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DTSTART;VALUE=DATE:20250422
DTEND;VALUE=DATE:20250425
DTSTAMP:20260403T191631
CREATED:20241119T182243Z
LAST-MODIFIED:20250313T200547Z
UID:3454-1745280000-1745539199@bridge2ai.org
SUMMARY:Voice Symposium & Hackathon 2025
DESCRIPTION:REGISTRATION IS OPEN FOR THE 2025 VOICE AI SYMPOSIUM + HACKATHON \nSUBMIT ABSTRACTS BY DECEMBER 15TH \nDISCOUNTED REGISTRATION FOR B2AI MEMBERS (see below for details) \n \nWe’re excited to invite you to the 2025 Voice AI Symposium and Hackathon\, presented by the NIH Common Fund’s Bridge2AI-Voice consortium! From April 22-24 in Tampa\, this unique three-day event will bring together researchers\, patients\, clinician-scientists and top minds in artificial intelligence\, bioethics\, voice biomarkers\, and transformative healthcare for an innovative and interactive hands-on experience. \n2025 Voice AI Symposium + Hackathon \nWhen: April 22-23 (Symposium) + Apri 24 (Hackathon) \nWhere: Sunny Tampa Florida! At the J.W. Marriott and the Morsani College of Medicine\, Taneja College of Pharmacy and Heart Institute\, Water Street \nHIGHLIGHTS FROM LAST YEAR \nWhy Attend? \nOur theme this year\, “Translating AI Research into Reality: Implementing Voice Biomarkers for Transformative Healthcare”\, will spotlight the real-world applications and ethical considerations of voice AI in healthcare. The symposium will feature prominent industry leaders and renowned bioethics experts\, providing a valuable platform for interdisciplinary discussion and learning. Last year\, we welcomed speakers from Google\, Microsoft\, Canary Speech\, Sonde Health\, Redenlab\, NIH\, and numerous international startups. \nHighlights of the Symposium: \n\nInteractive Panel Discussions: Engage with leaders and experts on the future of voice AI in healthcare\, including ethical considerations and practical applications.\n\n\nDeep Dive Workshops: Hands-on sessions designed to deepen your understanding and skill set in AI and voice biomarkers.\n\n\nTech Fair: A showcase of the latest tools and innovations in the field\, allowing you to explore cutting-edge technologies up close.\n\n\nHackathon: A full day dedicated to solving real-world healthcare challenges alongside other participants\, fostering collaboration and innovation.\n\n\nPoster Competition: A fantastic opportunity for researchers to present their work\, share insights\, and receive valuable feedback from peers and experts.\n\n\nNetworking Event: Connect with professionals across academia\, industry\, healthcare\, and patient advocacy. This is your chance to build valuable connections and explore collaborative opportunities.\n\nSecure your place today and join us in Tampa for an unforgettable experience at the forefront of AI and healthcare. \nB2AI members receive $100 off the cost of registration with the following code: B2AIdiscount! \nRegister Now:  https://www.eventsquid.com/register/26215 \nSubmit Abstracts: https://www.eventsquid.com/register/26217 \nWe look forward to seeing you in April! \nWarm regards\, \nJamie Toghranegar \n  \nJamie Toghranegar\, SLPD\, CCC-SLP\, CBIS \nResearch Project Manager\, Bridge2AI Voice \nSpeech Language Pathologist \nUSF Health Morsani College of Medicine \nUniversity of South Florida \n12901 Bruce B. Downs Blvd. \nTampa\, FL 33612
URL:https://bridge2ai.org/event/voice-symposium-hackathon-2025/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250514
DTEND;VALUE=DATE:20250801
DTSTAMP:20260403T191631
CREATED:20250610T145521Z
LAST-MODIFIED:20250611T220904Z
UID:5494-1747180800-1754006399@bridge2ai.org
SUMMARY:CM4AI Graph Community Detection Challenge
DESCRIPTION:The Opportunity and A Call to Action \nWe are excited to announce the launch of the CM4AI Graph Community Detection competition on Kaggle!  Participating in this challenge will give you a unique opportunity to be part of groundbreaking advancements in biomedical research as part of the Cell Maps for AI (CM4AI) initiative. \nChallenge Dates: May 14\, 2025 – July 31\, 2025 \nJoin the Frontier of Biomedical AI Research! \nThe Bridge2AI Functional Genomics Grand Challenge (Cell Maps for AI/CM4AI) is pleased to announce our Kaggle competition focused on using the data and tools generated by CM4AI and leveraging emerging AI/ML methods\, such as graph and quantum machine learning\, to advance biomedical science and precision medicine. \nCompetition Overview \nThe goal of this competition is to develop methods that identify communities within biological networks to uncover hidden structures and provide new insights into biological systems. By participating\, you will help push the boundaries of AI/ ML applications in the life sciences. \nWhy Participate? \n\nShape the Future of Science: Successful approaches can redefine how we understand cellular systems\, paving the way for innovative therapeutic strategies for cancer and other human disease.\nChallenge Yourself: Engage in solving a cutting-edge problem that bridges the gap between AI/ML and molecular biology.\nBe Part of a Global Community: Collaborate and compete with experts\, researchers\, and enthusiasts from diverse fields with mentorship from CM4AI investigators.\n\n Key Details \n\nCM4AI Resources: https://cm4ai.org and https://youtube.com/@CM4AI\nCompetition Link: https://www.kaggle.com/t/b25c9b18a199411892011bfb88680cf3\nObjective: Detect and identify communities from CM4AI SEC-MS data\, contributing to the Cell Maps for AI initiative.\n\nWho Should Join? \nThis competition is open to anyone passionate about artificial intelligence/machine learning\, computational biology\, or biomedical research. Whether you’re a seasoned expert or an enthusiastic beginner\, your contributions can help drive the next wave of discoveries. \nDon’t miss this opportunity to be part of a transformative journey at the intersection of AI and molecular biology! \n \nJoin the Challenge Now
URL:https://bridge2ai.org/event/cm4ai-graph-community-detection-challenge/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250520
DTEND;VALUE=DATE:20250523
DTSTAMP:20260403T191631
CREATED:20250321T153450Z
LAST-MODIFIED:20250520T200817Z
UID:4379-1747699200-1747958399@bridge2ai.org
SUMMARY:Spring 2025 All Hands & Open House Meeting
DESCRIPTION:All Hands Conference \nOur May 2025 All Hands Conference will be an opportunity for researchers and experts to engage in vibrant discussions. The NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2Al) program will propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (Al) that tackles complex biomedical challenges beyond human intuition. The biomedical research community generates a wealth of data\, but most of these data are not suitable for machine learning because they are incomplete. By bringing technological and biomedical experts together with social scientists and humanists\, the Bridge2Al program will help bring solutions to this deficit. \nOpen House \nThe Bridge2Al Open House will focus on collaborative approaches\, learn about current considerations\, explore new datasets\, and discuss other key issues related to bridging the gap from biomedical information to Al. Sessions will be centered around the activities of the Bridge2Al Data Generation Projects\, which stemmed from Grand Challenges put forth by the National Institutes of Health (NIH). \n📋 Check out Digital Program
URL:https://bridge2ai.org/event/now-through-april-18th-2025-register-for-the-spring-2025-all-hands-open-house-meeting/
LOCATION:NIH Neuroscience Center\, 6001 Executive Blvd\, Rockville\, MD\, 20852\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250522
DTEND;VALUE=DATE:20250523
DTSTAMP:20260403T191631
CREATED:20250422T141736Z
LAST-MODIFIED:20250502T154931Z
UID:5197-1747872000-1747958399@bridge2ai.org
SUMMARY:Bridge2AI Spring 2025 Open House
DESCRIPTION:Join us for the second annual Bridge2AI Open House on Thursday\, May 22\, 2025\, in Rockville\, MD! This event provides an amazing opportunity for scientists\, ethicists\, coders\, community members\, and practitioners with diverse expertise and experience levels to come together to build unique solutions that will help solve a range of relevant problems. The Bridge2AI Open House will focus on key issues related to bridging the gap from biomedical information to AI. Sessions will be centered around the activities of the Bridge2AI Data Generation Projects\, which stem from the National Institutes of Health’s (NIH) Grand Challenges. \nRegister By: May 16\, 2025\nRegister Here
URL:https://bridge2ai.org/event/bridge2ai-spring-2025-open-house/
LOCATION:NIH Neuroscience Center 6001 Executive Blvd Rockville MD United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250617T150000
DTEND;TZID=America/New_York:20250617T160000
DTSTAMP:20260403T191631
CREATED:20250605T174346Z
LAST-MODIFIED:20250605T174438Z
UID:5479-1750172400-1750176000@bridge2ai.org
SUMMARY:B2AI Discussion Forum on Emerging ELSI Issues: “Ethical\, Legal\, and Social Implications in AI Quality Assurance and Model Validation: Case Studies and Evolving Approaches” by Shannon McWeeney\, Ph.D.
DESCRIPTION:
URL:https://bridge2ai.org/event/b2ai-discussion-forum-on-emerging-elsi-issues-using-ai-in-patient-care-emerging-legal-issues-by-dr-michelle-mello-phd-copy/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250630
DTEND;VALUE=DATE:20251011
DTSTAMP:20260403T191631
CREATED:20250612T142733Z
LAST-MODIFIED:20251007T154816Z
UID:5501-1751241600-1760140799@bridge2ai.org
SUMMARY:MICCAI 2025 Multi Camera Robust Diagnosis of Fundus Diseases(MuCaRD) Challenge
DESCRIPTION:Introduction\nFundus imaging is an indispensable tool in primary care for the early detection of major ophthalmic diseases—such as diabetic retinopathy and glaucoma—and for guiding treatment decisions. By noninvasively visualizing the retinal vasculature and subtle changes at the optic nerve head\, fundus exams also serve as indicators of systemic health\, making them a first line of patient management. With the widespread adoption of high-resolution\, digital camera–based fundus imaging\, a variety of imaging modalities have rapidly entered clinical practice. Recently\, deep-learning–based models for classifying fundus diseases have demonstrated high sensitivity and specificity and have proven their clinical utility by being integrated into numerous software medical devices (SaMD). For example\, automated diabetic retinopathy screening systems and glaucoma-progression monitoring tools are already commercially available\, contributing broadly to diagnostic support and patient screening. However\, most models are trained and validated on data from a single camera type\, which limits their performance when applied to images from new or infrequently used devices. To overcome these practical constraints\, this challenge aims to develop AI models that deliver consistent diagnostic performance across diverse camera environments. Through the Multi-Camera Robust Diagnosis of Fundus Diseases (MuCaRD) challenge\, we will evaluate both robust classification algorithms that generalize to unseen devices and adaptive learning techniques that can quickly fine-tune using only a few sample images from a new camera. \n\n\nChallenge Description\n\nOverview:\nThe MuCaRD challenge addresses a critical gap in AI‐driven fundus screening: ensuring consistent performance across both familiar and unseen camera systems. Participants will develop and benchmark models under realistic constraints—training on a limited set of images from one device and then evaluating robustness and adaptability on entirely new devices. By simulating clinical and commercial deployment scenarios\, MuCaRD promotes methods that generalize beyond a single data source and can quickly fine‐tune to novel imaging hardware. \n\n\nTasks:\n\nTask 1: Zero-Shot Classification\nTrain on fundus images from a single camera and evaluate on completely unseen devices. Participants perform two separate binary classifiers (glaucoma vs. normal\, and referable DR vs. non-referable)\, submitting full model code and weights to the CodaLab platform. A hidden validation set (200 images each from Optomed Aurora\, Mediworks FC162\, Optos Ultra Wide\, Canon CR2) and a similarly‐sized test set ensure no data leakage.\nTask 2: Few-Shot Test-Time Adaptation\nExtend Task 1 by leveraging a small support set (5 labeled images per new camera: 1 positive\, 4 negative) provided online during validation and test phases. Models should demonstrate on-the-fly adaptation within a 10 s/image inference limit\, showcasing both robustness and efficient fine-tuning.\n\n\n\nDatasets:\n\nAI-READI dataset: A rigorously curated set of high-resolution color fundus images acquired on Optomed Aurora and Eidon cameras across three Bridge2AI partner sites (UAB\, UCSD\, UW). Images span all four type 2 diabetes severity categories and include expert-verified annotations for diabetic retinopathy stage\, image quality scores\, and linked clinical metadata (age\, sex\, HbA1c\, blood pressure\, comorbidities). This cohort is optimized to benchmark zero-shot model performance and cross-device generalization.\nMediwhale Collection: Training from one CR2 and testing images from 5 different cameras.\n\n\n\nEvaluation & Metrics:\nPerformance is measured by the average of the Area Under the ROC Curve (AUROC) and the Area Under the Precision–Recall Curve (AUPRC) for each disease. To mirror clinical feasibility\, all inference and adaptation steps must complete within 10 seconds per image\, though this limit does not directly penalize the score. Submissions are limited to two runs per day during validation to curtail leaderboard overfitting. \n\n\n\nImportant Dates\n\nTraining Release: June 30\, 2025\nValidation Submission: June 30 – August 15\, 2025\nTest Submission: August 15 – August 23\, 2025\nWinner Announcement: August 30\, 2025\nWorkshop: October 6–10\, 2025\n\n\n\nAwards\nCertificates will be presented to the top three teams in each task.\nThe first and corresponding authors of the winning teams will be invited to co-author the challenge summary paper and to present their results at the workshop. \n\n\nContact\nFor inquiries\, please email: g.young@mediwhale.com
URL:https://bridge2ai.org/event/miccai-2025-multi-camera-robust-diagnosis-of-fundus-diseasesmucard-challenge/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250715T150000
DTEND;TZID=America/New_York:20250715T160000
DTSTAMP:20260403T191631
CREATED:20250612T190630Z
LAST-MODIFIED:20250612T191825Z
UID:5506-1752591600-1752595200@bridge2ai.org
SUMMARY:B2AI Discussion Forum on Emerging ELSI Issues: “The Pulse of Ethical Machine Learning in Health” by Marzyeh Ghassemi\, Ph.D.
DESCRIPTION:Please join us on Tuesday\, July 15th\, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: \n“The Pulse of Ethical Machine Learning in Health“\,  by Dr. Marzyeh Ghassemi \nRegistration not required!  \nAdditional details in the attached documents and message below. \nBio: \nDr. Marzyeh Ghassemi is an Associate Professor at MIT in Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES). She holds MIT affiliations with the Jameel Clinic\, LIDS\, IDSS\, and CSAIL. For examples of short- and long-form talks Professor Ghassemi has given\, see her Forbes lightning talk\, and her ICML keynote.  \nProfessor Ghassemi holds a Germeshausen Career Development Professorship\, and was named a CIFAR Azrieli Global Scholar and one of MIT Tech Review’s 35 Innovators Under 35. In 2024\, she received an NSF CAREER award\, and Google Research Scholar Award. Prior to her PhD in Computer Science at MIT\, she received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar\, and B.S. degrees in computer science and electrical engineering as a Goldwater Scholar at New Mexico State University.  \nProfessor Ghassemi’s work spans computer science and clinical venues\, including NeurIPS\, KDD\, AAAI\, MLHC\, JAMIA\, JMIR\, JMLR\, AMIA-CRI\, Nature Medicine\, Nature Translational Psychiatry\, and Critical Care. Her work has been featured in popular press such as MIT News\, The Boston Globe\, and The Huffington Post.
URL:https://bridge2ai.org/event/b2ai-discussion-forum-on-emerging-elsi-issues-the-pulse-of-ethical-machine-learning-in-health-by-marzyeh-ghassemi-ph-d/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250814T080000
DTEND;TZID=America/Los_Angeles:20250815T170000
DTSTAMP:20260403T191631
CREATED:20250721T161200Z
LAST-MODIFIED:20250721T162349Z
UID:6068-1755158400-1755277200@bridge2ai.org
SUMMARY:Cell Maps for AI (CM4AI) CodeFest at University of Alabama Birmingham
DESCRIPTION:Are you interested in AI/ML and their applications in biomedicine and precision healthcare? Join the Functional Genomics Grand Challenge team and their group of interdisciplinary experts for the 2025 Cell Maps for AI (CM4AI) CodeFest at UAB. \nThis two-day\, in-person event is a hands-on workshop centered on the development of team-based projects using CM4AI datasets and state-of-the-art AI/ML tools to design and test novel approaches in cancer research\, drug discovery\, systems biology\, and precision medicine. Teams will present their projects virtually\, with cash awards available for the top 3! \nTo register\, please visit the link here. \nRegistration Deadline: August 6th\, 2025 \nFor questions\, please contact: cm4ai@yale.edu \nCodeFest Themes \nParticipants will collaborate in teams to build and present projects that leverage CM4AI data and tools\, with guidance from mentors at UAB\, Yale\, UCSD\, and other CM4AI institutions. \nFocus areas include: \n\nBiomedical graph networks\nGraph & quantum AI/ML methods\nData embedding\nData visualization\nVisible neural networks\nLarge language models
URL:https://bridge2ai.org/event/cell-maps-for-ai-cm4ai-codefest-at-university-of-alabama-birmingham/
LOCATION:University of Alabama at Birmingham
ATTACH;FMTTYPE=image/png:https://bridge2ai.org/wp-content/uploads/2025/07/CM4AI-CodeFest-Flyer.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250819T150000
DTEND;TZID=America/New_York:20250819T160000
DTSTAMP:20260403T191631
CREATED:20250804T152840Z
LAST-MODIFIED:20250804T152840Z
UID:6220-1755615600-1755619200@bridge2ai.org
SUMMARY:B2AI Discussion Forum on Emerging ELSI Issues: “Data Management in the Extremes” by Dr. Jennifer Wagner
DESCRIPTION:Please join us on Tuesday\, August 19th\, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Data Management in the Extremes”\,  by Dr. Jennifer Wagner. \nRegistration not required!  \nAdditional details in the attached documents and message below. \nBio: \nJennifer K. Wagner\, JD\, PhD\, is an Assistant Professor at Penn State University\, affiliated with law\, engineering\, anthropology\, and biomedical sciences. A licensed attorney since 2007\, her interdisciplinary research focuses on the human right to science\, privacy\, and equity in genetic and digital health technologies. She has published over 70 articles\, received NIH funding\, and her work has been cited by the U.S. Supreme Court. She serves on editorial boards and national ethics committees and teaches courses on genetics law\, privacy\, and biomedical AI.
URL:https://bridge2ai.org/event/b2ai-discussion-forum-on-emerging-elsi-issues-data-management-in-the-extremes-by-dr-jennifer-wagner/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250916T150000
DTEND;TZID=America/New_York:20250916T160000
DTSTAMP:20260403T191631
CREATED:20250819T174150Z
LAST-MODIFIED:20250819T174407Z
UID:6278-1758034800-1758038400@bridge2ai.org
SUMMARY:B2AI Discussion Forum on Emerging ELSI Issues: “Rational Health AI and Respect for Persons” by Dr. Ida Sim
DESCRIPTION:Please join us on Tuesday\, September 16th\, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Relational Health AI and Respect for Persons”\,  by Dr. Ida Sim  \nRegistration not required!  \nAdditional details in the attached documents and message below. \nBio: \nIda Sim\, MD\, PhD is Professor of Medicine (UCSF) and Computational Precision Health (UCSF and UC Berkeley) and Co-Director of the UCSF UC Berkeley Joint Program in Computational Precision Health. She obtained her B.Sc. in Biology\, her MD\, and her PhD in Medical Informatics from Stanford. A practicing primary care physician\, Dr. Sim completed her Internal Medicine internship and residency at the Massachusetts General Hospital and a fellowship in General Medicine at the Palo Alto VA.  \n  \nDr. Sim’s research is on cyberinfrastructure and policies for large-scale health data sharing and AI for managing multiple chronic conditions in primary care. She is Co-founder of Open mHealth\, which defines the IEEE 1752 global open standard for patient-generated health data interoperability\, and co-leads JupyterHealth\, a new project bringing the Jupyter ecosystem to healthcare. She is also Co-founder of Vivli\, the world’s largest platform for clinical trial data sharing. In prior work\, Dr. Sim was the founding Project Coordinator of the World Health Organization’s International Clinical Trials Registry Platform and led the establishment of the first global policy on clinical trial registration.  \n  \nDr. Sim is a member of the National Academy of Medicine and the American Society for Clinical Investigation\, a Fellow of the American College of Medical Informatics\, and a recipient of the United States Presidential Early Career Award for Scientists and Engineers (PECASE).
URL:https://bridge2ai.org/event/b2ai-discussion-forum-on-emerging-elsi-issues-rational-health-ai-and-respect-for-persons-by-dr-ida-sim/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251021T150000
DTEND;TZID=America/New_York:20251021T160000
DTSTAMP:20260403T191631
CREATED:20250918T193438Z
LAST-MODIFIED:20251007T154849Z
UID:6817-1761058800-1761062400@bridge2ai.org
SUMMARY:B2AI Discussion Forum on Emerging ELSI Issues: “The Observer Project: Transforming Healthcare from the Outside” by Dr. Kevin Johnson
DESCRIPTION:  \nPlease join us on Tuesday\, October 21st\, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “The Observer Project: Transforming Healthcare from the Outside”\,  by Dr. Kevin Johnson. \nRegistration not required!  \nAdditional details in the attached documents and message below. \nBio: \nKevin B. Johnson\, MD\, MS is the David L. Cohen University Professor of Biomedical Informatics\, Computer Science\, Pediatrics\, and Science Communication at the University of Pennsylvania\, and Vice President of Applied Clinical Informatics in the University of Pennsylvania Health System. He received his MD from Johns Hopkins and his MS in Medical Informatics from Stanford University. Previously\, he served as Chair for the Department of Biomedical Informatics and Chief Informatics Officer for Vanderbilt University Medical Center.  \n  \nA clinical informatics researcher\, Johnson was among the world’s first researchers to propose and demonstrate the value of text-messaging in behavior change. Dr. Johnson developed the first ever computer-based documentation system used at Hopkins\, as well as the first e-prescribing system used at Vanderbilt—both of which became platforms for numerous evaluations by Johnson and his trainees. As director of the Penn Artificial Intelligence for Ambulatory Care Innovation (AI4AI)\, he and his lab focus on various uses of AI to reimagine the clinical encounter.   \n  \nHe has authored over 200 publications and has won numerous national awards.  He was elected to the American College of Medical Informatics in 2004 (FACMI) and (FAMIA)\, The Academic Pediatric Society in 2010\, the National Academy of Medicine in 2010\, the International Association of Health Science Informatics in 2021 (FIAHSI)\, the American Institute of Medical and Biological Engineering in 2022 (FAIMBE).
URL:https://bridge2ai.org/event/b2ai-discussion-forum-on-emerging-elsi-issues-the-observer-project-transforming-healthcare-from-the-outside-by-dr-kevin-johnson/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251211T120000
DTEND;TZID=America/Los_Angeles:20251211T130000
DTSTAMP:20260403T191631
CREATED:20251208T183857Z
LAST-MODIFIED:20251208T185059Z
UID:7181-1765454400-1765458000@bridge2ai.org
SUMMARY:TRM LLM Module Lecture: "Spatial Intelligence: A Key to Embodied AI" with Parisa Kordjamshidi
DESCRIPTION:Join us on Thursday\, December 11\, 2025\, at 12:00 PM PT/3:00 PM ET for the lecture: “Spatial Intelligence: A Key to Embodied AI” with Parisa Kordjamshidi\, PhD. This will be the 5th installment in the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Large Language Model (LLM) Module. \nLearning Objectives: \n\nDefine spatial reasoning and generalization within the context of AI model development.\nIdentify and explain the current limitations of large vision–language models.\nDescribe neurosymbolic AI modeling and articulate how it can enhance model generalization\n\nBiography: \nDr. Parisa Kordjamshidi is an Associate Professor of Computer Science and Engineering at Michigan State University since 2019. After her PhD (KU Leuven\, Belgium)\, she completed her postdoctoral training at the KnowEng Center of NIH BD2K Program at UIUC. At MSU\, her research spans Artificial Intelligence (AI)\, machine learning\, natural language processing (NLP)\, neuro-symbolic AI\, and multi-modal LLMs. She currently directs the Heterogeneous Learning & Reasoning Lab at MSU. She is the recipient of the NSF CAREER Award (2019–24)\, the Amazon Faculty Research Award (2022)\, and the Fulbright Scholar Award (2025). \nDr. Kordjamshidi has a strong publication record across leading AI and NLP venues\, including ACL\, EMNLP\, NAACL\, NeurIPS\, AAAI\, IJCAI\, and ICLR. She serves as the Action Editor of TACL and as a member of the editorial boards of JAIR and other impactful journals. She has served on organizing committees for major conferences such as NAACL\, EMNLP\, ECML-PKDD\, and AAAI\, and as a (senior) area chair or program committee member for top venues including ACL\, IJCAI\, NAACL\, EMNLP\, and AAAI.
URL:https://bridge2ai.org/event/trm-llm-module-lecture-spatial-intelligence-a-key-to-embodied-ai/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20251218T120000
DTEND;TZID=America/Los_Angeles:20251218T130000
DTSTAMP:20260403T191631
CREATED:20251208T185642Z
LAST-MODIFIED:20251208T185908Z
UID:7192-1766059200-1766062800@bridge2ai.org
SUMMARY:TRM LLM Module Lecture: “Navigating Ethical AI in Healthcare: Protecting Consumers and Patients” with Adela Grand
DESCRIPTION:Join us on Thursday\, December 18\, 2025\, at 12:00 PM PT/3:00 PM ET for the lecture: “Navigating Ethical AI in Healthcare: Protecting Consumers and Patients” with Adela Grand\, PhD. This will be the 6th installment in the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Large Language Model (LLM) Module. \nLearning Objectives: \n\nExplain why ethical principles are essential in the design and evaluation of AI-based mental health applications.\nIdentify and critique key components of the FUTURE-AI framework for ensuring trustworthy and human-centered AI systems.\nApply the FUTURE-AI framework to evaluate an AI-based mental mobile app for robustness.\n\nBiography: \nDr. Adela Grando\, PhD\, FAMIA\, FACMI\, is a Professor of Biomedical Informatics at Arizona State University and an Adjunct Assistant Professor at the Mayo Clinic. At ASU\, her research focuses on healthcare information technology\, patient-centered technologies\, and mobile health\, with an emphasis on privacy-preserving data sharing and clinical decision support. She completed postdoctoral training at UCSD’s Division of Biomedical Informatics and at Oxford and Edinburgh Universities through UK Cancer Research\, following her PhD training in Spain. \nDr. Grando has an extensive publication record in leading venues\, including AI in Medicine\, the Int. J. of Med. Inform.\, and Applied Clin. Inform. She previously served as Associate Editor for the Health Informatics Journal and currently serves on the editorial boards of the Journal of Biomedical Informatics and AI in Medicine. She is recognized as a Fellow of both the American Medical Informatics Association (FAMIA) and the American College of Medical Informatics (FACMI).
URL:https://bridge2ai.org/event/trm-llm-module-lecture-navigating-ethical-ai-in-healthcare-protecting-consumers-and-patients-with-adela-grand/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260120T150000
DTEND;TZID=America/New_York:20260120T160000
DTSTAMP:20260403T191631
CREATED:20260107T171614Z
LAST-MODIFIED:20260107T191657Z
UID:7224-1768921200-1768924800@bridge2ai.org
SUMMARY:Bridge2AI Discussion Forum on Emerging ELSI Issues: “Trust Starts Upstream: Recommendations for Creating Ethically Sourced Health Data Repositories for AI/ML"
DESCRIPTION:Please join us on Tuesday\, January 20th\, 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Trust Starts Upstream: Recommendations for creating ethically sourced health data repositories for AI/ML\,” by Dr. Camille Nebeker. \n\n\n\n\nCreating ethically sourced and trustworthy health data repositories is critical for building trustworthy biomedical and behavioral research infrastructure\, especially when such repositories underpin machine learning and AI systems. In Ethical sourcing in the context of health data supply chain management: a value sensitive design approach (Nebeker et al.\, 2025)\, we integrate value sensitive design (VSD) with concepts from supply chain management to operationalize ethical values across the stages of developing health data repositories. The resulting framework identifies key actors\, values (e.g.\, traceability\, security\, equity)\, and tensions that arise during repository creation and highlights practices such as documenting data provenance\, articulating expectations for data stewards\, and implementing comprehensive privacy and bias mitigation strategies. \nDuring this session\, Dr. Nebeker will provide an overview of this framework with a focus on developing a companion checklist that is grounded in VSD and supply chain scaffolding and can be used as actionable guidance in dataset creation. \n\n\n\n\nBio: \nDr. Camille Nebeker is a professor of public health with appointments in the UC San Diego Design Lab and the Herbert Wertheim School of Public Health and Human Longevity Science. In 2018\, Dr. Nebeker co-founded the ReCODE Health center\, which is dedicated to conducting cutting edge research to inform ethical practices in digital/AI health research – including machine learning and the use of large language models. The ReCODE Health center supports education and consultation services to guide ethical practices in technology-supported health research across diverse research sectors including traditional academic research and\, increasingly\, the health technology sector. She’s a principal investigator with the Bridge2AI Bridge Center’s Ethical\, Legal and Social Implications Core.
URL:https://bridge2ai.org/event/bridge2ai-discussion-forum-on-emerging-elsi-issues-trust-starts-upstream-recommendations-for-creating-ethically-sourced-health-data-repositories-for-ai-ml/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260129T150000
DTEND;TZID=America/New_York:20260129T160000
DTSTAMP:20260403T191631
CREATED:20260120T200859Z
LAST-MODIFIED:20260120T202421Z
UID:7284-1769698800-1769702400@bridge2ai.org
SUMMARY:TRM Novel AI Technology Module Lecture: "Beyond LLMs: Neuro-Symbolic Approaches for Language Understanding in the Biomedical Domain" by Dr. Mihai Surdeanu
DESCRIPTION:“Join us on Thursday\, January 29\, 2026\, at 12:00 PM PT/3:00 PM ET for the lecture: “Beyond LLMs: Neuro-Symbolic Approaches for Language Understanding in the Biomedical Domain” by Dr. Mihai Surdeanu. This lecture is part of the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module. \nLecture Learning Objectives: \n\nUnderstand the advantages and disadvantages of neural (in particular LLM) architectures vs. neuro-symbolic approaches in the biomedical space.\nLearn how to build symbolic and neuro-symbolic natural language processing systems that are faithful\, pliable\, and fast.\n\nBiography: \nDr. Mihai Surdeanu is a Professor of Computer Science in the College of Science at the University of Arizona\, with joint appointments in Linguistics and Cognitive Science. His research focuses on natural language processing\, including question answering\, information extraction\, and building systems that derive meaning from unstructured text\, with a strong emphasis on interpretable models that can explain their decisions. \nDr. Surdeanu has received the ACL Outstanding Area Chair Award (2023) and the Distinguished Scholar Award from the University of Arizona’s Department of Computer Science (2023). He is an active contributor to the NLP community\, serving as an Action Editor for Transactions of the Association for Computational Linguistics (TACL) since 2019 and as Senior Area Chair for ACL (2023\, 2025) and EMNLP (2022). He has held Area Chair roles for EMNLP\, NAACL\, and COLING–LREC across multiple years. Dr. Surdeanu has also served on program committees for ACL and EMNLP for a long time\, in addition to contributing to COLM\, COLING\, as well as Graph-Based NLP and Pan-DL workshops.” \nIntroduction Slides
URL:https://bridge2ai.org/event/trm-novel-ai-technology-module-lecture-beyond-llms-neuro-symbolic-approaches-for-language-understanding-in-the-biomedical-domain-by-dr-mihai-surdeanu/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260217T150000
DTEND;TZID=America/New_York:20260217T160000
DTSTAMP:20260403T191631
CREATED:20260115T160552Z
LAST-MODIFIED:20260121T202705Z
UID:7259-1771340400-1771344000@bridge2ai.org
SUMMARY:Bridge2AI Discussion Forum on Emerging ELSI Issues: “Pragmatic and Nimble AI Governance in Healthcare"
DESCRIPTION:Please join us on Tuesday\, February 17th 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Pragmatic and Nimble AI Governance in Healthcare“\,  by Dr. Susannah Rose. \n\n\n\n\nDr. Susannah Rose will discuss the ethical issues related deploying system-wide artificial intelligence in healthcare delivery organizations. This presentation will focus on the practical governance policies\, process and challenges. Attendees will have the opportunity to ask questions as part of an engaging and dynamic presentation. \n\nBio: \n\n\n\n\nDr. Rose is an ethicist and mixed-methods researcher specializing in patient experience and the ethics of artificial intelligence (AI) in healthcare. She is an Associate Professor at Vanderbilt University Medical Center and serves as Vice-Chair of VUMC’s AI Technology Committee and Executive Director of the ADVANCE Center. Dr. Rose previously founded the AI + Ethics Program at Cleveland Clinic\, teaches public health ethics at Harvard T.H. Chan\, and her research is funded by organizations including ARPA-H\, NIH\, and The Greenwall Foundation.
URL:https://bridge2ai.org/event/bridge2ai-discussion-forum-on-emerging-elsi-issues-pragmatic-and-nimble-ai-governance-in-healthcare/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260219T150000
DTEND;TZID=America/New_York:20260219T160000
DTSTAMP:20260403T191631
CREATED:20260120T202102Z
LAST-MODIFIED:20260120T202333Z
UID:7291-1771513200-1771516800@bridge2ai.org
SUMMARY:TRM Novel AI Technology Module Lecture: "Encrypted Machine Learning" by Dr. Vishnu Boddeti
DESCRIPTION:Join us on Thursday\, February 19\, 2026\, at 12:00 PM PT/3:00 PM ET for the lecture: “Encrypted Machine Learning” by Dr. Vishnu Boddeti. This lecture is part of the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module. \nLecture Learning Objectives: \n\nUnderstand the advantages and disadvantages of neural (in particular LLM) architectures vs. neuro-symbolic approaches in the biomedical space.\nLearn how to build symbolic and neuro-symbolic natural language processing systems that are faithful\, pliable\, and fast.\n\nBiography: \nDr. Vishnu Boddeti is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University and the Director of the Human Analysis Lab. His research focuses on developing AI systems with provable guarantees of fairness\, privacy\, and accuracy\, with applications spanning high-stakes scientific and societal domains. His work includes auditing and mitigating bias in foundation models through fairness–utility trade-offs and adversarial red-teaming\, designing cryptographically secure AI systems using homomorphic encryption and FHE-native architectures\, and advancing physics-informed AI for scientific discovery by integrating physical laws to improve generalization and reduce data requirements. \nHe has received multiple distinguished research honors\, including the 2024 IEEE-CCF Cloud Computing Best Paper Award\, Best Paper Awards at IROS 2023 and IEEE TBIOM (2022–2023)\, and recognition as an Editor Highlight in Nature Communications. He is also a recipient of a Facebook Research Grant on Multi-objective Co-evolutionary Learning (2021). Dr. Boddeti is an active contributor to the research community\, serving as Senior Area Editor for IEEE Transactions on Information Forensics and Security (2025) and Area Chair for NeurIPS (2025) and AutoML (2023). His research demonstrates that well-designed cryptographic\, statistical\, and physical constraints can enable AI capabilities\, providing both theoretical foundations and practical systems for trustworthy AI deployment in scientific and biomedical contexts.” \nIntroduction
URL:https://bridge2ai.org/event/trm-novel-ai-technology-module-lecture-encrypted-machine-learning-by-dr-vishnu-boddeti/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260226T150000
DTEND;TZID=America/New_York:20260226T160000
DTSTAMP:20260403T191631
CREATED:20260223T160917Z
LAST-MODIFIED:20260223T161007Z
UID:7465-1772118000-1772121600@bridge2ai.org
SUMMARY:TRM Novel AI Technology Module Lecture: "From Volume to Value: Rethinking Data for AI in Healthcare” by Dr. Teresa Wu
DESCRIPTION:  \nJoin us on Thursday\, February 27\, 2026\, at 12:00 PM PT/3:00 PM ET for the lecture: “From Volume to Value: Rethinking Data for AI in Healthcare” by Dr. Teresa Wu. This lecture is part of the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module. \nDr. Teresa Wu is the Fulton Professor of Industrial Engineering\, the Vice Dean for Academic and Student Affairs at Ira Fulton Schools of Engineering (FSE)\, Arizona State University. She is also the founding Director of the ASU–Mayo Center for Innovative Imaging (AMCII)\, a multi-institutional center uniting ASU engineers and data scientists with clinicians at Mayo Clinic\, Arizona. Her research focuses on machine learning and deep learning for heterogeneous\, multi-modal medical data\, with applications in disease diagnosis and prognosis. \nDr. Wu is a President’s Professor at ASU (2024) and an IISE Fellow (2020)\, and has received honors including the IBM Faculty Research Award in Health Systems (2017)\, the Harold G. Wolff Lecture Award at Mayo Clinic (2015)\, and the Fulton Schools Exemplar Award at ASU (2016). She was also an ASU PLuS Global Health Alliance Fellow (2016–2020) and an NSF CAREER Award recipient (2003). She serves as the Emeritus Editor-in-Chief of IISE Transactions on Healthcare Systems Engineering; Associate Editor forJournal of Alzheimer’s Disease\,Neuroscience and Biomedical Engineering\, and IIE Transactions on Healthcare Engineering. She is an active contributor to the research community through editorial leadership\, program committees for NIPS\, SDM\, and KDD\, long-standing NSF grant review service\, and a member of the Institute of Industrial and Systems Engineers. \nLecture Learning Objectives: \n\nReview the evolution of AI methodologies\, with a focus on modeling approaches in quantitative medical imaging.\nReview the impact of data quality versus data quantity on the performance and reliability of AI models in medical applications.\nLearn how post-hoc calibration improves prediction with confidence.\n\nIntroduction
URL:https://bridge2ai.org/event/trm-novel-ai-technology-module-lecture-from-volume-to-value-rethinking-data-for-ai-in-healthcare-by-dr-teresa-wu/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260317T150000
DTEND;TZID=America/New_York:20260317T160000
DTSTAMP:20260403T191631
CREATED:20260121T202613Z
LAST-MODIFIED:20260121T202831Z
UID:7375-1773759600-1773763200@bridge2ai.org
SUMMARY:Bridge2AI Discussion Forum on Emerging ELSI Issues: “Conjoint analysis of perspectives on ethical tradeoffs in data generation project"
DESCRIPTION:Please join us on Tuesday\, March 17th 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Conjoint analysis of perspectives on ethical tradeoffs in data generation project”\,  by Dr. Dr. Nicholas G. Evans. \nRegistration not required!\, view past recordings here. \n Additional details in the attached documents and message below. \nBio: \nDr. Nicholas G. Evans\, Ph.D. is Associate Professor of Political Science at the University of Massachusetts Lowell\, where he co-directs the Modelling Individual and Networked Decisions (MIND) Lab. His work focuses on the intersection of ethics\, infectious disease\, emerging technologies\, and national security. His current major projects focus on ethics of artificial intelligence\, funded by the National Institutes of Health\, US Army Research Laboratory DEVCOM\, and Greenwall Foundation. \nDr. Evans is best known for his work on “dual-use research of concern\,” beneficial scientific research that has a risk of misuse in the development of weapons of mass destruction. In 2012 he completed one of the first Ph.D. dissertations on the ethics of dual-use research of concern\, where he wrote on the scope and strength of scientific freedom in the face of national security concerns. He has since published more than a dozen articles\, books\, and book chapters on dual-use research. In Spring 2025 he published Gain of Function with The MIT Press Essential Knowledge Series\, providing a thoroughgoing guide to the topic\, its controversies\, and future. \nDr. Evans is also a recognized expert in public health ethics\, writing on the ethics of social distancing\, research ethics during health emergencies\, and the use of force in pandemic response. His 2016 collection\, Ebola’s Message: Public Health and Medicine in the 21st Century received favorable reviews in Nature from Dr. Peter Piot\, who first identified the virus in 1976. His new book on the ethics of pandemic preparedness and response\, War on All Fronts: A Theory of Health Security Justice\, was published in May 2023. Both are available open access at The MIT Press Website. \nPrior to his appointment at the University of Massachusetts Lowell\, Dr. Evans completed postdoctoral research at the University of Pennsylvania. In 2015\, he held an Emerging Leaders in Biosecurity Initiative Fellowship at the UPMC Center for Health Security\, Baltimore; has held visiting appointments at the Universities of Exeter\, Bradford\, and Cambridge; and is a three-time Fondation Brocher resident scholar in bioethics in Hermance\, Switzerland. He is also a former policy officer with the Australian Department of Health where he worked on therapeutics regulation\, and assisted reproduction policy.
URL:https://bridge2ai.org/event/bridge2ai-discussion-forum-on-emerging-elsi-issues-conjoint-analysis-of-perspectives-on-ethical-tradeoffs-in-data-generation-project/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260319T150000
DTEND;TZID=America/New_York:20260319T160000
DTSTAMP:20260403T191631
CREATED:20260223T180613Z
LAST-MODIFIED:20260223T180613Z
UID:7471-1773932400-1773936000@bridge2ai.org
SUMMARY:TRM Novel AI Technology Module Lecture: “Multimodal Deep Learning Models for Thyroid Cancer Risk Stratification” by Dr. William Speier
DESCRIPTION:  \nJoin us on Thursday\, March 19\, 2026\, at 12:00 PM PT/3:00 PM ET for the lecture: “Multimodal Deep Learning Models for Thyroid Cancer Risk Stratification” by Dr. William Speier. This lecture is part of the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module. \nDr. William Speier is an Associate Professor in the Departments of Radiology\, Bioengineering\, and Bioinformatics at UCLA and a member of the Medical Informatics home area. He is the Associate Director of the UCLA Biomedical Artificial Intelligence Research (BAIR) Laboratory\, where his research focuses on developing machine learning and AI methods to improve clinical support applications\, including brain-computer interface assistive devices and automated pipelines for limbal stem cell deficiency diagnosis. His work integrates large language models\, statistical modeling\, system optimization\, and evaluation metrics\, with a strong emphasis on translating computational methods into real-world clinical implementation. \nDr. Speier serves as Co-chair of the Medical Informatics Curriculum Committee and on the Steering Committee for the Brain Info Conference. He is an Academic Editor for Frontiers in Human Neuroscience (since 2023) and PLOS ONE (since 2018)\, and has contributed as a mentor in the UCLA CARE Science\, Engineering\, and Math (SEM) Summer Program (2019) and the Bruins-In-Genomics (BIG) Mentorship Program (2019-20). His research highlights a commitment to translational science\, combining theoretical development with online implementation and patient testing. \n\nLecture Learning Objectives: \n\nExplain the importance of type 1 error in thyroid cancer diagnosis.\nCompare different approaches to handle multi-modal data.\nEvaluate the effectiveness and clinical utility of biomedical AI applications.\n\nIntroduction
URL:https://bridge2ai.org/event/trm-novel-ai-technology-module-lecture-multimodal-deep-learning-models-for-thyroid-cancer-risk-stratification-by-dr-william-speier/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260326T150000
DTEND;TZID=America/New_York:20260326T160000
DTSTAMP:20260403T191631
CREATED:20260323T172703Z
LAST-MODIFIED:20260323T172918Z
UID:7571-1774537200-1774540800@bridge2ai.org
SUMMARY:TRM Novel AI Technology Module Lecture: “Identifying Heterogeneous Treatment Effects using Machine Learning for Future Precision Medicine and Public Health” by Dr. Kosuke Inoue
DESCRIPTION:Join us on Thursday\, March 26\, 2026\, at 12:00 PM PT/3:00 PM ET for the lecture: “Identifying Heterogeneous Treatment Effects using Machine Learning for Future Precision Medicine and Public Health” by Dr. Kosuke Inoue\, MD\, PhD. This lecture is part of the Bridge2AI Training\, Recruitment\, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module. \nDr. Kosuke Inoue is a physician-epidemiologist at Kyoto University whose research focuses on clinical and cardiovascular epidemiology\, with an emphasis on statistical modeling and causal inference. Formally trained as an endocrinologist\, he has advanced training in causal inference methodologies. His research integrates causal inference frameworks with machine learning algorithms to analyze high-dimensional cohort and clinical trial data. He also applies machine learning–based heterogeneous treatment effect methods to both randomized controlled trial (RCT) and observational data to better understand variation in treatment responses and disease risk across populations. \nDr. Inoue has established a strong research record\, with 160 peer-reviewed publications\, including 95 first- or last-author papers\, over the past decade. His work has been recognized with many prestigious honors\, including the Young Scientist Award from the Ministry of Education\, Culture\, Sports\, Science and Technology of Japan (2025)\, MIT Technology Review Innovators Under 35 Japan (2023)\, the Medical Research Encouragement Prize from the Japan Medical Association (2023)\, the Young Investigator Award from the Japan Endocrine Society (2023)\, and the Encouragement Award from the Japan Epidemiological Association (2024). His work advances the integration of epidemiology\, causal inference\, and data science to support more evidence-based clinical and public health decision-making. \nLecture Learning Objectives: \n\nAssessing treatment effect heterogeneity is essential for understanding mechanisms behind average effects and identifying sub groups with higher or lower benefit.\nRecently developed machine learning methods\, including casual forests and meta-learners\, can be used for evaluating such heterogeneity.\nThe High-Benefit Approach\, an approach targeting individuals with high benefit\, has the potential to serve as a future personalized medicine strategy by efficiently allocating healthcare resources and reducing health disparities.\n\nIntroduction
URL:https://bridge2ai.org/event/trm-novel-ai-technology-module-lecture-identifying-heterogeneous-treatment-effects-using-machine-learning-for-future-precision-medicine-and-public-health-by-dr-kosuke-inoue/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260421T150000
DTEND;TZID=America/New_York:20260421T160000
DTSTAMP:20260403T191631
CREATED:20260319T152839Z
LAST-MODIFIED:20260319T153033Z
UID:7551-1776783600-1776787200@bridge2ai.org
SUMMARY:Bridge2AI Discussion Forum on Emerging ELSI Issues: “Making Health AI Work: Turning Principles into Real-World Impact"
DESCRIPTION:  \nThis month\, Dr. Cora Han discussed how health systems can move from high-level AI principles to practical\, responsible implementation. Drawing on UC Health’s experience\, she covered governance\, real-world use cases\, and challenges around regulation\, data\, and workflow integration — as well as how AI can improve care delivery\, reduce clinician burden\, and scale innovation responsibly across healthcare \n— \nRegistration not required!\, view past recordings here. \nAdditional details in the attached documents and message below. \nBio: \nCora Han\, JD is Chief Health Data Officer for University of California Health. As a strategic leader at the intersection of healthcare\, technology\, and governance\,  Han directs the Center for Data-driven Insights and Innovation (CDI2)\, a systemwide data platform that leverages health data to improve care\, drive research\, and foster innovation. She also directs UC-wide data governance initiatives\, including the responsible development and application of AI in healthcare. Previously\, Han served as a senior attorney in the Federal Trade Commission’s Division of Privacy and Identity Protection\, where she played a leading role on health privacy matters in both enforcement and policy. She is a frequent speaker on artificial intelligence\, data governance\, and data privacy.
URL:https://bridge2ai.org/event/bridge2ai-discussion-forum-on-emerging-elsi-issues-making-health-ai-work-turning-principles-into-real-world-impact/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260428T083000
DTEND;TZID=America/Los_Angeles:20260429T170000
DTSTAMP:20260403T191631
CREATED:20260318T143951Z
LAST-MODIFIED:20260318T144840Z
UID:7547-1777365000-1777482000@bridge2ai.org
SUMMARY:2026 Spring All-Hands Meeting
DESCRIPTION:Dear Bridge2AI Community:\n\n\nWe are excited to invite you to register for the 2026 Bridge2AI All-Hands Meeting\, taking place April 28-29 at the NIH Neuroscience Center with Conference Chairs Dr. Mónica Muñoz Torres and Dr. Yulia Levites Strekalova.\n\n\nThe NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) program was established to solve the AI-readiness gap in biomedical data\, setting the stage for the ethical use of AI in behavioral and medical research. As the program enters its fourth year\, the focus has shifted from foundational architecture to tangible results. The 2026 All-Hands Meeting highlights the consortium’s landmark data releases and tools while charting its evolution from a structured consortium into a broader\, collaborative community. This transition is captured in this year’s theme: From Data to Wisdom. \n\n\nTo register now\, please visit the meeting website. Registration will close on April 15\, 2026. 
URL:https://bridge2ai.org/event/2026-spring-all-hands-meeting/
LOCATION:NIH Neuroscience Center 6001 Executive Blvd Rockville MD United States
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260504
DTEND;VALUE=DATE:20260507
DTSTAMP:20260403T191631
CREATED:20251022T142747Z
LAST-MODIFIED:20251022T143007Z
UID:6968-1777852800-1778111999@bridge2ai.org
SUMMARY:2026 Voice AI Symposium & Hackathon
DESCRIPTION:Registration and Call for Science are now open for the 2026 Bridge2AI Voice Symposium + Hackathon! Join us May 4–6\, 2026\, in beautiful St. Petersburg\, Florida\, for one of the only global events dedicated entirely to voice biomarkers. \nThe Voice AI Symposium has become an internationally-recognized event and one of the only conferences focused solely on the research\, development\, and implementation of voice biomarkers to improve healthcare. Unlike some large-scale tech conferences\, the Voice AI Symposium is intentionally intimate and designed to give every attendee meaningful opportunities to meet pioneers\, tastemakers\, and thought leaders shaping the future of healthcare through voice AI technologies. Building on the success of past years\, the 2026 Voice AI Symposium will bring together the forefront innovators\, researchers\, clinicians\, entrepreneurs\, and industry leaders of the voice biomarker space for a two-day immersive experience at the forefront of voice and AI in healthcare. \n  \nHighlights will include: \n\nHands-on Training & Workshops using the Bridge2AI-Voice dataset and tools.\nPodium presentations selected through an open Call for Science\nInteractive Panels & Keynotes featuring international experts and visionaries in healthcare and AI.\nTech Fair & Demos where attendees can experience cutting-edge applications of voice AI.\nPitch Competition spotlighting groundbreaking startups.\nNetworking Events designed to foster real connections across disciplines.\nand more!\n\nSubmit your most innovative research and technology under this year’s theme:\n“Translating AI Research into Reality: Implementing Voice Biomarkers for Transformative Healthcare.” \nKey Dates:\nAbstract Submission Deadline: December 5\, 2025\nNotification of Selection: January 15\, 2026\nSymposium + Hackathon: May 4–6\, 2026 \nDon’t miss your chance to be part of this global movement at the intersection of voice\, data\, and health innovation — and to connect with the community shaping the next era of healthcare AI. \nRegister early to secure your spot — there is limited capacity!\nVoice AI Symposium: https://www.eventsquid.com/event.cfm?id=29517\nCall for Science: https://www.eventsquid.com/event.cfm?id=30025
URL:https://bridge2ai.org/event/2026-voice-ai-symposium-hackathon/
LOCATION:The Vinoy Resort & Golf Club\, 501 5th Ave NE\, St. Petersburg\, FL\, 33701\, United States
ORGANIZER;CN="Bridge2AI Voice":MAILTO:bridge2aivoice@usf.edu
END:VEVENT
END:VCALENDAR