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From a clinical perspective: diagnosis, staging, and assessment of speech and language disorders; informatics support for clinical research; data and AI governance; clinical documentation, communication, and workflow; adverse safety events. From a computational perspective: language model development and adaptation; summarization and discourse; information retrieval; representation learning. Evaluation, statistics, and visualization.

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Associate Professor at Oregon Health & Science University; vocateur teacher of data visualization and scientific communication; by nature somehow always The Guy Who Asks Awkward Questions And Gets Us All In Trouble.

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In my role leading team science I provide leadership on how to implement and evaluate best practices for collaboration building and team science on the Science Coordination & Community Engagement team. I am passionate about advancing community-centered solutions to advance birth justice, racial equity, and systems change through health policy.

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Principal Scientist in Team Science at Sage Bionetworks. 

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William Hersh, MD, FACP, FACMI, FAMIA, FIAHSI

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William Hersh, MD, FACP, FACMI, FAMIA, FIAHSI

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My research efforts have revolved around the area of information retrieval, also known as search, applied to biomedicine. My current work focuses on the application of search techniques to electronic health record data, aiming to improve patient cohort discovery and amplification of signals of rare diseases.

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Professor of Medical Informatics and Clinical Epidemiology at OHSU. Course Director of the AMIA Clinical Informatics Review Board Course. Co-PI of B2AI Voice Program.

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My research interests lie in collaborative care, chronic disease management, quality, and what clinical information systems need to support these areas. I'm also is interested in patient safety. 

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Professor of Medical Informatics and Clinical Epidemiology, Professor of Medicine (Division of General Internal Medicine and Geriatrics) at OHSU. Vice Chair of Medical Informatics and Clinical Epidemiology. Chief Research Information Officer. Internal Medicine Doctor. Team lead of Voice. 

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My research focuses on systems biology, specifically, on human cell architecture and molecular networks. Additionally, I am interested in bioinformatics concepts and technologies that have significantly advanced our understanding of genetic influences on diseases and their treatments.

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Professor of Medicine, Bioengineering, and Computer Science at UC San Diego with 20 years of experience, including roles as Director or Co-Director of multiple NIH-funded genomics and bioinformatics programs.

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My research focuses on developing advanced patient monitoring systems using AI and sensor technology. We are creating scalable machine learning methods for real-time, autonomous monitoring in ICUs and for assessing mental health in community-dwelling patients using wearable technology.

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Associate Professor in the J. Crayton Pruitt Family Department of Biomedical Engineering, Electrical & Computer Engineering, & Computer & Information Science & Engineering at University of Florida. 

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I am interested in integrating AI into laryngology to enhance voice research, healthcare digitization, and data driven care. I am dedicated to improving health systems efficiency and care quality through technology and collaborating with various partners to optimize patient care.

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Assistant Professor of Otolaryngology at USF Health Morsani College of Medicine. Contact PI of Bridge2AI Voice. 

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My research includes developing tools for intelligent human-centered health care that delivers optimized care tailored to a patient’s “personal clinical profile” using digital data. Much of my interest lies in postoperative complications, specifically sepsis and acute kidney injury. 

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Senior Associate Dean for Research Affairs at the University of Florida in College of Medicine. R. Glenn Davis Professor of Medicine, Surgery, Anesthesiology, and Physiology & Functional Genomics. Director of the Intelligent Clinical Care Center. Co-PI of CHoRUS. 

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My research focuses on leveraging large biomedical datasets for predictive modeling and precision medicine, including the development of computational tools and clinical models to enhance patient care and treatment efficacy.

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Professor at Yale School of Medicine, specializing in medical informatics and data science, with extensive experience in software development and system architecture.

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My research focuses on acquisition and analysis of telemetry waveform, EEG, medication administration, and contextual electronic health record data, linking these to clinical outcomes. Using this data at MGH and through national consortia, my work aims to develop approaches that individualize patient care as well as develop and test new therapies.

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Director of the Massachusetts General Hospital Neurosciences Intensive Care Unit, Director of the MGH Neurosciences Data Science and AI Center, and Associate Professor at Harvard Medical School. 

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My research interests include health information technology integration into clinical workflows; predictive modeling utilizing traditional statistical methods, machine learning/deep learning, and natural language processing; implementation and clinical translation of these models. 

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Professor of Ophthalmology and Division Chief for Ophthalmology Informatics and Data Science at UCSD. Co-PI of AI-READI. 

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I aim to enhance our understanding of age-related and glaucomatous changes in the eye by developing methods to detect these changes more efficiently and reduce necessary testing. My research also focuses on identifying risk factors that predict rapid progression of glaucoma.

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Professor at the Viterbi Family Department of Ophthalmology at UCSD. Co-PI with Dr. Sally Baxter on the Skills and Workforce Development Module and site PI (with Dr. Sally Baxter as co-PI) on the Data Module.

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My research focuses on finding the connections between the eye and the brain using non-invasive imaging, Big Data, and advanced computational approaches.

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Klorfine Family Endowed Chair Professor of Ophthamology and Director of of Clinical Research in the Department of Ophthamology at the University of Washington. Co-PI of AI-READI. 

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I am interested in the intersection of large clinical medical datasets and non-traditional computational techniques such as applying novel visualization approaches to analyze results from cloud and cluster-based computing environments.

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C. Dan and Irene Hunter Endowed Professor of Ophthalmology at the University of Washington and PI of AI-READI. 

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My research interests lie at the intersection of clinical, molecular, and imaging data. My group focuses on applying techniques from modern data science strategies, particularly machine-learning, and creating biomarkers to help ensure therapies are selected that maximize cure and minimize morbidities. 

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Professor of Human Genetics and Urology at UCLA. Director of the UCLA Jonsson Comprehensive Cancer Center’s Cancer Data Science Program. Associate Director of Cancer Informatics at the UCLA Institute for Precision Health.

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I am interested in big data analytics, machine learning, natural language processing, bioinformatics, and computational medicine. My work involves developing algorithms to unearth patterns in extensive, multi-modal biomedical datasets, innovating in areas such as representation learning, knowledge graphs, and data integration, with strong collaborations with biomedical researchers and physicians.

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Leonard Kleinrock Chair Professor in Computer Science and Computational Medicine at UCLA. Director for Training on AI/ML Basic Concepts and Special Topics Education Modules.

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My research interests include informatics and data science for biomedical research and healthcare in areas related to distributed information architectures and mHealth. My work bridges contemporary computational approaches with the opportunities arising from the breadth of biomedical observations and the EHR, tackling the associated translational challenges.

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Professor of Radiological Sciences, Bioengineering & Bioinformatics at UCLA. Senior Associate Director for Informatics, UCLA Clinical & Translational Science Institute. Senior Associate Dean for Bioscience Graduate Programs & Postdoctoral Affairs. David Geffen Chair in Informatics. for the Bridge2AI Bridge Center Tools Team at UCLA. Co-PI for B2AI Bridge Center. 

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My research interests include prevention of cardiovascular disease as it pertains to diabetes and social determinants of health. 

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Professor of Medicine/Cardiology at UCLA. Director of the UCLA Women’s Cardiovascular Health Center, the UCLA-Barbra Streisand Women’s Heart Health Program, Co-Director of the UCLA Program in Preventive Cardiology, and Director of the UCLA Fellowship Program in Cardiovascular Diseases. Attending Cardiologist. Co-PI of the Bridge2AI Bridge Center Training Team at UCLA. 

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My research interests center around proteome biology and data science within the framework of cardiovascular health and integrating AI/ML application into BioMed. At B2AI Bridge Center we have created education curricula including lectures on Ethical Trustworthy AI (ETAI), AI/ML Workflows, Large Language Models (LLMs), and Data Generation Projects (DGPs).

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Professor of Physiology, Medicine/Cardiology, & Biomedical Informatics at UCLA. Director of Integrated Data Science Training in Cardiovascular Medicine; Associate Director of Scalable Analytics Institute Computer Science UCLA. PI of NIH B2AI Bridge Center Training. 