Predictive Analytics World for Healthcare Las Vegas 2020
May 31-June 4, 2020 – Caesars Palace, Las Vegas
Vice President of Data Science
Halim is a high tech innovator who spearheaded world-class data science projects at game changing techs like eBay and Teradata. Formally educated in Machine Learning, his professional expertise span Information Retrieval, Natural Language Processing, and Big Data. Halim has a proven track record of applying state of the art data science techniques across industry verticals such as eCommerce, web & mobile services, airline, BioPharma, and the medical technology industry. He currently leads the AI department at Cognoa, a data driven behavioral healthcare startup in Palo Alto.
Halim Abbas is speaker of the following session:
Former Product Lead, Machine Learning, Lyft
Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.
Gil Arditi is speaker of the following session:
Yu Chen is a Research Advisor of Outcomes and Translations Research at Eli Lilly and Company. He applies data mining, machine learning, and systems biology approaches in translational medicine study. He has 15+ years of R&D experience in industry. Yu completed his PhD in Bioinformatics from the joint program by University of Tennessee and Oak Ridge National Laboratory and performed his post-doctoral research at Novartis Pharmaceuticals Corporation.
Yu Chen is speaker of the following session:
Daniel Chertok PhD
Sr. Data Scientist
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.
Daniel Chertok PhD is speaker of the following session:
Kelley Counts is a Data Scientist at OneBlood. He leads teams that develop and deploy innovative machine learning applications to increase blood donations, anticipate hospital demand for blood products, and optimize the supply chain. Kelley also has expertise in marketing analytics, data visualization, and the development of statistical business solutions. In addition to his work at OneBlood, Kelley supervises teams of students in Data Science graduate programs. He has also worked on committees to design Python-based Machine Learning graduate courses. Kelley is a frequent speaker on practical applications of machine learning and has published articles on analytics-driven organizational change and workforce adoption. He has served on international professional boards as an advisor on analytics, digital technology, and information systems. Kelley has a Bachelors in Biochemistry, and a MS and MBA in Business Analytics.
Kelley Counts is speaker of the following session:
Chief Operating Officer
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.
Jeff Deal is speaker of the following session:
Associate Professor of Biostatistics, Radiation Oncology
Dr. DeWees is an Associate Professor of Biostatistics at Mayo Clinic in Arizona and serves as the lead biostatistician for Radiation Oncology across the Mayo Clinic enterprise. He is involved in all aspects of radiation oncology; working with departmental researchers from fields including: biologists, physicists, clinicians, residents, and students. He is responsible for design, monitoring, analysis, interpretation, and reporting for genetic, biological, animal, human, and machine trials. He aids in the design, implementation and publication of grants, prospective, and retrospective trials. Dr. DeWees’ research focuses on the optimization and utilization of statistical methodology for clinical data and patient reported outcomes.
Todd Dewees is speaker of the following session:
Co-Founder & Chief Scientist
Colleen Farrelly is a co-founder and the Chief Scientist of Quantopo, LLC. She was the lead statistician working with the Malian government on the 2014 Ebola outbreak and public health response, and her prior industry work has spanned TRICARE contracts for the US Navy, research and development at Cypher Genomics for the Genome England Competition and Celgene failed drug revival pipeline, consulting work within cardiology analytics and clinical trials, and predictive analytics work at Graham Holdings (Kaplan Higher and Professional Education), as well as educational work at Purdue University Global on their new analytics program. She is a writer for KDnuggets and is attempting her first lay audience analytics book at the moment.
Colleen Farrelly is speaker of the following session:
Head of Responsible Innovation, Global Affairs
Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.
Jen Gennai is speaker of the following session:
Statistical Programmer Analyst
Michael Golafshar is speaker of the following session:
Trained originally in Ecosystem Analysis & Modeling, Dr. Nisbet modeled forests at the University of California, Santa Barbara. He moved to NCR in 1994, developing configurable data mining applications for customer Churn, Propensity-to-buy, and Customer Acquisition in Telecommunications. He has worked also in Insurance, Banking, Credit, membership organizations (e.g. AAA), and Health Care industries. He is lead author of the award-winning Handbook of Statistical Analysis & Data Mining Applications (Academic Press, 2009, 2017), and a co-author and general editor of the award-winning "Practical Text Mining" (Academic Press, 2012) and Practical Predictive Analytics and Decisioning Systems in Medicine (Academic Press, 2015). A new book on Effective Data Preparation is available from with Cambridge University Press. Currently, he serves as an Instructor in the University of California at Irvine Predictive Analytics Certificate Program, teaching many online and on-campus courses each year in Effective Data Preparation and Predictive Analytics Applications.
Bob Nisbet is speaker of the following session:
Dr. Zeydy Ortiz is the co-founder & CEO of DataCrunch Lab, LLC. She has been helping teams and organizations transform data into value across many industries including IT, financial, retail, and the manufacturing sectors. Her team built an innovative, award-winning digital assistant that was recognized as 'Highest Potential Value to Manufacturers' for increasing visibility of real-time production and plant operations.
She started her career as a Performance Engineer at IBM building predictive models to inform business strategy. She worked on multiple projects focused on improving performance & efficiency. She earned recognition for innovation on Smarter Planet/IoT solutions and for her industry contributions defining resource efficiency metrics. Dr. Ortiz obtained her bachelor's degree from the University of Puerto Rico, master's from Texas A&M University, and Ph. D. in Computer Science from North Carolina State University.
Zeydy Ortiz is speaker of the following session:
Principal Data Scientist
Matt earned a MS in Physical Chemistry from the University of Rochester and a PGDip with distinction from DeMontfort University in Industrial Data Modeling. He began his career interfacing and automating instrumentation and sensors. When he joined General Electric 2004, he focused his career on applying the scientific method to analytics problems. Matt has applied data science to a varied array of fields including chemometrics, sustainability, industrial internet, and compliance.
Matthew Pietrzykowski is speaker of the following session:
Karl Rexer founded Rexer Analytics in 2002. He and his teams provide predictive modeling and analytic consulting to clients across many industries. Recent clients include PwC, Boston Scientific, Redbox, ADT
Security, Interamericana University, MIT, A.S.Watson, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Several software companies have sought Karl's input, and in 2008 and 2010 he served on SPSS's (IBM) Customer Advisory Board. He also served 11 years on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and views. Summary reports from these surveys are available as a free download from the Rexer Analytics website.
Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.
Karl Rexer is speaker of the following session:
Vice President of Innovative Strategies
Vickie Rice is a 20-year veteran of the benefits business and an expert in healthcare claims, analytics and product management. Rice spent a decade in key administrative roles at Blue Cross and Blue Shield of Oklahoma and then served as Product Manager for Data and Analytics at Benefitfocus where she helped create innovative data tools to help both benefits administrators and consumers make fact-based decisions about their healthcare benefits.
In her current role as VP of Innovative Strategies for CareATC, Rice has brought her passion of using data and technology to help patients live their healthiest lives to the Product Strategy team, leading them in their mission of offering world class healthcare services and solutions to our patients, providers and employer clients.
Vickie Rice is speaker of the following session:
Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.
Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.
Eric Siegel is speaker of the following session:
Executive Director, Enterprise Data Intelligence
Michael Thompson has over 30 years of using analytics to unleash hidden stories within data. The quest has led him to use a variety of data warehousing, visualization, statistical, data mining methodologies, and analytic modeling creations. The work of his teams has been shared in the Wall Street journal, industry symposiums, and publications over the years. With a personal goal to help others on their journey to find opportunities hidden in their data, Mike has led analytic teams across large financial and healthcare organizations.
Currently, Mike leads a multi-disciplined team (physicians, nurses, statisticians, data scientists, data analysts, data engineers, and data warehouse developers) to fulfill the insatiable financial, operational, clinical, quality, and population health analytic needs of the organization as the Executive Director of Enterprise Data Intelligence at Cedars-Sinai in Los Angeles, CA.
Michael Thompson is speaker of the following session: