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Speakers

 John Ainsworth

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

David Anderson, Ph.D

Assistant Professor, Operations Management

Baruch College

Dr. David Anderson currently is an Assistant Professor of Operations Management at Baruch College, and is an Outside Partner at Elder Research, a data mining consultancy. He was a consultant at Booz Allen Hamilton prior to completing his PhD. He has worked as a technical lead on analytics projects for government and industry clients, and consulted with hospital systems in New York, Maryland, and Washington D.C. His academic research focuses on predictive modeling and applied optimization. His has published extensively in academic journals like Nature, Production and Operations Management, and IIE Transactions on Healthcare Systems Engineering. David received his Ph.D. in operations management from the University of Maryland, and a B.S. in Applied Math from The College of William and Mary.

Session: Predicting Colorectal Cancer Mortality

 Jeff Deal

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

Benjamin Dummitt, PhD

Senior Research Data Scientist

Mercy Virtual

Benjamin Dummitt, PhD, serves as a data scientist for Mercy Virtual. Mercy is the 5th largest Catholic Health system in the US. Prior to joining Mercy, Dr. Dummitt was employed at Monsanto Company as a Business Process Analyst/Analytical Scientist. Dr. Dummitt has a wide variety of experience in the disciplines of Biological Sciences, Information Technology, and Data Analysis. He earned his doctorate at St. Louis University Medical School from the department of Molecular Biology and Biochemistry. He has several peer reviewed publications to his credit, including original research papers, a review paper, and a book chapter. He has championed the use of innovative technology approaches to research problems throughout his career and continues to do so for Mercy.

Session: Predictive Models for Retrospective and Real Time Evaluation of Septic Shock

 Alan Eisman

Alan Eisman

SVP of Sales and Business Development

HBI Solutions, Inc

Alan Eisman is SVP of Sales and Business Development for HBI Solutions, Inc which offers predictive analytics and performance analysis solutions to healthcare organizations worldwide. Prior to his role at HBI, Alan worked for Information Builders where he helped to form and led the organization's healthcare practice. Alan has over 25 years of senior management experience leading high growth sales and delivery teams and has advised a wide range of healthcare clients on the implementation and use of analytic applications. Alan holds a B.S. of Management from Rensselaer Polytechnic Institute.

Lunch and Learn: Practical Advice for Integrating Predictive Analytics Into Your Clinical Care Management Workflow

Dr. John Elder, Ph.D.

Dr. John Elder, Ph.D.

Founder & Chair

Elder Research

@johnelder4

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. 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

Dr. Michelle Gong

Director of Critical Care Research

Montefiore Medical Center

Dr. Gong is the Director of Critical Care Research at Montefiore Medical Center and Professor in Medicine and Epidemiology and Population Health at Albert Einstein College of Medicine. After receiving an engineering degree at the University of Pennsylvania, Dr. Gong went on to earn a medical degree at the Yale University School of Medicine and a Master of Clinical Epidemiology at the Harvard School of Public Health. Dr. Gong is recognized nationally and internationally for her expertise in critical care research. Her overall research focus has been on the prediction and prevention of acute critical illness and their complications. Continuously funded by the NIH for over 10 years for her research, her current projects have focused on acute respiratory distress syndrome, prevention of delirium, long term outcomes,development of new electronic acute care interfaces and the implementation science of how to improve adherence to best practice in critical care.

Session: Re-Engineering Electronic Health Record Systems to Facilitate Clinical Analytics in the Intensive Care Unit

 Thomas Hill, Ph.D.

Thomas Hill, Ph.D.

Executive Director Analytics

Dell Software Group

Dr. Thomas Hill is Executive Director for Analytics at Dell Software Group. He joined Dell through the acquisition of StatSoft Inc. in April 2014, where he had been Senior Vice President for Analytic Solutions for over 20 years and was responsible for building out Statistica into a leading analytics platform. Dr. Hill received his Vordiplom in psychology from Kiel University in Germany and earned an M.S. in industrial psychology and a Ph.D. in psychology and quantitative methods from the University of Kansas. He was on the faculty of the University of Tulsa from 1984 to 2009, where he conducted research in cognitive science and taught data analysis and data mining courses. He has received numerous academic grants and awards from the US National Science Foundation, the National Institute of Health, the Center for Innovation Management, and other institutions. Over the past 20 years, his team has completed diverse consulting projects with companies from practically all industries and has worked with leading financial services, insurance, retailing, manufacturing, pharmaceutical, healthcare, and other companies in the United States and internationally on identifying and refining effective predictive modeling solutions for a broad scope of applications. Dr. Hill has published widely on innovative applications for data mining and predictive analytics and is also the author (with Paul Lewicki, 2005) of "Statistics: Methods and Applications," the "Electronic Statistics Textbook" (a popular on-line resource on statistics and data mining), and a co-author of "Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications" (2012) and "Practical Predictive Analytics and Decisioning Systems for Medicine" (Elsevier/Academic Press, 2014). Hill is also a contributing author to the popular "Handbook of Statistical Analysis and Data Mining Applications (2009)."

Sponsor Presentation: Big Data Challenges and Best Practices

Dr. Martin Kohn

Dr. Martin Kohn

Chief Medical Scientist

Sentrian (formerly with IBM Watson)

Dr. Martin Kohn is Chief Medical Scientist at Sentrian. His research work includes healthcare population analytics and the role of expert systems in the clinical decision process. Dr. Kohn is a board-certified emergency physician with over 30 years of hospital-based practice and management experience. He is an alumnus of MIT, Harvard Medical School and NYU, and is a Fellow of the American College of Emergency Physicians and the American College of Physician Executives. He is board certified in Clinical Informatics through the American Board of Preventive Medicine. Dr. Kohn is on the editorial board of the Journal of Emergency Medicine and has published multiple articles and book chapters on clinical, technical and management subjects.

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.

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

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

Ion Nemteanu

Manager of Analytic Services

Becton Dickinson

Ion Nemteanu is the Manager of Analytic Services Team for Becton Dickinson where he leads a team of data scientists and analytic consultants to support BD's R&D teams. Ion has specialized in studying and automating useful insights for over 13 years using a variety of experience from different industries. Most recently, Ion has worked closely with clinical medical device data and leverages predictive analytics to enhance BD's customers' experiences, improve the delivery of clinical services, and to reduce the patient's hospital length of stay. Ion holds a Master's Degree in Predictive Analytics from Northwestern University and a Bachelor's in Business/MIS from California State University, San Marcos.

Session: Reducing Service Costs by Predicting Device Failures

 Jessica Taylor

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

Jaya Tripathi

Principal Scientist (Principal Investigator on Project)

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.

Session: Identifying Prescription Drug Fraud and Abuse

 Nephi  Walton

Nephi Walton

MD, MS Biomedical Informatics

Washington University / University of Utah

Nephi Walton received an MD as well as a masters in Biomedical Informatics from the University of Utah, where his work was focused on using data mining and predictive analytics in the fields of genetics, bio-surveillance and hospital management.

He was the winner of the 2008 American Medical Informatics Association National Data Mining Competition. He has more than 7 years of experience using neural networks, Bayesian networks, decision trees, and other data mining methods for predictive analytics. He has 18 years of experience in industry programming and managing databases, including the development of award winning complex 3D and mobile applications.

In addition to his work in industry he is a physician at Washington University where he is completing a dual residency in both pediatrics and genetics. He has contributed to several books and papers on predictive analytics and data mining.

KEYNOTE: Predictive Analytics, Genomics, and Precision Medicine - Separating the Hype from the Reality

 Eric Williams

Eric Williams

Director of Data Science

Omada Health

Eric Williams is Director of Data Science at Omada Health. As an undergraduate Eric studied physics at UC Berkeley, later receiving his PhD from Columbia University in Particle Physics. He was a Researcher at CERN for several years and a Postdoctoral Scholar at Memorial Sloan-Kettering Cancer Center before joining Omada Health in 2014. At Omada, Eric's team focuses on the data science of behavior change - leveraging analysis, machine learning and experimentation to lower the global burden of obesity related chronic disease. He also volunteers with DataKind, an organization devoted to helping social organizations tackle critical humanitarian issues using data.

Session: What Healthcare Can Learn from Netflix: Building Personalization and Optimization into Preventative Care

 William Wood

William Wood

VP, Medical Affairs

St. Joseph Healthcare

William Wood, M.D. is Vice President of Medical Affairs at St. Joseph Healthcare, a Covenant hospital in Bangor, Maine. His current responsibilities include health information technologies for St. Joseph Healthcare. Prior to his current position, he served as CMIO for 5 years and medical director of internal medicine for 20 years. Dr. Wood, along with the care management team at St. Joseph Healthcare, have enjoyed a close working relationship with HealthInfoNet and more recently with HBI refining their real-time data analytics package. Dr. Wood is a Maine native and a graduate of Dartmouth Medical School and completed his residency in internal medicine at Mount Auburn Hospital in Cambridge, Massachusetts.

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

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

Scott Zasadil, Ph.D

Chief Scientist

UPMC Health Plan

Dr. Zasadil holds a Ph.D. in Mathematical Physics from Indiana University with a specialization in Partial Differential Equations, Numerical Analysis, and Statistical Mechanics. He is the Chief Scientist for the Health Economics department at UPMC Health Plan where he utilizes machine learning and data mining techniques in the development of predictive models. His prior job titles have included positions as: mathematician, physicist, software engineer and scientist. He has been involved in the programming, modeling, simulation and data analysis of projects in the fields of atmospheric physics, radiation oncology, supply chain logistics, and medical informatics.

Session: The Best of Both Worlds: Predictive Modeling Using Both Health Plan and Hospital Data

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