharmacopeial Convention.
Ketemwabi Yves Shamavu is a PhD candidate at the University of Nebraska Medical Center. He is working toward a degree in biomedical informatics, with a specialization in AI and computer science. He is interested in clinical informatics, Bayesian networks, explainable AI, deep learning, and natural language processing. He was a Fulbright Scholar from 2015 to 2018.
LONGEVITY SOLUTIONS, University of Wisconsin-Madison
Josiah Hanna, Faculty Advisor, is assistant professor in the Computer Science Department at the University of Wisconsin, Madison. He studies a branch of machine learning called reinforcement learning (RL). The goal of the research is to develop and apply reinforcement learning algorithms that are effective with a limited amount of time interacting with a task.
Rufus Sweeney is a medical student at the UW School of Medicine and Public Health. He is Oklahoma Choctaw and is interested in solving difficult problems in Indian territory, such as diabetes and alcoholism. His background includes a year of diabetes basic science research that culminated in publication in Science magazine, as well as work in several startups.
Miriam Sweeney is a designer with expertise in user experience and user interface. She has experience in venture capital and product management and has successfully launched and grown companies from zero revenue to profitability.
Cassie Vanderwall is a clinical dietitian with experience as a leader and team member at UW Health. She is an instructor and researcher with a passion for disease prevention, wellness, and empowering individuals for better health. She founded the Lifestyle Change Program at UW-Madison, which helps patients modify their lifestyle to treat diabetes and prediabetes.
Sam Pabich is a faculty member in the Division of Endocrinology in the Department of Medicine. Her research focuses on obesity and diabetes. She is involved in projects assessing the efficacy of weight loss strategies, particularly psychological motivators, low-carbohydrate dietary interventions, and effective pharmaceuticals. She is interested in factors that affect patient adherence to therapeutic strategy and dietary control of diabetes.
Stephanie Johnson is manager of Teaching and Research Application Development (TRAD) at UW-Madison, which partners with researchers, instructors, and campus staff to conceptualize, design, and implement innovative software solutions. TRAD specializes in supporting research ideas, application development, data collection, and data visualization needs.