Daniel has been helping organizations navigate the complexities of creating actionable insights from their data for more than 10 years. At Elder Research, Daniel is responsible for leading the Commercial Analytics group. He leads highly specialized teams in the building and assessment of analytical models, having worked across a wide-range of industries including insurance, oil and gas, and manufacturing. Examples of Daniel's successes include creating custom scoring algorithms to identify outliers and rare business events, providing model validation audits, and developing ensemble models that help reduce operational downtime and associated losses.

Daniel earned a BS degree in Applied Mathematics and Master's Degree in Advanced Analytics from North Carolina State University. Prior to joining ERI, he owned a project and logistics management consulting firm and served as a Captain in the US Army in numerous leadership and intelligence roles. He is an expert data scientist, comfortable with diverse data sources in diverse industries.

Daniel Chertok, Ph.D., is a Sr. Data Scientist at NorthShore University HealthSystem. He is responsible for developing predictive models for population health management, operational cost containment and staffing optimization. Additionally, Daniel provides thought leadership on best analytical practices and has authored an internal standard operating procedures manual implemented by the Clinical Analytics team. His previous experience includes work in quantitative finance. Daniel holds a Ph.D. in Applied Mathematics from Simon Fraser University in Canada and an Eng. Math in Applied Mathematics from Peter the Great St. Petersburg Polytechnic University.

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.

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.

Chris is the Chair of Predictive Analytics World Healthcare and the Vice President of Advanced Analytics for OSF Healthcare where he leads a team of data scientists and automation engineers who create and deploy industry leading advanced analytics solutions.  He has more than 16 years of experience working in healthcare and holds a MS in Predictive Analytics from Northwestern University, where he focused on advanced modeling techniques and predictive text mining.

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.

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.

Nick has spent the past 11 years at OSF HealthCare developing and implementing analytical solutions in a variety of roles. He began his career building the tools that maintain, process, and visualize data as a data engineer and business intelligence developer to building machine learning and optimization models as a data scientist. He currently serves as the Manager of Data Science Services where he and his team leverage their diverse quantitative backgrounds to solve critical and complex problems across all areas of the healthcare system. Nick holds bachelor’s and master’s degrees in Industrial and Systems Engineering from Northern Illinois University.

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.