TRM LLM Module Lecture: "Spatial Intelligence: A Key to Embodied AI" with Parisa Kordjamshidi
2025-12-11 12:00 - 13:00 (America/Los_Angeles)
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.
Learning Objectives:

Define spatial reasoning and generalization within the context of AI model development.
Identify and explain the current limitations of large vision–language models.
Describe neurosymbolic AI modeling and articulate how it can enhance model generalization

Biography:
Dr. 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).
Dr. 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.

TRM LLM Module Lecture: “Navigating Ethical AI in Healthcare: Protecting Consumers and Patients” with Adela Grand
2025-12-18 12:00 - 13:00 (America/Los_Angeles)
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.
Learning Objectives:

Explain why ethical principles are essential in the design and evaluation of AI-based mental health applications.
Identify and critique key components of the FUTURE-AI framework for ensuring trustworthy and human-centered AI systems.
Apply the FUTURE-AI framework to evaluate an AI-based mental mobile app for robustness.

Biography:
Dr. 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.
Dr. 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).

Bridge2AI Discussion Forum on Emerging ELSI Issues: “Trust Starts Upstream: Recommendations for Creating Ethically Sourced Health Data Repositories for AI/ML"
2026-01-20 15:00 - 16:00 (America/New_York)
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.

Creating 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.
During 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.

Bio:
Dr. 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.

TRM Novel AI Technology Module Lecture: "Beyond LLMs: Neuro-Symbolic Approaches for Language Understanding in the Biomedical Domain" by Dr. Mihai Surdeanu
2026-01-29 15:00 - 16:00 (America/New_York)
“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.
Lecture Learning Objectives:

Understand the advantages and disadvantages of neural (in particular LLM) architectures vs. neuro-symbolic approaches in the biomedical space.
Learn how to build symbolic and neuro-symbolic natural language processing systems that are faithful, pliable, and fast.

Biography:
Dr. 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.
Dr. 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.”
Introduction Slides

Bridge2AI Discussion Forum on Emerging ELSI Issues: “Pragmatic and Nimble AI Governance in Healthcare"
2026-02-17 15:00 - 16:00 (America/New_York)
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.

Dr. 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.

Bio:

Dr. 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.

TRM Novel AI Technology Module Lecture: "Encrypted Machine Learning" by Dr. Vishnu Boddeti
2026-02-19 15:00 - 16:00 (America/New_York)
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.
Lecture Learning Objectives:

Understand the advantages and disadvantages of neural (in particular LLM) architectures vs. neuro-symbolic approaches in the biomedical space.
Learn how to build symbolic and neuro-symbolic natural language processing systems that are faithful, pliable, and fast.

Biography:
Dr. 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.
He 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.”
Introduction

Bridge2AI Discussion Forum on Emerging ELSI Issues: “Conjoint analysis of perspectives on ethical tradeoffs in data generation project"
2026-03-17 15:00 - 16:00 (America/New_York)
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.
Registration not required!, view past recordings here.
Additional details in the attached documents and message below.
Bio:
Dr. 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.
Dr. 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.
Dr. 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.
Prior 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.

2026 Voice AI Symposium & Hackathon
2026-05-04 - 2026-05-06 | The Vinoy Resort & Golf Club, 501 5th Ave NE, St. Petersburg, FL, 33701, United States
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.
The 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.

Highlights will include:

Hands-on Training & Workshops using the Bridge2AI-Voice dataset and tools.
Podium presentations selected through an open Call for Science
Interactive Panels & Keynotes featuring international experts and visionaries in healthcare and AI.
Tech Fair & Demos where attendees can experience cutting-edge applications of voice AI.
Pitch Competition spotlighting groundbreaking startups.
Networking Events designed to foster real connections across disciplines.
and more!

Submit your most innovative research and technology under this year’s theme:
“Translating AI Research into Reality: Implementing Voice Biomarkers for Transformative Healthcare.”
Key Dates:
Abstract Submission Deadline: December 5, 2025
Notification of Selection: January 15, 2026
Symposium + Hackathon: May 4–6, 2026
Don’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.
Register early to secure your spot — there is limited capacity!
Voice AI Symposium: https://www.eventsquid.com/event.cfm?id=29517
Call for Science: https://www.eventsquid.com/event.cfm?id=30025
