Data Intelligence Systems Lab (DISL) » Department of Epidemiology » College of Public Health and Health Professions

Mission Statement

DISL’s interests are in the areas of data science and machine learning, with particular focus on biomedical modelling. Our research activities include both theoretical and applied studies aimed at developing prediction models of future health and life aided by technology and data intelligence. Furthermore, we are innovating research in data science by hybridizing theory-based approaches with hypothesis-free, bottom-up data mining. We are committed to fostering an environment of diversity and inclusion both through research, education and scholarly activities. DISL’s vision is pursuing ideas in “humanely ethical” artificial intelligence for health and beyond, working to ameliorate recent discomforting results in social and welfare modelling, as “biased algorithms are everywhere, and no one seems to care.”

People

Team Lead

PHHP Coordinator for AI

Mattia Prosperi

Professor And College Coordinator Of Artificial Intelligence

Phone: (352) 273-5860

Email: m.prosperi@ufl.edu

CV: View Curriculum Vitae:

Full Profile

Current Members

Name	Title	Email
Shantrel S Canidate	Clinical Assistant Professor	ssc1987@ufl.edu
Inyoung Jun	Graduate Research Assistant	inyoungjun@ufl.edu
Yiyang Liu	Postdoctoral Scholar	yliu26@ufl.edu
Simone Marini	RES AST PROF	simone.marini@ufl.edu
Shannan N Rich	GRADUATE AST-R	shannanrich@ufl.edu
Rodrigo A Mora	OPS-Spons Prjs Non-Clerical	rmora1228@ufl.edu
Hae Jin J So	Data Intelligence Research Coordinator	hso@ufl.edu
Tayla M Hunt	Special Projects Coordinator	taylamoore@ufl.edu

Former Members


Zhaoyi Chen	Jae Min	Kai Wang	Shantanu Ghosh

Collaborators

Dr. Marco Salemi
Professor in Department of Pathology
Emerging Pathogens Institute

Dr. Ilaria Capua
Professor in Department of Animal Sciences
Director of One Health Center for Excellence

Dr. Jiang Bian
Associate Professor in Department of Health Outcomes & Biomedical Informatics
Director of Cancer Informatics Shared Resource

Dr. Christina Boucher
Assistant Professor in Department of Computer & Information Science & Engineering

Dr. Alberto Riva
Director of Digital Biology Group
Bioinformatics Associate Scientist
Interdisciplinary Center for Biotechnology Research

Dr. Volker Mai
Associate Professor in Department of Epidemiology

Dr. Robert L. Cook
Professor in Department of Epidemiology
Director of Southern HIV Alcohol Research Consortium

Workshop

Current Projects

NSF SCH INT Enabling real-time surveillance of antimicrobial resistance
Aims at developing computational tools to process and analyze high-throughput sequencing data from antimicrobial resistance studies using mobile and portable technologies
Forecasting trajectories of HIV transmission networks with a novel phylodynamic and deep learning network
Aims at fusing deep learning with phylodynamics modelling toward multi-factor prediction of transmission clusters in the HIV epidemic
COV-DYNAMITE
Dynamic clustering of SARS-CoV-2 phylogenies under heterogeneous sampling to identify and forecast transmission hotspots
Antimicrobial Resistance
Our latest project studies the acquisition of antibiotic resistance in pathogens through clinical and agricultural surveillance and development of novel methods to analyze metagenomics data. This project is supported by National Institute of Allergy and Infectious Diseases.
HIV
We are currently pursuing several projects on HIV transmmission: 1) Developing novel theoretical and technical framework to model HIV transmission clusters, 2) geospatial modeling of HIV drug resistance in Florida, and 3) investigating the role of viral evolution in HIV-associated neurocognitive disorders. These projects are supported by National Institute of Allergy and Infectious Diseases, National Institute of Neurological Disorders and Stroke, and Florida Department of Health.
Job Loss
Using deep learning and natural language processing, we are studying individual and network determinants of dramatic life events like job loss using social media. This project is supported by National Science Foundation.

News

Abstract: “Longitudinal analysis of HIV clinical outcomes reveals persistent racial and ethnic disparities in Florida from 2012-2019” by Rich SN, Hu H, Xia Y, Liu Y, Lucero R, Spencer EC, Cook RL, & Prosperi M won second best abstract at the Florida Community, Providers, Research Conference on HIV in April 2021.
Jun I, Rich SN, Bian J, Chen Z, Prosperi M. Challenges in replicating secondary analysis of electronic health records data with multiple computable phenotypes: a case study on methicillin-resistant Staphylococcus aureus bacteremia infections. International Journal of Medical Informatics. September 2021, 104531, ISSN 1386-5056.
Dr. Prosperi and Dr. Salemi, Pathology (in collaboration with Dr. Azarian at University of Central Florida) receive funding from the Rockefeller Foundation to expand genomic surveillance and epidemiology capacity in Central Florida and Southeastern US.
Dr. Prosperi published a new paper on Causal AI: “Propensity score synthetic augmentation matching using generative adversarial networks (PSSAM-GAN).“
Dr. Marini’s proposal to the Consortium for Medical Marijuana Clinical Outcomes Research has won a grant ($67,309) to study the effects of cannabidiol (CBD) in curbing chronic inflammation of people living with HIV at the single-cell level. Dr. Simone Marini is PI and Dr. Carla Mavian is MPI.
DISL Postdoctoral scholar Yiyang published “Liu Y, Siddiqi KA, Cook RL, Bian J, Squires PJ, Shenkman EA, Prosperi M, Jayaweera DT. Optimizing identification of people living with HIV from electronic medical records (EHR): Computable phenotype development and validation.” at Methods of Information in Medicine [in press], 2021
Inyoung Jun received KSEA-KUSCO* scholarship which is to recognize Korean graduate students in the US who excel in academics as well as in services to the community, and have demonstrated a potential to become future leaders of the society for closer cooperation between the U.S. and Korea.
DISL PhD student Inyoung Jun presented her work “How can machine learning improve prediction of hospital deaths due to drug-resistant bacterial disease?” at UFII Fellows Journal Club on April 29th, 2021.
Dr. Prosperi has been named Coordinator for AI for the College of Public Health and Health Professions.
Our new method for causal AI (DAG bagging) has been published by the Journal of Biomedical Informatics.
Drs. Boucher, Jeong, Prosperi, and Ruiz have been awarded the NSFSmart and Connected Health grant “Enabling real-time surveillance of antimicrobial resistance” to develop computational tools tailored to mobile/portable technology and protocols.
Dr. Prosperi et al. published the paper “Causal inference and counterfactual prediction in machine learning for actionable healthcare” in Nature Machine Intelligence
DISL student Inyoung Jun has been awarded the UF Informatics Institute Graduate Student Fellowship
Dr. Prosperi (in collaboration with Dr. Salemi, Pathology; Dr. Cook, Epidemiology; and Dr. Wu, Engineering) has been awarded an new R01 from NIH NIAID as MPI, titled “Forecasting trajectories of HIV transmission networks with a novel phylodynamic and deep learning framework”
Dr. Prosperi with Dr. Natalie Dean (UF Biostatistics) and Dr. Marco Salemi (UF Pathology) have been awarded a new NSF project in response to the COVID-19 epidemic, titled RAPID: Dynamic Identification of SARS-COV-2 Transmission Epicenters in Presence of Spatial Heterogeneity (COV-DYNAMITE)
Read our new comment on the importance of developing causal AI
Check out our latest commentary on the never-ending rivalry between statistics and machine learning
Dr. Prosperi and Dr. Bian (HOBI Dept) published a correspondence in Nature Machine Intelligence, titled “Is it time to rethink institutional review boards for the era of big data?”

Kai Wang graduates — Kai Wang earned his PhD and will pursue a postdoctoral opportunity at Harvard. Congratulations to Dr. Wang!

Recent Publications

For the most up-to-date list, please visit: Google Scholar

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