Foundational Discussions in Artificial Intelligence-Readiness and Workforce Development

In 2021, the NIH Office of Data Science Strategy (ODSS) supported its first cohort of scientific projects in Artificial Intelligence, divided into two different but overlapping research themes. The two different research themes include: Workforce Development at the Interface of Information Sciences, Artificial Intelligence (AI) and Machine Learning (ML), and Biomedical Sciences (NOT-OD-21-079) and Collaborations to Improve the AI/ML-Readiness of NIH- Supported Data (NOT-OD-21-094).

ODSS sponsored a kick-off primary investigator (PI) meeting for both cohorts, held virtually November 1, 2, and 15, 2021. The kick-off meeting provided an opportunity to bring together these experts to network, share ideas, and potentially inspire collaborations or further sharing. It was also an opportunity for NIH to better understand details of the planned activities and challenges in the training and research environment to build AI-ready data sets and associated tools; learn about methods to recruit the expertise needed; and better understand the available resources across the AI Readiness and AI Workforce Development teams.

Read a report of the kickoff meeting.

In 2022, ODSS sponsored a closeout meeting of this cohort of projects, held virtually October 24, 31, and November 1, 2022. The purpose of these meetings was to provide an opportunity for awardees to showcase their work and share their experiences with other colleagues working in AI and AI-workforce development. View a summary of the meeting. The agenda and links to presentations follow.

Agendas and Presentations

ODSS AI Supplements Closeout Meeting
NOT-OD-21-079 (AI Workforce)
Day 1: October 24, 2022
Time	Presentation
	Day 1 Video
11:00 a.m. – 11:10 a.m.	Welcome and Introductions Laura Biven Michael Spittel
11:10 a.m. – 11:40 a.m.	Updates on AI from NIH Laura Biven
11:40 a.m. – 3:05 p.m.	Lightning Talks and Breakouts Parallel Interactive Lightening Talks - Session A Room 1 FAIR and Practical Data Science Training at the Chemistry–Biology Interface. PI: Catherine Grimes Room 2 Adding a FAIR Data Practices Curriculum to UF's Practicum AI AI/ML Training Workshops. PI: David Julian Parallel Interactive Lightening Talks - Session B Room 1 Stackable Trainings in the FAIRification and AI/ML-Readiness of Data with Applications to Environmental Health and Justice PI: Phil Brown Room 2 AI Training Module for Vision Science PI: Kate Keller Room 3 Predoctoral Training in Biological Data Management for Advanced Computational Analysis and the Ethical Usage of Biological Data PI: Thomas Tullius Parallel Interactive Lightening Talks - Session C Room 1 Maximizing Student Development in Data- and Information Science-Related Disciplines for Biomedical Ph.D. Trainees at Texas A&M University and Beyond PI: Christi Retzer Room 2 Workforce Training for Making Data FAIR and Compatible with Machine Learning and Artificial Intelligence Applications PI: Marcus Craig Room 3 Development of Data Science Course and Summer Bootcamp for Alzheimer’s Disease and Related Dementia Researchers PI: Chunyu Wang Parallel Interactive Lightening Talks - Session D Room 1 Cancer Research Workforce Development in FAIR Artificial Intelligence and Machine Learning Presenter: Issam El Naqa PI: William Cress Room 2 Making Data FAIR and AI/ML Applications for Cancer Prevention and Control (AI/ML-CAPAC) Research Among Hispanics PI: Ana Patricia Ortiz Room 3 Demystifying Machine Learning and Best Data Practices Workshop Series for Underrepresented STEM Undergraduate and M.S. Researchers Bound for Ph.D. Training Programs Presenter: Pleuni Pennings PI: Raymond Esquerra Parallel Interactive Lightening Talks - Session E Room 1 Making Environmental Health Data FAIR and AI/ML-Ready Presenter: Jeanette Stingone: PI: Gary Miller Parallel Interactive Lightening Talks - Session F Room 1 Next Generation Sequencing and Biological Imaging in the Era of Machine Learning Presenter: Jake Search PI: Karen Guillemin
3:05 p.m. – 3:20 p.m.	Open Conversation of Cohort Support and Future Vision Laura Biven
3:20 p.m. – 3:30 p.m.	Thank you and Closeout Laura Biven

ODSS AI Supplements Closeout Meeting
NOT-OD-21-094 (AI Readiness)
Day 2: October 31, 2022
Time	Presentation
	Day 2 Video
11:00 a.m. – 11:10 a.m.	Welcome and Introductions Laura Biven Michael Spittel
11:10 a.m. – 11:40 a.m.	Updates on AI from NIH Laura Biven
11:40 a.m. – 3:05 p.m.	Lightning Talks and Breakouts Parallel Interactive Lightening Talks - Session A Room 1 Building a Substance Use Data Commons for Public Health Informatics PI: Majid Afshar Room 2 A Computational Pipeline to Evaluate AI/ML Readiness in Digital Datasets in the Framingham Heart Study Presenter: Vijaya Kolachalama PI: Lindsay Farrer Room 3 An AI-Ready Vascular Model Repository for Modeling and Simulation in Cardiovascular Disease Presenter: Luca Pegolotti PI: Alison Marsden Room 4 Enabling the AI/ML-Readiness of Massive Single-Cell Data for Discovering RNA Regulatory Biology Presenter: Julia Salzman Room 5 Addressing Class Imbalance and Missingness in the PROTECT Database Presenter: David Kaeli PI: Akram Alshawabkeh Room 6 De-identified Delirium Data: Finding Delirium to Study Delirium Presenter: Richard Kennedy Parallel Interactive Lightening Talks - Session B Room 1 Using Machine Learning and Artificial Intelligence Models to Predict Muscle Stem Cell Biological Age and Regenerative Potential PI: Fabrisia Ambrosio Room 2 Precision Care After Cardiac Arrest PI: Karen Hirsch Room 3 Democratizing Machine Learning for Researchers Working in Alzheimer’s Space Presenter: Benjamin Goudey PI: Colin Masters Room 4 Improving AI/ML-Readiness of Data Generated Under the R01:Protein Signatures of APOE2 and Cognitive Aging Presenter: Paola Sebastiani or Ofer Mendelevitch PI: Daniel Edward Promislow Room 5 Development and Use of an AI/ML-Ready Dog Aging Project Dataset Presenter: Matt Dunbar PI: Daniel Edward Promislow Parallel Interactive Lightening Talks - Session C Room 1 Towards Automatic Transcription of Post-Stroke Disordered Speech PI: Steven Bedrick Room 2 Cross-Modality Imaging Data Annotations for Deep Learning-Based Analysis Solutions in the Auditory Field Presenter: Chris Buswinka PI: Artur Indzhykulian Room 3 PERCEPT: A Database of Clinical Child Speech for Automatic Speech Recognition and Classification PI: Tara McAllister Room 4 Model Organism Neural Circuit Knowledge Graph Presenter: Paul Sternberg or Sharan Prakash PI: Paul Sternberg Room 5 Agent-Based Participation of Machine Learning Models in a Crowdsourcing System Presenter: Pietro Michelucci PI: Chris B. Schaffer Parallel Interactive Lightening Talks - Session D Room 1 Using Artificial Intelligence for Alzheimer’s Disease Drug Repurposing PI: Feixiong Cheng Room 2 Developing AI/ML-Ready Aging Trajectory Files PI: Olga Jarrin Montaner Room 3 Harnessing Multimodal Data To Enhance Machine Learning of Children’s Vocalizations PI: Daniel Messinger Room 4 Detecting Speech Articulation Patterns Following Laryngeal Cancer Treatment Using Artificial Intelligence and Machine Learning Presenter: Jun Wang or Nordine Sebkhi PI: Jun Wang Room 5 Rescuing Missed Longitudinal MRI Scans in the UNC Early Brain Development Study Presenter: Martin Styner PI: John Gilmore Parallel Interactive Lightening Talks - Session E Room 1 A Novel Dataset for Speech Analysis in Serious Mental Illness (Parent Study: Social Cognitive Biases and Suicide in Psychotic Disorders) PI: Colin Depp Room 2 Improving AI/ML-Readiness of Data Generated from HABLE or Other NIH-Funded Research Presenter: Fan Zhang PI: Sid O’Bryant Room 3 Machine Learning Development Environment for Single-Cell Sequencing Data Analyses PI: Dong Xu Room 4 Improving AI/ML-Readiness of FaceBase Research Datasets Presenter: Rob Schuler PI: Carl Kesselman Room 5 Making Data From the Center for GWAS in Outbred Rats FAIR and AI/ML Ready Presenter: Abraham Palmer Parallel Interactive Lightening Talks - Session F Room 1 AI/ML-Readiness for Neuroimaging of Language PI: Rutvik Desai Room 2 Machine Learning-enabled Comparative Transcriptomic Profiling to Validate Nanoscript-Induced Inner Ear Hair Cells Presenter: Brandon Conklin PI: Kibum Lee Room 3 Multi-omic Human Brain Immune Cell (HBIC) Resources for AI/ML Applications Presenter: Donghoon Lee PI: Panagiotis Roussos Room 4 Fair Risk Predictions for Underrepresented Populations Using Electronic Health Records PI: Judy Zhong Room 5 Extending the QCArchive Small Molecule Quantum Chemistry Archive To Support Machine Learning Applications in Biomolecular Modeling Presenter: John Chodera PI: Michael Shirts Room 6 Assessing HER Data Readiness for ML/AI Algorithms in Sepsis and Antimicrobial Resistance Presenter: Cristina Vazquez Guillamet PI: Cristina Vazquez Guillamet
3:05 p.m. – 3:20 p.m.	Open Conversation of Cohort Support and Future Vision Laura Biven
3:20 p.m. – 3:30 p.m.	Thank you and Closeout Laura Biven

ODSS AI Supplements Joint Closeout Meeting
Day 3: November 1, 2022
Time	Presentation
	Day 3 Video
11:00 a.m. – 11:10 a.m.	Welcome and Introductions Laura Biven Michael Spittel
11:10 a.m. – 12:00 p.m.	Recognizing and Integrating Social Good into the AI Development Lifecycle Bradley Malin, Accenture Professor of Biomedical Informatics, Biostatistics, and Computer Science; Vice Chair for Research Affairs Department of Biomedical Informatics, Vanderbilt University
12:05 p.m. – 1:00 p.m.	Data Science at NIH Susan Gregurick, Associate Director for Data Science and Director of the Office of Data Science Strategy, NIH
1:00 p.m. – 3:05 p.m.	Breakouts
3:05 p.m. – 3:20 p.m.	Open Conversation of Cohort Support and Future Vision Laura Biven
3:20 p.m. – 3:30 p.m.	Thank you and Closeout Laura Biven