MEET OUR SPEAKERS
Combiz Abdolrahimi
Senior Advisor
U.S. Federal Identity Forum (FedID)
Combiz is an attorney, technologist, and former regulator/policymaker with over 14 years of public and private sector experience helping U.S. Federal, State, and international governments, and health agencies.
Panel Discussion: Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals.
Cupid Chan
Chairperson BI & AI, Board of Directors,
Technical Steering Committee
Linux Foundation ODPi
Cupid is a well-established technology professional and an adjunct professor at the University of Maryland.
Morning Plenary Session: Catch Me if You Can – How to Fight Fraud, Waste and Abuse using Machine Learning AND Machine TEACHING (by human)
Roni Garland
Deputy Director, Division of Service and Infrastructure Fulfillment
CMS
Roni has worked for CMS for over 9 years and actively supports ISG in promoting the use of HCD through CCSQ and the agency.
Welcome from CMS Leadership
Steve Geller
VP Digital Services
eSimplicity
Steve has delivered many user-friendly digital products and customer experiences across industries as a product manager and leader.
Panel Discussion: Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals
Adam Heller
Director, Division of Service and Infrastructure Fulfillment
CMS
Adam has worked for CMS for over 10 years, and continues to support the maturation of the level of HCD beliefs and practices in the Information Systems Group's work and culture.
Welcome from CMS Leadership
Dr. Rachele Hendricks-Sturrup
Health Policy Counsel
The Future of Privacy Forum
Dr. Hendricks-Sturrup’s work involves using mixed methods research to explore and address ethical, legal, and social issues and implementation barriers at the forefront of health policy and innovation. Her research centers on generating best practices for the use and processing of health and genetic data.
Afternoon Plenary Session: Federated Learning to Collect Mobile Patient-Reported Outcomes
Dr. Sara R. Jordan
Policy Counsel, Artificial Intelligence
The Future of Privacy Forum
Dr. Jordan's expertise includes privacy implications for data sharing, data and Artificial Intelligence (AI) review boards, and privacy analysis and ethical challenges of AI and Machine Learning (ML) technologies.
Afternoon Plenary Session: Federated Learning to Collect Mobile Patient-Reported Outcomes
Harlan Krumholz, MD, SM
Director of the Yale New Haven Hospital Center for Outcomes Research and Evaluation, Harold H. Hines, Jr. Professor of Medicine
Yale University
Dr. Krumholz is a cardiologist and a leading expert in the science to evaluate and improve the quality and efficiency of care, reduce disparities, improve integrity in medical research, and avoid wasteful practices.
Panel Discussion: Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals
Ian Lowrie
Lead User Experience Researcher
Ad Hoc LLC
Hospital Quality Reporting
Ian is an anthropologist of technology and work. His research has focused on developer experience, the sociology of artificial intelligence work, and the ethnographic study of large-scale data handling platforms.
Presentation: How Humans Make AI Work
Darryl Marshall
Director of Consulting
eSimplicity
Darryl has engineered and led predictive and operational data modeling engagement in the Federal sector since 2011.
Panel Discussion: Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals
Keith A. McFarland
SVP and Chief Innovations Officer
eSimpilcity LLC
Keith’s background includes product management, development, delivery, and customer experience. He is the creative inventor of multiple patents.
Panel Discussion: Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals
Edward F. O’Connor
Director – Solutions Architecture, Health Division
ManTech
Edward focuses on systems of systems engineering (SoSE) practices, human factors engineering, and approaches that bring clinical, design, engineering, and operations resources together to solve problems.
Presentation: Using Human-Centered Machine-Learning (HCML) to Improve Data Quality & Data Governance Projects
Christina Schilstra
Innovation Program Manager
Tantus Technologies
Christina, with over 22 years of healthcare IT experience, recently developed AI proofs-of-concept for CMS.
Presentation: A Gold Mining Adventure – Using Natural Language Processing and Machine Learning to find Gold in Unstructured Data
Bin Shao, Ph.D.
Lead AI Scientist and Architect
eSimplicity
With a deep understanding of the latest advances in AI and machine learning research, Dr. Shao specializes in using computer vision and deep reinforcement learning technologies to solve real-world problems.
Panel Discussion: Capabilities and Challenges for Machine Learning focused on Preserving Privacy and CMS Healthcare Goals
Stephanie Warren
UX Content Strategist
Bellese Technologies
Hospital Quality Reporting
Stephanie creates engaging digital experiences and is obsessed with uncovering ways to reduce friction within government systems.
Presentation: How Humans Make AI Work