Members

Mohammad Al-Ani is a cardiologist for advanced heart failure and imaging (TTE, TEE, CMR, CCTA).

Key Research: Cardiomyopathy, extracorporeal membrane oxygenation, hypertrophic cardiomyopathy

Li Chen’s lab focuses on developing deep learning and statistical methods and software for analyzing large-scale multi-omics data, such as genetics, single-cell genomics, and metagenomics.

Key Research: aging and cancer, multi-omics data with imaging, EHR data

Raquel Dias’s lab develops and applies cutting-edge artificial intelligence (AI) methods to examine important research questions across multiple fields of biological sciences, agricultural sciences, and biomedical research.

Key Research: biological sciences, agricultural sciences, biomedical research

Reza Forghani’s research focuses on the use of AI to improve health through enhanced AI-assisted diagnostics, as well as non-interpretative AI applications for improving health care processes, quality, efficiency, and sustainability.

Key Research: precision diagnostic applications, neck oncology, neuroimaging

Xiao Fan’s primary interest lies in the application of AI to medical, biochemical, and genetic questions. She has completed projects on microRNA target prediction, annotation of intrinsically disordered regions in proteins, and prediction of protein crystallization.

Key Research: computational genetics, biochemical, genetic questions

Diego Guarin’s Movement Estimation and Assessment Laboratory at the University of Florida is pioneering the development of a new generation of AI tools for objectively assessing Parkinson’s disease from videos.

Key Research: neural control of movement, neurological conditions and their effect on movement, machine learning and computer vision

Faheem Guirgis’s current and future work is leveraging AI to perform multiomics analysis on ‘omics data from critically patients with Sepsis and ARDS.

Key Research: sepsis, lipid metabolism, clinical trials

Sarah Kim is a practicing pharmacometrician who is passionate about model-informed and AI-powered drug development and is currently leading several computational modeling projects to create and innovate quantitative solutions in healthcare.

Key Research: disease-drug-trial modeling and simulation, AI applications to maximize the use of imaging data in drug development

Mei Liu’s long-term research goal is to develop innovative (AI/ML) methods to support Predictive, Preventive, Personalized, and Participatory (P4) medicine.

Key Research: artificial intelligence, biomedical informatics, machine learning

Alicia Mohr is an active surgeon-scientist who cares for critically ill trauma patients and whose research focuses on the interactions between stress, chronic inflammation, bone marrow dysfunction, and an altered microbiome following traumatic injury.

Key Research: critical care surgery, acute respiratory distress syndrome, anemia

Michael Pizzi is interested in developing machine learning algorithms to identify trends in patient physiologic data to alert clinicians of impending intracranial pressure increases and worsening brain tissue compliance.

Key Research: neurocritical care, acute ischemic stroke,
traumatic brain injury

Louis Scampavia’s team employs High Throughput Screening (HTS) robotics to accelerate the drug discovery process thorough full automation of large-scale screening experiments.

Jinnie Shin has expertise in application of theory-based natural language processing and learning analytics in education research, and she has focused on investigating how to bridge the gap between psychometric analysis and artificial intelligence in education research.

Yu Wang’s research aims to develop AI/ML-based methods for building reliable and trustworthy cyber-physical systems (such as implanted/wearable devices) for healthcare applications.

James Wynn’s research is focused on the investigation of neonatal-specific innate immune cellular function and inflammatory signaling during sepsis as well as development of novel therapeutic immunomodulatory strategies aimed at improving sepsis outcomes. 

Feifei Xiao’s research involves using machine learning methods to build valid predictive models to resolve public health–related problems, such as using support vector machine methods to predict aphasia severity and specific language measures using multi-modal neuroimaging datasets.

The aim of Jie Xu’s research is to develop integrative, fair, and interpretable approaches that can effectively mine insights from big health data, towards accelerating precision medicine.

Rui Yin’s research seeks to improve public health at both individual and population levels, providing insights into biological and medical problems with computational approaches.

Dr. Dasa’s research seeks to use Big Data analytics, Casual Reference and machine Learning coupled with Real Word Evidence (RWE) to explore ways to enrich patient recovery.

At UF, Ivan Ruchkin leads the Trustworthy Engineered Autonomy (TEA) Lab. His research aims to make autonomous systems safer and more trustworthy. He developS techniques, tools, and methodologies for modeling, analyzing, verifying, controlling, and monitoring autonomous robotic and cyber-physical systems.

Dr. Gong’s research interests are centered around the convergence of deep learning, medical imaging, and data science to enhance the diagnosis and treatment monitoring of various diseases, particularly Alzheimer’s disease (AD) and cancer. His work involves developing novel methodologies in medical physics-informed deep learning, leveraging prior information-guided network design, and applying clinical task-driven network training for more accurate and precise results.

Dr O’Dell is an Associate Professor in the Department of Radiation Oncology in Gainesville. As part of the Therapeutic Medical Physics faculty, he serves as a research mentor for graduate student research. Dr O’Dell oversees the Medical Image and Computational Analysis Lab, which is interested in discovering and applying novel image analysis and image-based computational techniques for improved detection, follow-up, and treatment of cancer.

Dr. Singh Ospina is an Associate Professor in the Division of Endocrinology, Diabetes and Metabolism at the University of Florida. She is board certified in Internal Medicine. She was awarded her medical degree from the University of Panama, Panama. She received her Endocrinology, Diabetes and Metabolism fellowship training at the Mayo Clinic, Rochester where she also completed a Master in Clinical and Translational Science.

Amelia Winger-Bearskin is an artist who innovates with artificial intelligence in ways that make a positive impact on our community and the environment. She is a Banks Family Preeminence Endowed Chair and Associate Professor of Artificial Intelligence and the Arts, at the Digital Worlds Institute at the University of Florida.  She is the inventor of Honor Native Sky, a project for the U.S. Department of Arts and Culture: Honor Native Land Initiative. She founded Wampum.Codes which is both an award-winning podcast and an ethical framework for software development based on indigenous values of co-creation. 

Dr. Hochhegger has a distinguished research career in both the domain of securing grants and extensive peer-reviewed publication activity.

Dr. Newbutt is an Assistant Professor of Advanced Learning Technologies and Director of the Equitable Learning Technology Lab (ELTL) in the Institute for Advanced Learning Technologies. He brings many years’ experience of developing technologies with autistic, and underserved groups. This work began by exploring multimedia programs for deaf communities in the UK. Beyond this, he has also designed and evaluated learning technologies (namely: podcasting and vodcasting) in undergraduate classrooms. 

Mingzhang Yin is an Assistant Professor of Marketing at the Warrington College of Business of University of Florida. His primary research interests are in the intersection of quantitative marketing, Bayesian statistics, probabilistic machine learning, and causal inference. He develops methodologies for probabilistic models, approximate Bayesian inference, and observational studies. He explores marketing applications in online advertisement, personalization, E-commerce and data-driven consumer analysis.

Masoud Rouhizadeh, M.A., Prof.MS., M.S., Ph.D., serves as an Assistant Professor in the Department of Pharmaceutical Outcomes and Policy at the University of Florida. Through the University’s AI in the Health Sciences Initiative, he plays central leadership roles as the Lead for the College of Pharmacy’s AI Task Force and as the Lead for the AI Collaboration Hub at the Intelligent Critical Care Center. Additionally, he holds an Adjunct Assistant Professor appointment within the Division of Biomedical Informatics and Data Science at the Johns Hopkins School of Medicine.

Mackenzie Bolen is a graduate student in the biomedical neuroscience Ph.D. program at the University of Florida, College of Medicine. She is interested in identifying the interplay between inflammatory bowel disease (IBD) and Parkinson’s risk via the lens of the immune system.

Dr. Ou’s research is inspired by the community-centered informed hazard-oriented decision-making, which lead to the development of high fidelity and computational efficient regional-scale simulation platform. Her research experience includes physical and surrogate modeling of complex civil infrastructure systems, machine learning, information theory, advanced experimental testing, model updating, and the integration of data analytics with physical-based modeling.

Dipankar Gupta is a board-certified physician specializing in pediatrics, pediatric cardiology, and pediatric critical care medicine. He received his medical degree from the University College of Medical Sciences at the University of Delhi in India. He then pursued pediatric residencies at Safdarjang Hospital at the University of Delhi and at Brookdale University Hospital and Medical Center in Brooklyn.

Dr. Naveen Baskaran is an internist in Gainesville, Florida and is affiliated with UF Health Shands Hospital. He received his medical degree from Madras Medical College and has been in practice between 11-20 years. Dr. Naveen Baskaran has expertise in treating inpatient dementia, diabetes, chronic diabetes, among other conditions.

Dipankar Gupta completed medical school at the Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER) in Puducherri. He was a Rhodes scholar at Oxford University in England, where he earned a master’s degree in applied mathematics and a research doctorate in mathematical biology. He received his clinical training in internal medicine through rotations in various hospitals in the British National Health Service and completed a general neurology residency at the Institute of Neurological Sciences in Glasgow. He was fellowship trained in epilepsy and EEG at the Cleveland Clinic.
Dipankar Gupta’s career has been devoted to the care of patients with epilepsy, along with research in the science surrounding epilepsy. His publications have appeared in multiple peer-reviewed journals, and his work has been funded by the National Institute of Neurological Disorders and Stroke, as well as the American Epilepsy Society, among others.

Dr. Hu is currently serving as a Research Assistant Professor in the Department of Medicine at the College of Medicine and the Intelligent Clinical Care Center (IC3) at the University of Florida. His academic journey began with a bachelor’s degree in Electronic Information Engineering, followed by a Master’s in Computer Science. He earned a Ph.D. in Biomedical Engineering from the University of Florida in 2019. His research focuses on the application of advanced multimodal signal processing, machine learning, and AI to explore the complexities of cognitive function and address impairments in neurological and psychiatric disorders. Through this work, he aims to drive innovations in clinical decision-making, precision medicine, and patient care.

As a professor in the University of Florida Division of Transplantation and Hepatobiliary Surgery, I treat patients with liver cancer, liver disease, liver injury, bile duct cancer and bile duct injuries, mostly with surgery or with liver transplantation. Deceased donor transplantation grants me the privilege of making the most of tragedy and wrestling meaning from so many unanswered questions. I see transplantation as a miracle, and it amazes me every time.
My focus as a physician and scientist is on providing individualized care for each one of my patients. Right now, we work on the application of technology we develop in our lab to practical surgical and medical questions. Essentially, our focus is on getting the right drug or care to the right patient in the right amounts at the right times.
Before joining the division of transplantation and hepatobiliary surgery, I graduated with a doctorate degree in biochemistry and a medical degree from the University of California, San Francisco. Thereafter, I completed a general surgery residency and a fellowship in multivisceral transplant and hepatobiliary surgery from the University of California, Los Angeles.

Dr. Graim received her Ph.D. in 2016 from the University of California, Santa Cruz, advised by Professor Josh Stuart. She did postdoctoral research at Princeton University and the Flatiron Institute, Simons Foundation, working with Professor Olga Troyanskaya. Dr. Graim’s research operates at the confluence of life science research and computer science. Her lab develops machine learning models that integrate diverse large-scale genomics data to address key questions in human health and disease. These models effectively probe complex biological networks to answer questions arising from basic science and translational research. Dr. Graim’s overarching goal is to map the mechanisms of human diseases and to enable development of personalized therapies.

Key Research: bioinformatics, computational biology, machine learning, data science and informatics