John Ainsworth
Senior Data Scientist
University of Virginia Health System
John Ainsworth is a senior data scientist employed by the Universityof Virginia Health System since July of 2014. He is currently workingwith the UVa Medical Center on a variety of predictive analyticprojects including the CMS AI Challenge where his team was selected asone of 25 competitors. Prior to coming to UVA, John designed,implemented, deployed, and monitored predictive analytic solutions fora wide variety of industries for Elder Research, a predictiveanalytics consulting company.
Session: Developing a custom Severe Sepsis Early Warning System for deployment into Epic
David Anderson, Ph.D
Assistant Professor, Operations Management
Baruch College
Jeff Deal
Chief Operating Officer
Elder Research
Jeff Deal is the Chief Operating Officer for Elder Research, the nation's leading data science, machine learning, and artificial intelligence consultancy. He has also been the Chair of the Predictive Analytics World for Healthcare conference since its inception in 2014. In his role at Elder Research, Jeff oversees the operations of the business including contracting, finances, regulatory/legal issues and human resources. Jeff has worked with dozens of clients to understand their business needs and organizational goals and, in the process, has gained insight into organizational obstacles to successful data analytics engagements. His talk on the Top 10 Data Mining Business Mistakes has been well received at prior Predictive Analytics World conferences. In 2016, Jeff and the Elder Research President & CEO, Gerhard Pilcher, published, Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics.
Jeff has more than 30 years of experience in business operations, planning, and government relations, primarily in the health care industry. Prior to ERI, he was the president of a health planning consulting business that assisted hospitals and physicians with operational analysis, forecasting, and navigating through complex regulatory processes. Before that, Jeff spent 16 years in hospital administration with responsibility for clinical, support, and planning functions. Jeff has a Master of Health Administration degree from Virginia Commonwealth University and an undergraduate degree from the College of William and Mary.
Benjamin Dummitt, PhD
Senior Research Data Scientist
Mercy Virtual
Session: Predictive Models for Retrospective and Real Time Evaluation of Septic Shock
Alan Eisman
SVP of Sales and Business Development
HBI Solutions, Inc
Lunch and Learn: Practical Advice for Integrating Predictive Analytics Into Your Clinical Care Management Workflow
Dr. John Elder, Ph.D.
Founder & Chair
Elder Research
John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, and Washington DC. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.
Special Plenary Session: Doing Space-Age Analytics with Our Hunter-Gatherer Brains
Dr. Michelle Gong
Director of Critical Care Research
Montefiore Medical Center
Thomas Hill, Ph.D.
Executive Director Analytics
Dell Software Group
Sponsor Presentation: Big Data Challenges and Best Practices
Dr. Martin Kohn
Chief Medical Scientist
Sentrian (formerly with IBM Watson)
Prior to joining Jointly Health, Dr. Kohn was the Chief Medical Scientist for Care Delivery Systems in IBM Research where he led IBM's support for the transformation of healthcare, including the use of the Watson supercomputer in healthcare. He speaks frequently on the issues of healthcare transformation, the role of information technology, the Patient Centered Medical Home and clinical decision support. Dr. Kohn is a co-author of IBM's white paper "Patient-Centered Medical Home - What, Why and How." Dr. Kohn was previously in IBM Healthcare Strategy and Change, which helped healthcare systems and clinicians optimize process and make best use of health information technology.
His extended training and experience in health care management, policy and operations, as well as his background as a systems engineer, enable him to communicate with all stakeholder groups. He has had major roles in addressing the interaction between clinical process and information technology in projects involving information sharing, clinical process re-design, patient access and policy.
KEYNOTE: Real World Data and the Transformation of Healthcare
Wasim Malik, Ph.D.
Assistant Professor and Director of Harvard
MIT Laboratory for Neuromotor Signal Processing
Dr. Wasim Q. Malik is the Director of the Laboratory for Neuromotor Signal Processing and Assistant Professor at Harvard Medical School. He is affiliated with the Department of Anesthesia, Critical Care and Pain Medicine at Massachusetts General Hospital. He also holds visiting faculty appointments at Massachusetts Institute of Technology and Brown University. He is also with the Center of Excellence for Neurorestoration and Neurotechnology, Department of Veterans Affairs Medical Center, Providence, RI.
Wasim received his Ph.D. in electrical engineering from the University of Oxford, UK, in 2005. In his doctoral research, he designed high data-rate ultrawideband (UWB) systems for indoor wireless communications. From 2005 to 2007, he was a Research Fellow at the University of Oxford, where he developed MIMO signal processing techniques for multi-gigabit UWB wireless communications. From 2007-2010, he was a Postdoctoral Research Fellow at MIT LIDS and MIT/Harvard NSRL with Prof. Emery Brown, where he conducted research in computational neuroscience focusing on statistical signal processing and adaptive filtering algorithms for two-photon neuroimaging and neural decoding.
He has published an edited book titled Ultra-Wideband Antennas and Propagation for Communications, Radar and Imaging (UK: Wiley, 2006). He was the Lead Guest Editor of the IET Microwaves Antennas and Propagation special issue on "Antenna systems and propagation for future wireless communications" (Dec. 2007). In addition to 5 patents, he has published in excess of 100 research papers in refereed journals and conference proceedings. He received the Association for Computing Machinery Recognition of Service Award (2000), the Best Paper Award in the ARMMS RF & Microwave Conference (Steventon, UK, 2006), the ESU Lindemann Science Fellowship (2007), and the CIMIT Shore Career Development Award (2010).
Wasim is the current Chair of the IEEE Engineering and Medicine in Biology Society (EMBS), Boston Section. He is a Senior Member of the IEEE, a Member of the IEEE Life Sciences Technical Committee, a Member of the IEEE Communications Society, a Member of the Society for Neuroscience, a Member of the Society for the Neural Control of Movement, and a Member of the New York Academy of Sciences. He routinely serves on the organizing and technical program committees of various international conferences, and was the Chair of IET UWBST'08 and IEEE ICUWB'08. He has been a grant reviewer for the national research councils of Norway, Romania, Singapore and Chile. He served on the UK Ofcom Task Group on Mobile and Terrestrial Propagation, and as an expert on the use of information and communication technologies for the health sector in the Scientific and Technological Policy panel of the European Parliament and Commission. He is a member of the EU Framework Programme COST Action Network on "Patients at the heart of finding innovations to manage dementia through engineering and robotics" (PATHFINDER). He is the Co-Chair of the IEEE Medical Devices Big Data Standards Working Group, a joint effort of the IEEE Standards Association, Life Sciences Technical Committee, Engineering in Medicine & Biology Society, and Big Data Initiative.
Keynote: Brain-Machine Interface Technology: Separating Hope from Hype
Melanie McLeod
Health IT Transformation and Analytics
Kaiser Permanente
Melanie McLeod, MA, MPH is a Senior Operations Consultant in Health IT Transformation and Analytics (HITTA). Melanie joined KP in 2013 and provides analytic and project management support on evaluation and strategic optimization projects related to KPHC and kp.org. Her projects have included Open Notes, Ready to Quit and the Virtual Care Center of Evaluation and Research. Prior to joining KP, Melanie worked internationally for five years and domestically for four years as an evaluation manager for health related projects.
Session: Ready to Quit? Using Predictive Analytics to Increase Enrollment in Smoking Cessation Programs
Ion Nemteanu
Manager of Analytic Services
Becton Dickinson
Session: Reducing Service Costs by Predicting Device Failures
Jessica Taylor
Care Manager
St. Joseph Healthcare
Jessica is a care manager for St. Joseph Healthcare. She directly manages and makes assignments to staff for high risk patients using the real time predictive tools.
Session: Real-Time, Clinical Driven Predictive Analytics for Care Management
Lunch and Learn: Practical Advice for Integrating Predictive Analytics Into Your Clinical Care Management Workflow
Jaya Tripathi
Principal, Data Analytics
MITRE Corporation
Jaya Tripathi is a Principal Scientist and an advanced analytics expert in The MITRE Corporation’s Information Technology Technical Center.
She is the principal investigator in MITRE's effort to apply health IT concepts to address prescription drug misuse and abuse. She has been working in this domain for many years and has collaborated with law enforcement officials, physicians, policy makers, Board of Pharmacy, academicians and state and Federal partners.
She has been at MITRE for 14 years. Before joining MITRE, Ms. Tripathi worked at several multinational corporations, applying big data analytics on projects such as a customer retention forecasting pilot for a major telecommunications company, and the origin-and-destination revenue management, one of the most significant innovations in the airline industry. She holds master’s degrees in physics and computer science from the University of Texas.
Nephi Walton
Associate Medical Director
Intermountain Healthcare
Dr. Nephi Walton is a biomedical informaticist and clinical geneticist with experience in machine learning and genomics. He had led several research initiatives in genomics and informatics at Geisinger prior to joining Intermountain Healthcare. At Geisinger he successfully completed a pilot integration of genomics data into the EPIC electronic health record system for both pharmacogenomics and CDC tier one genetic conditions. He currently serves as the Associate Medical Director of Intermountain Precision Genomics where he leads the HerediGene Genomic Sequencing Return of Results program. He also serves as the Associate Medical Director of Intermountain’s sequencing laboratory. He is the Chair of Genomics and Translational Bioinformatics for the American Medical Informatics Association and has presented at several meetings on translating the use of genomics into general medical practice, something he is actively pursuing at Intermountain Healthcare.
KEYNOTE: Predictive Analytics, Genomics, and Precision Medicine - Separating the Hype from the Reality
Eric Williams
Director of Data Science
Omada Health
William Wood
VP, Medical Affairs
St. Joseph Healthcare
Session: Real-Time, Clinical Driven Predictive Analytics for Care Management
Lunch and Learn: Practical Advice for Integrating Predictive Analytics Into Your Clinical Care Management Workflow
Ken Yale, JD, DDS
Instructor
University of California - Irvine
Ken is trained in population statistics, medicine/dentistry, and law. He worked in clinical practice, data science, care management, and health regulations. Ken was a government official in the US Senate and White House. After that he was Founder/CEO of Advanced Health Solutions and held executive positions at CorSolutions, Matria Healthcare, UnitedHealth Group, and Aetna. Ken held leadership roles in the Maryland State Task Force on Electronic Medical Records, the University of Maryland Center for Health Information and Decision Systems, and Utilization Review Accreditation Commission (URAC). He is a frequent author and speaker, including Handbook of Statistical Analysis and Data Mining Applications; Clinical Integration: Population Health and Accountable Care; Divining Healthcare Charges for Optimal Health Benefits Under the Affordable Care Act. With a team of data science industry experts he leads a certificate program in Healthcare Predictive Analytics at University of California, to train the next generation of health data scientists.
KEYNOTE: Predictive Analytics, Genomics, and Precision Medicine - Separating the Hype from the Reality
Scott Zasadil, Ph.D
Chief Scientist
UPMC Health Plan
Session: The Best of Both Worlds: Predictive Modeling Using Both Health Plan and Hospital Data