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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:  Predicting Patient Risk of Acquiring Antibiotic Resistant Superbugs from the Environment

 Feras Batarseh

Feras Batarseh

Research Assistant Professor

George Mason University - George Washington University

Feras A. Batarseh is a Research Assistant Professor with the College of Science at George Mason University (GMU). His research spans the areas of Data Science, Artificial Intelligence, and Context-Aware Software Systems.

Dr. Batarseh obtained his Ph.D. and M.Sc. in Computer Engineering from the University of Central Florida (UCF) (2007, 2011), and a Graduate Certificate in Project Leadership from Cornell University (2016). His research work has been published at various prestigious journals and international conferences. Additionally, Dr. Batarseh published and edited several book chapters. He taught data science and software engineering courses at multiple universities including GMU, UCF as well as George Washington University (GWU).

Prior to joining GMU, Dr. Batarseh was a Program Manager with the Data Mining and Advanced Analytics team at MicroStrategy, Inc., a global business intelligence corporation based in Tysons Corner, Virginia. During his tenure, he helped several clients make sense of their data and gain insights into improving their operations. Furthermore, throughout his career, Dr. Batarseh worked with multiple federal and state government agencies on a variety of data science applications and analytical deployments. He is currently working with the Economic Research Services (ERS at the US Department of Agriculture) towards building intelligent data management systems. 

Session:  Evaluating the Quality of State's Healthcare Using Big Data Analytics

 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.

 Erek Dyskant

Erek Dyskant

Co-founder and VP of Impact

BlueLabs

Erek Dyskant is co-founder and VP of Impact at BlueLabs, an analytics and technology company dedicated to harnessing the power of data to produce meaningful two-way engagement between people and organizations. Erek is focused on empowering individuals to take steps that make their political voice heard, improve their health, and strengthen their financial security.

As lead of the BlueLabs healthcare & public sector practice, he has transformed government agencies and large healthcare organizations to take a data-driven, evidence-based approach to engaging with their constituents, where the experience is streamlined and each individual receives the information that is proven to help them take the next step.

Before co-founding BlueLabs, he lead the geospatial analytics team at Obama's 2012 re-election campaign, where he developed the geospatial algorithms necessary to make 25 million effective, relevant, voter contacts in 4 days.

Session:  Creating Engaging Patient Journeys with Persuasion Modeling

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: Thinking Hard and Soft:  The Clash of Data Science, AI, and Human Expertise

Workshop:  The Best and the Worst of Predictive Analytics: Machine Learning Methods and Common Data Science Mistakes

 Brendan FitzGerald

Brendan FitzGerald

Director of Research

HIMSS Analytics

As director of research, FitzGerald is responsible for all HIMSS Analytics research initiatives and is the author of the Essential Briefs Knowledge Series publications. He and his team work closely on custom engagements, conducting and analyzing qualitative and quantitative research to meet client needs. A former Wall Street equity analyst, FitzGerald has applied his data analysis and research acumen in the healthcare information technology industry for the past 10 years.

Session:  State of Precision Medicine: Where it is headed and how to discern the signals from the noise

 Chris Franciskovich

Chris Franciskovich

Vice President of Advanced Analytics

OSF Healthcare System

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.

Session: The Tale of Two Models: Identifying High Risk Patients in an Ambulatory Setting

Session:  The Benefits and Challenges of Building an In-House Data Science Team

 Miriam Friedel

Miriam Friedel

Director of Commercial Analytics

Elder Research, Inc

Dr. Miriam Friedel has over a decade of experience with scientific modeling, predictive analytics, and software engineering in fields spanning theoretical physics, transportation, neuroscience, and telecommunications.  Her unique background enables her to bridge the gap between complex concepts and understandable, actionable results. Dr. Friedel has built and deployed models to predict customer churn and user segmentation, has mined survey responses for a major non-profit, and has wide experience analyzing complex scientific data in physics and biology. Miriam leads the Commercial Data Science Team at Elder Research. 

Prior to joining Elder Research, Miriam worked as a management consultant, helping clients to build and deploy software solutions with wide-ranging organizational impact; and as a research scientist in a neuroimaging lab, developing scientific software and performing advanced statistical analysis. Miriam has a B.S. in Physics from Brown University and a Ph.D. in Physics from the University of California, Santa Barbara and is a co-author on over fifteen peer-reviewed journal articles. 

Session:  Speaker Moderator

 Anna Kondic

Anna Kondic

Executive Director, Predictive Economic Modeling

Merck KGaA

Anna Georgieva Kondic is a mathematician by training with a PhD in mathematical physics from Duke University. Аnna also holds an MBA from New York University. After finishing her PhD, Anna completed her postdoctoral training in computational toxicology at CIIT, followed by a research professorship position at New Jersey Institute of Technology. During her 16 years in the pharmaceutical industry at Novartis and Merck, Anna worked in a variety of mathematical, data mining, decision analysis and economics applications and in a variety of therapeutic areas, most notably oncology, osteoporosis and cardio-vascular disease.

Session:  Predicting Survival in Lung Cancer Based on Early Clinical Readouts using Modeling of Literature Data

 Aleksandar Lazarevic

Aleksandar Lazarevic

Senior Director

Aetna

Aleksandar Lazarevic, Ph.D., Senior Director at Aetna Analytics Organization (Hartford, CT).  Aleksandar is responsible for overall predictive analytics solutions in Aetna's health care fraud initiative. In addition to the health care industry, Aleksandar has extensive experience in analytics projects ranging from banking, credit and insurance industry, to diagnostics and computer security applications. He has co-edited a book on cyber security threats, written eight book chapters and published over 50 research articles, which were cited more than 3,500 times. He holds a PhD degree in data mining and machine learning from Temple University.

Session:  Machine Learning for Health Care Fraud Detection

 Pamela Peele

Pamela Peele

Chief Analytics Officer

UPMC Health Plan & UMPC Enterprises

Keynote:  Healthcare Analytics: Why is this so expensive and hard? And what are we getting for our money
Expert Panel: Is there an "Easy Button" for Healthcare Analytics?

 Juli Plack

Juli Plack

Vice President of Information Delivery

OSF Healthcare

Juli is the Vice President of Information Delivery for Healthcare Analytics at OSF Healthcare System.  She is responsible for advanced analytics (including predictive modeling), intake, review and prioritization of reporting and analytic requests from the business to enable decision making, process improvement, and value creation across the Ministry.  She has more than 20 years of analytical experience and over 10 years of healthcare experience. Juli holds a Bachelor of Science degree with majors in both Business Administration and Marketing from Illinois State University.

Session:  The Benefits and Challenges of Building an In-House Data Science Team

 Simon Rimmele

Simon Rimmele

Associate, Analytics

NYC Mayor's Office of Data Analytics

Simon Rimmele is an Analytics Associate at the Mayor's Office of Data Analytics in New York City. He uses quantitative tools such as statistical learning algorithms to improve operational outcomes and service delivery for New Yorkers.

He previously spent several years in the financial sector, focusing on multi-asset market risk management at McKinsey & Company's Investment Office. He has a BA in Economics from
Columbia University.

Session:  Legionnaires' Disease in New York City: Analytics of the Built Environment for Emergency Services

 George Savage

George Savage

Co-Founder & Chief Medical Officer

Proteus Digital Health

George Savage is chief medical officer and co-founder of Proteus Digital Health, and formerly the company's vice president of research and development. He sees Digital Medicine as an invaluable collaboration platform for patient and physician, integrating information about a patient's response to therapy directly into everyday healthcare.

George is focused on developing the clinical and economic evidence needed to secure global regulatory approvals and spur widespread adoption of Proteus's ingestible sensor platform. He serves on the board of the California Life Sciences Association, the Boston University College of Engineering advisory council, and in 2016 was elected a Fellow of the American Institute for Medical and Biological Engineering.

George holds a B.S. in biomedical engineering from Boston University, an M.D. from Tufts University School of Medicine, and an M.B.A. from Stanford University Graduate School of Business. He completed postgraduate training in surgery at the University of Massachusetts and is licensed to practice medicine in California. George has a successful 27-year track record of starting and developing technology-based healthcare companies in Silicon Valley.

Keynote:  Digital Medicine: Returning Patients to the Center of Healthcare

 Matt Schuchardt

Matt Schuchardt

Director of Business Development and Innovation

HIMSS Analytics

Matt Schuchardt is the Director of Innovation and Business Development at HIMSS Analytics. Matt is responsible for HIMSS Analytics' Predict and machine learning projects. He has more than 15 years of experience in healthcare IT research. Matt began his career in healthcare IT research working with Sheldon Dorenfest at Dorenfest & Associates, the original healthcare technology research firm. He joined HIMSS as part of the Dorenfest acquisition in 2004. With 15 years of experience unlocking the value of data, Matt understands data capture, knows data usage and sees a brighter data-driven future.

Prior to entering the healthcare IT field, Matt worked in in the field as a social worker at the Jane Addams Hull House. Matt has a BA in Anthropology from the University of Chicago where he worked as a researcher at the National Opinion Research Center.

Session:  State of Precision Medicine: Where it is Headed and How to Discern the Signal from the Noise

Dr. Eric Siegel

Dr. Eric Siegel

Conference Founder

Machine Learning Week

@predictanalytic

Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI Applications Summit, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.


Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

Session:  Conference Founder Remarks

 Yunlong Wang, Ph.D.

Yunlong Wang, Ph.D.

Manager, Advanced Analytics

QuintilesIMS

Yunlong Wang: Data scientist of Advanced Analytics at QuintilesIMS. Trained as a computer and machine learning scientist, Yunlong has expertise in machine learning, data modeling and their applications to social network analysis and health care industry. In this capacity, he provides methodological and analytical support to help clients solve complex issues in business and health outcomes research. Prior joining QuintilesIMS, Yunlong was a post-doctoral research fellow at the University of Minnesota. He received his PhD degree in computer engineering from the Stony Brook University. He has published more than 15 journal/conference papers and book chapters.

Session:  Using Deep Learning to Identify the Key Triggers of Initiating Patient First Line Treatment: An Oncology Case Study

 Jason Weinberg

Jason Weinberg

Data Scientist

OSF Healthcare

Jason Weinber is a Statistician at OSF Healthcare. He applies data mining, machine learning, and inferential techniques to improve operational and clinical initiatives throughout the OSF Ministry. He has 5+ years of experience in the healthcare industry and holds an MS in Health Informatics from The College of Saint Scholastica, a private Benedictine university. His academics focused on software development, biostatistics, consumer informatics, predictive modeling and data mining techniques.

Session:  The Tale of Two Models: Identifying High Risk Patients in an Ambulatory Setting

 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:  State of the Data Science in Healthcare
Expert Panel: Is there an "Easy Button" for Healthcare Analytics?

 Yilian Yuan, Ph.D.

Yilian Yuan, Ph.D.

Vice President, Statistics and Advanced Analytics

QuintilesIMS

Yilian Yuan is vice president, Statistics and Advanced Analytics at QuintilesIMS. She leads a team of data scientists, statisticians and research experts to help clients address a broad range of business and industry issues. Dr. Yuan has an extensive background in applying econometric and statistical modeling, predictive modeling and machine learning, discrete choice modeling and quantitative market research, combined with patient-level longitudinal data to provide actionable insights for Pharma clients to improve business performance. 

Session:  Using Deep Learning to Identify the Key Triggers of Initiating Patient First Line Treatment: An Oncology Case Study

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