Speakers Predictive Analytics World Chicago 2013
 Dean Abbott

Dean Abbott

President

Abbott Analytics, Inc.

@deanabb

Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.

He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Case Study: My Five Predictive Analytics Pet Peeves

 Swati  Abbott

Swati Abbott

CEO

Blue Health Intelligence

As Chief Executive Officer, Swati Abbott is leading the effort for Blue Health Intelligence (BHI®) to leverage data insights to develop innovative analytics solutions. This strategy includes extending the company's reach to external audiences, while enhancing BHI's value to Blue Cross and Blue Shield companies.

Prior to joining BHI, Abbott served as President of Elsevier/MEDai, an industry leader in predictive analytics, where she provided leadership and strategic vision to position the company at the forefront of the healthcare industry. Before MEDai, Abbott was Managing Director for the Medical Management Strategic Business Unit at ViPS, where she led strategic solutions development for medical management data warehousing and HEDIS reporting for healthcare payer clients. Abbott was also involved in leading SoftMed Systems, Inc. to create and provide solutions for hospitals and integrated delivery networks in the key areas of medical chart abstraction, quality assurance, utilization management, risk management and regulatory reporting.

As a respected industry leader, Abbott is a regular speaker at industry conferences, presenting on topics related to predictive modeling, medical home and healthcare clinical analytics. She is also a contributor and member of the editorial board for Predictive Modeling magazine and has been quoted in notable industry publications regarding the use and future of predictive analytics, the state of healthcare analytics and quality improvement initiatives. In 2010, Frost and Sullivan recognized Abbott as one of the Movers and Shakers in healthcare.

Abbott holds a Master of Science in computer science and a Bachelor of Science in physics from Delhi University, India.

Case Study: Leveraging Disparate Data Sources to Drive Business Decisions

 Guha  Athreya

Guha Athreya

Sr. Manager, Analytics

AbsolutData

• Responsible for delivery of analytics service and solutions
• Over 10 years of analytics experience across various verticals including financial services, CPG and hospitality
• Expertise in applications of analytics to enhance marketing effectiveness, risk management, CRM & consumer insights processes
• Responsible for overall service delivery across multiple client engagements
• Post Graduate degree in marketing sciences from the Department of Management Studies at IIT Madras

Gold Sponsor Presentation: Driving Marketing ROI across On-Line and Off-Line Channels

 Jeff  Brazell

Jeff Brazell

CEO

The Modellers

Jeff brings to his role as CEO at The Modellers a unique skill set and genuine passion for high-end market research to blend with a rich and diversified background in management experience, academic training and applied expertise, keen and tutored quantitative insight and university teaching experience. Over the past twenty years, he has held various high-level management positions at several national and international firms, has taught marketing at two Universities, and been extensively involved in researching new quantitative methods. While at the University of Sydney, Australia, Jeff developed relationships with several colleagues with whom he founded The Modellers.

For many years, Dr. Brazell has been actively involved in designing and delivering foundational and applicable research projects to help clients with their most difficult challenges. Some of Jeff's project/clients include General Motors, American Express, Intel, P&G, Citibank, Disney, Gateway Computers, GE, Kodak, eBay, IBM, Lucas Arts, Paramount, Purina, Schick, Toyota, and Verizon.

Case Study: Predictions At Work: Tools for Decision Support

 Veronique  Duverneuil

Veronique Duverneuil

Global Brand Analytics Director

Hewlett-Packard Company

Ms Veronique Duverneuil is the Director of Global Brand Analytics Team within the Global Brand Protection Organization at Hewlett Packard Company. She is managing a worldwide team of professional program managers and analysts specialized in the detection and minimization of fraud, in the Services, Sales and Supply Chain areas.

Ms Duverneuil has been with Hewlett-Packard for 24 years where she had various positions, in finance, IT, recycling business, Channel program management and Compliance & Audit, prior joining Global Security Services (GSS) in 2010.

Ms Duverneuil holds a Business Administration Degree from the Grenoble Ecole de Management Business School in France, with a major on new technologies.

Ms Duverneuil is married. She resides in Grenoble, France.

Case Study: Predictive Modeling of Warranty Non Compliance Detection

Dr. John Elder

Dr. John Elder

CEO & Founder

Elder Research, Inc.

@johnelder4

Dr. John Elder heads the US's largest and most experienced data mining consulting team -- with offices in Charlottesville Virginia, Washington DC, and Baltimore Maryland. Founded in 1995, Elder Research (www.datamininglab.com) focuses on investment, commercial and security applications of advanced analytics, including text mining, credit scoring, image recognition, production optimization, cross-selling, drug efficacy, market timing, and fraud detection.

John earned Engineering degrees from Rice University and the University of Virginia, where he's an adjunct professor teaching Optimization or Data Mining. Prior to 19 years at ERI, he spent 5 years in aerospace defense consulting, 4 heading research at an investment management firm, and 2 in Rice's Computational & Applied Mathematics department.

Dr. Elder has authored innovative data mining tools, is a frequent keynote speaker, and has chaired international Analytics conferences. John was honored to serve for 5 years on a panel appointed by President Bush to guide technology for National Security. His book with Bob Nisbet and Gary Miner, Handbook of Statistical Analysis & Data Mining Applications, won the PROSE award for Mathematics in 2009. His book with Giovanni Seni, Ensemble Methods in Data Mining, was published in February 2010, and his book on Practical Text Mining, with Andrew Fast and 4 others, won the 2012 PROSE Award for top book in Computing and Information Sciences.

Special Plenary Session: General Lessons We Can Learn from Blackbox Trading

 Jerrard  Gaertner

Jerrard Gaertner

President

Canadian Information Processing Society - Ontario

Jerrard Gaertner is a Chartered Professional Accountant (CPA), Certified Information Systems Auditor (CISA), Certified Information Systems Security Professional (CISSP), as well as holding certifications in IT governance, internal audit, fraud investigation and technology management. He is President of the Canadian Information Processing Society (Ontario), and Senior Vice-President - Risk, Compliance and Security, at Managed Analytic Services Inc., which he co-founded. For 25+ years, Jerry has worked in the areas of systems assurance, computer audit and security, eventually leading the national practices at two difference global accounting firms. He is author of numerous articles on security, privacy, technology governance and risk, and co-author of 3 books. Jerry serves on the IT specialization committee of the CICA and is developing a graduate-level program in computer security/privacy for a major university. He has spoken to the ACM, ISACA, Canadian Bar Association, U Waterloo, among many other venues. Jerry is a graduate of MIT.

Case Study: Compliance Issues in Real World Analytics - Security, Privacy, Regulatory Requirements and Due Diligence

 Rayid Ghani

Rayid Ghani

Chief Data Scientist

Obama for America

Rayid Ghani was the Chief Scientist at Obama for America 2012 campaign focusing on analytics, technology, and data. His work focused on improving different functions of the campaign including fundraising, volunteer, and voter targeting and mobilization using analytics, social media, and machine learning. Before joining the campaign, Rayid was a Senior Research Scientist and Director of Analytics research at Accenture Labs where he led a technology research team focused on applied R&D in analytics, machine learning, and data mining for large-scale & emerging business problems in various industries including healthcare, retail & CPG, manufacturing, intelligence, and financial services. In addition, Rayid serves as an adviser to several start-ups in Analytics, is an active organizer of and participant in academic and industry analytics conferences, and publishes regularly in machine learning and data mining conferences and journals.

Keynote: Analytics and the Presidential Elections

 Stephen Gold

Stephen Gold

VP of Worldwide Marketing

IBM

Stephen Gold is Vice President of WW Marketing, Watson Solutions, IBM Software Group. He has overall responsibility for the brands marketing strategy, marketing communications, social media, public relations, analyst relations, sales enablement, demand generation, and events. As a member of the senior leadership team he is working to help commercialize industry solutions based on IBM’s transformative Watson technology.

Prior to joining IBM, Stephen was Vice President of Marketing (CMO) for SPSS, acquired by IBM in 2009. As President of the Aberdeen Group, a Harte-Hanks Company, Stephen oversaw all aspects of the publically traded market research organization, which covered twenty-six distinct technology markets. Previous to this Stephen successfully scaled and sold two Silicon Valley based startups; Azerity to ModelN in 2006 in the capacity as CEO and Digital Market to Agile (now Oracle), as its CMO.

Stephen has a twenty-year winning track record of leading successful enterprises and building businesses across industries (technology, software and services) and geographies (domestic and international) for both high growth private and multi-billion dollar publicly traded corporations. Stephen holds a B.S. in Mechanical Engineering from the University of Illinois at Champaign-Urbana and graduated with distinction from Carnegie Mellon University with an MBA. The Pennsylvania Small Business Association and Carnegie Mellon have both recognized him as "Entrepreneur of the Year". Stephen has appeared on CNN and is a featured speaker at various conferences and universities.

Keynote: Putting IBM Watson to Work

 Brett Goldstein

Brett Goldstein

Chief Data Officer

City of Chicago

Before coming to City Hall as Chief Data Officer, Brett Goldstein founded and directed the Chicago Police Department's Predictive Analytics Group, which aims to predict when and where crime will happen. Goldstein is a former Commander in the Chicago Police Department. Previously, Goldstein was an early employee with OpenTable. He earned his Bachelor's degree from Connecticut College, his MS in criminal justice at Suffolk University, and his MS in computer science at University of Chicago. Brett is pursuing his PhD in Criminology, Law and Justice at the University of Illinois-Chicago. He resides in Chicago with his wife and two children.

Keynote: Lessons from Year 2: Operationalizing the Principles of Predictive Analytics

 Robert Gottel

Robert Gottel

Reliability Centered Maintenance Manager

TTX

Robert Gottel has been in the rail industry for 35 years. He worked at Electro-Motive in quality, reliability and system engineering. Gottel has a bachelor's degree in mechanical engineering from Valparaiso University, a master's degree in operations research from Illinois Institute of Technology and a master's degree in engineering management from Northwestern University.

Case Study: Predicting Wheel Failure Rate for Railcars

 Greg Green

Greg Green

Director of Agency Strategy

Google

Greg is currently Global Director of Agency Strategy within Google's Agency team, focused on enhancing Google's value proposition to Agencies. In this role, Greg works closely with Sales, Product and R&D teams on critical Agency programs such as Insights for Media Planning, ROI and Media Mix, Media Analytics and Budget Allocation tools.

Greg was previously EVP, Managing Director, VivaKi Nerve Center and SVP, Global Head of Analytics at Digitas, both part of Publicis Groupe. Greg's career also includes other leadership positions in Marketing Analytics as the Chief Strategy Officer at The Allant Group as well as leading the private sector business analytics initiative at Price Waterhouse, as a Principal Consultant.

Case Study: Power of Prediction in an Unpredictable World

 Robert  Grossman

Robert Grossman

Partner

Open Data Group

Robert Grossman is a Partner at Open Data Group, which specializes in building predictive models over big data. He is also the Director of the Laboratory for Advanced Computing (LAC) at the University of Chicago. The LAC is a leader in big data, predictive modeling, data intensive computing and related areas. He has developed new methodologies in big data and predictive modeling and led the development of new software tools for data mining, cloud computing and data warehousing. Prior to founding Open Data Group, he founded Magnify, Inc. in 1996. Magnify's technology provides data mining solutions to the insurance industry. Grossman was Magnify's CEO until 2001 and its Chairman until it was sold to ChoicePoint in 2005. He was one of the founders of the Data Mining Group, which develops the Predictive Model Markup Language (PMML). PMML is the leading standard for exchanging predictive models.

Case Study: Quickly Identifying Incidents from Twitter Streams

 Fred  Grunwald

Fred Grunwald

Vice President Analytics

New Directions Behavioral Health

Fred Grunwald is the Vice President of Analytics at New Directions Behavioral Health where he manages the Analytics, Reporting and Claims Audit functions. Fred has led numerous Analytics efforts directed at improved outcomes and lower costs in the Behavioral Health market. These include lowering readmissions, increasing HEDIS™ scores, using patient mix to create comparative case rates for facilities, and identifying utilization differences using demographic lifestyle clusters.

Fred has worked in health care for his entire career in both hospitals and payer settings. He has a Master of Business Administration degree from the University of Chicago and an undergraduate degree in Industrial Engineering & Operations Research from the University of Missouri.

Case Study: Deploying Predictive Models In Virgin Waters: Predicting Behavioral Health Readmissions

 Mike  Gualtieri

Mike Gualtieri

Principal Analyst

Forrester Research

Mike's work at Forrester Research is focused on software technology, platforms, and practices that enable application development professionals to deliver faster agility, prescient customer experiences, and breakthrough operational efficiency. His key technology and platform coverage areas are big data predictive analytics, blazing-fast performance best practices, user experience design, and emerging technologies that make software faster and smarter. Mike is also a leading expert on the intersection of business strategy, architecture, design, and creative collaboration.

Mike is a recipient of the Forrester Courage Award for making bold calls that inspire leaders and guide great decisions. He is also the record holder of the most-read Forrester blog post.

Case Study: Big Data Predictive Analytics Solutions

 Matt   Habiger

Matt Habiger

Quantitative Analyst

New Directions Behavioral Health

Matt Habiger is a Quantitative Analyst at New Directions Behavioral Health and President of Presage Economics LLC. He has experience applying data mining and statistical techniques in the retail, banking, nonprofit, political and healthcare sectors. Prior to joining New Directions, Matt taught at several regional universities and worked on credit card analytics at a regional bank. His current focus at New Directions is on exploring the link between behavioral health and medical conditions and partnering with clinical operations to measure program performance.

Case Study: Deploying Predictive Models In Virgin Waters: Predicting Behavioral Health Readmissions

 Monika Heller

Monika Heller

Chief Medical Officer

CogCubed

Monika Heller, M.D. is a graduate of Carleton College and is Adjunct Professor at the University of Minnesota. She is a practicing Child and Adolescent Psychiatrist and a recent graduate of the University of Minnesota. She has practiced in a variety of settings including schools, community outreach programs, and medical/physical rehabilitation units. Dr. Heller believes in a multidisciplinary treatment approach to mental health.

Case Study: Videogames for Diagnosis: Predictive Executive Functioning Models Using Interactive Devices

Dr.  Thomas  Hill

Dr. Thomas Hill

Vice President of Analytic Solutions

StatSoft, Inc.

Thomas Hill is Executive Director for Analytics at Dell's Information Management Group. Tom joined Dell through Dell's acquisition of StatSoft (www.StatSoft.com) in April 2014, where he held the role of VP for Analytic Solutions for over 20 years. He is now responsible for guiding the integration and development of innovative end-to-end solution leveraging the breadth and depth of Dell's capabilities.

Tom received his Vordiplom in psychology from Kiel University in Germany, and earned a Masters degree in Industrial Psychology and a Ph.D. in Psychology and Quantitative Methods from the University of Kansas. He was Associate Professor at the University of Tulsa from 1984 to 2009, where he taught data analysis and data mining courses. As Vice President for Analytic Solutions at StatSoft, Tom has been involved for over 20 years in the development of data analysis, data and text mining algorithms, and the delivery of analytic solutions.

He has received numerous academic grants and awards from the National Science Foundation, the National Institute of Health, the Center for Innovation Management, Electric Power Research Institute, and other institutions.

He has completed diverse consulting projects with companies from practically all industries, and has worked with the leading financial services, insurance, manufacturing, pharmaceutical, retailing, and other companies in the US and internationally, on identifying and refining effective data mining and predictive modeling solutions for diverse applications.

Tom has published widely on innovative applications for data mining and predictive analytics. He is 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), a co-author of Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications (2012), and the forthcoming Practical Predictive Analytics and Decisioning Systems for Medicine (2014). He is also a contributing author to the popular Handbook of Statistical Analysis and Data Mining Applications (2009).

Expert Panel: Big Data for Predictive Analytics

 Kathleen  Kane

Kathleen Kane

Principal Decision Scientist

Fidelity Investments

Kathleen Kane is a Principal Decision Scientist with the Modeling and Analytics Strategy team at Fidelity Investments in Smithfield, RI. The Modeling and Analytics Strategy team works with partners in marketing, distribution and product to answer business questions using statistical data analysis.

Kathleen has more than ten years of data mining experience in the financial services industry. Kathleen received her BA in engineering from Dartmouth College, and her MS from the MIT Sloan School of Management.

Case Study: True-Lift Modeling: Mining for the Most Truly Responsive Customers & Prospects

 Tom Kern

Tom Kern

Risk Modeling Manager

Paychex, Inc.

Tom Kern is a Risk Modeling Manager at Paychex, Inc. Under the Risk Management umbrella, Tom helps to coordinate and execute a wide range of projects centered on predictive modeling, optimizing processes in all departments from sales strategy to internal operations and mitigating risk throughout the company.

Tom joined Paychex in 2012. Prior to Paychex, Tom was a Predictive Modeling Analyst with a large digital marketing agency, servicing major clients in the financial services, insurance, and automotive industries. He holds a MA from Boston University in Applied Statistics, and a BA from Boston University in Applied Mathematics. Tom is a four-time PAW speaker.

Case Study: Collections: Every Penny Counts

 Mahesh Kumar

Mahesh Kumar

CEO

Tiger Analytics

Dr. Mahesh Kumar is the founder and CEO of Tiger Analytics, a boutique consulting company that focuses on applying advanced data analytics in the fields of retail management, social media and online advertising, and e-commerce marketing. Prior to founding Tiger Analytics, Dr. Kumar was on the faculty of the Smith School of Business and Rutgers Business School. Dr. Kumar has conducted research in the areas of data mining and statistical modeling and has successfully applied his research to solve problems related to forecasting, pricing, promotions, and customer segmentation. He has extensive consulting experience with companies such as McKinsey & Company, SAS, JC Penney, Levis, TTX, ProfitLogic, LucidMedia, CompassLabs, BlackArrow and Predictix. Dr. Kumar holds a Ph.D. in Operations Research from MIT, a post-doc in Marketing from MIT Sloan, and a bachelor's degree in Computer Science from the Indian Institute of Technology, Mumbai.

Case Study: Predicting Wheel Failure Rate for Railcars

 Satish  Lalchand

Satish Lalchand

Director

Deloitte Financial Advisory Services LLP

Satish Lalchand is a Director at Deloitte Financial Advisory Services LLP, specializing in advanced analytics & big data , business rules development and modeling. His areas of expertise includes: financial investigations, Enterprise Fraud Management (EFM) and anti-money laundering investigations. He has a master's degree in computer information systems and a bachelor's degree in economics.

Expert Panel: Big Data for Predictive Analytics

 Robert  Lancaster

Robert Lancaster

Solution Architect

Orbitz Worldwide

Rob Lancaster has been in software development for the last 13 years, developing solutions for the travel industry. He is currently a Solutions Architect for Orbitz with a focus on applying predictive analytics to improve the performance of Orbitz hotel systems. He is the organizer of Chicago's Machine Learning meetup group and an organizer for Chicago's Big Data user group

Case Study: Hotel Pricing: Survival Analysis for Cache Time-to-Live Optimization

 Wei Liang

Wei Liang

Risk Modeling Analyst

Paychex, Inc.

Wei Liang, Ph.D., has been a Risk Modeling Analyst in the Modeling & Risk Review group at Paychex, Inc. since January 2011. His work involves analyzing the outcome of regular and strategic business activities, providing insight and assessment for marketing, up-sell, retention and risk-management efforts, creating predictive models to add business intelligence.

With a deep understanding of statistical methods and being well versed in the statistical software such as SAS, R and Stata, Wei plays an important role in the effort for compiling the Paychex American Small Business Index.

He is also highly skilled in methods such as Monte Carlo Simulations and Time Series Analysis. Prior to Paychex, he held post doctoral positions in several universities and conducted research in laser and material science.

Wei holds a Ph.D in Physics from Arizona State University, a B.S. in Physics from Sichuan University in China and a M.A. in Biostatistics from the University at Buffalo.

Case Study: Collections: Every Penny Counts

 KV Nathan

KV Nathan

Senior Manager, Customer Service Analytics Delivery, Global Analytics (GLA)

Hewlett-Packard Company

KV Nathan with closer to three decades of knowledge assimilated experience has pioneered the Supply Chain, Process Transformation, Analytics Delivery, Project Management and People Management across Singapore and India.

KV Nathan is the Senior Delivery Manager, Global Analytics at Hewlett-Packard Company and is responsible to create Analytics capability in Warranty and Customer Service Domain. As part of this role, KV Nathan is responsible for delivery of analytics related to customer service and warranty within Global Analytics.

Before this, Nathan was part of HP Singapore holding APJ role and has executed numerous process improvement projects for cost savings in Supply Chain, Logistics, Returns Management , Quality management ,Customer support and Warranty.

Prior to HP, Nathan was holding the position of Project and Quality Manager in one of the leading Power Company in India and shifted to Oil & Gas Manufacturing Sector in Singapore. He transformed the Process Systems and was solely responsible for getting ISO 9001: 1994 Certifications for the Oil & Gas Company in Singapore.

Nathan has graduated from Faculty of Engineering and Technology of Annamalai University, India. He has obtained a Lead ISO Auditor, Six Sigma trained and Consultant of SAP S&D Module.

Nathan possesses a clear understanding of the Supply Chain & Warranty industry, technology trends with the distinction of instituting new practices to achieve superior business excellence at the lowest overall cost.

Case Study: Predictive Modeling of Warranty Non Compliance Detection

 Stephen Omans

Stephen Omans

CEO and Founder

Deal Me Health

Stephen Omans is an experienced healthcare consultant with more than +20 years experience. His extensive knowledge covers revenue cycle, coding, billing, and claims management. His experience also includes researching issues, case management development, claims management systems, billing and coding, physician practices, as well as various provider markets, RAC audits, ICD-9 conversions, cost containment strategy, project management, and staff development.

Case Study: Predicting Provider Reimbursements

 John Pantano

John Pantano

Senior Workforce Analyst

Los Alamos National Laboratory

John Pantano is the Senior Workforce Analyst at LANL and was leader of the Workforce Data and Analysis (WDA) Office from 2006-2009. His current responsibilities include modeling, analysis and reporting that support lab wide workforce planning and risk analysis. The workforce analysis and modeling includes the use of multivariable statistical techniques along with various mathematical modeling techniques. The analysis is being utilized here at LANL and within the DOE complex through a collaborative effort with analysts at LANL and LLNL.

Case Study: Modeling Workforce Attrition - A Comparison of Techniques

 Claudia  Perlich

Claudia Perlich

Chief Scientist

Media6Degrees

Since 2010, Claudia Perlich holds the position of chief scientist at Media6Degrees, a startup that specializes at targeted online display advertising. Claudia received her Ph.D. in Information Systems from Stern School of Business, New York University in 2005 and holds additional graduate degrees in Computer Science. Claudia joined the Data Analytics Research group at the IBM T.J. Watson Research Center in 2004 and continued her research on data analytics and machine learning for complex real-world domains and applications. She is the author or 50+ scientific publications and holds multiple patents in the area of machine learning, has won various data mining competitions, best paper awards, and speaks regularly at conferences and other public events.

Case Study: Wallet Estimation for Sales Force Optimization at IBM

 Nalini  Polavarapu

Nalini Polavarapu

Advanced Analytics Lead

Monsanto

Dr. Nalini Polavarapu is an Advanced Analytics and Workflow lead at Monsanto, where she leads a team of data scientists and workflow engineers responsible for design and optimization of process flows implemented in software systems. Her team develops predictive and optimization algorithms leveraging machine learning and operations research techniques to accelerate Monsanto's product development.

Prior to joining Monsanto, Nalini applied machine learning and analytics to advance research in cancer biology and human brain evolution. She also developed text analytics algorithms for CDC. Nalini earned a PhD in Bioinformatics, dual Masters in Computer Science and Bioinformatics from Georgia Institute of Technology in Atlanta, Georgia. Nalini has authored and co-authored several research articles in leading scientific journals and co-authored book chapters on high throughput biomedical data analysis and applications.

Gold Sponsor Presentation: Improving Agriculture with Big Data and Analytics

 Mukund                     Raghunath

Mukund Raghunath

Geography Head

Mu Sigma Inc.

Mukund Raghunath is the Geography Head for Mu Sigma. He has over 11 years of Engineering and consulting experience with a leading telecommunications company and a leading Sales and Marketing Strategy firm in the US. He has helped several Fortune 500 companies in the Pharmaceutical and Healthcare space address a broad range of business issues. He also has extensive experience in product planning, development and management in the telecom sector.

Mukund has a Masters Degree in Computer Science from the University of Illinois and an MBA with honors from the University of Chicago, Graduate School of Business.

Gold Sponsor Presentation: muPDNA - Encoding Intelligence

 Greta Roberts

Greta Roberts

Co-Founder & CEO

Talent Analytics, Corp.

@GretaRoberts

As Co-founder and CEO, Greta is responsible for charting a predictive analytics approach and software platform to solving employee challenges. In addition to her role as CEO, she was elected as The Program Chair for Predictive Analytics World for Workforce and continues as Faculty at the International Institute for Analytics.

Greta brings a unique perspective to solving complex, long-term challenges. This is never more evident in the firm's early direction to use analytics to solve "line of business" challenges instead of "HR" challenges and modeling business outcomes instead of HR outcomes. This approach has lead Talent Analytics recognized leader in predicting employee performance and attrition. Talent Analytics focuses their work on high value, high turnover positions like Sales positions, Bank Tellers, Insurance Agents, Customer Service Reps and Data Scientists; all areas where reduced attrition or increased performance can yield $ millions in bottom line savings or income.

Greta is a sought-out international thought leader, presenter, and author. She has been a multi-year presenter at Predictive Analytics World (PAW), keynoting in 2014 at PAW Toronto, the ADMA Global Forum in Sydney, Australia, the INFORMS Analytics Conference SAP Sapphire. In addition to speaking, she is often quoted in the press in a variety of influential business publications.

Case Study: Using Analytics to Build Your Analytics Bench: Announcing 2012 Analytics Professionals Study Result

 Bill  Romine

Bill Romine

Computer Scientist

Lawrence Livermore National Laboratory

Bill Romine currently works in the Enterprise Modeling group at the Lawrence Livermore National Laboratory where he is involved in data driven management support. Earlier in his career at Livermore he developed analyses of experimental scientific data. Prior to joining the Lab he worked as a pension actuary for consulting firms. His formal academic training includes both mathematics and applied statistics. His current interests include the application of data mining techniques to problems in the social sciences.

Case Study: Modeling Workforce Attrition - A Comparison of Techniques

 Kurt  Roots

Kurt Roots

Founder & CEO

CogCubed

Kurt Roots started his first company, which provided web analytics, while in high school. He holds an M.B.A. and M.S. in Software Engineering and M.S. in Information Systems. In graduate school at Iowa State University, he did research in machine learning and data mining. After spending five years at Oracle, he worked at an innovative software firm devoted to predictive retail optimization solutions, before moving on to management consulting and other ventures. Kurt grew up with two brothers, one who is autistic. Mike has an extremely rare chromosomal disorder called Monosomy 9p and with only a few hundred cases diagnosed worldwide, it has taught Kurt what it means to be unique.

Case Study: Videogames for Diagnosis: Predictive Executive Functioning Models Using Interactive Devices

 Eric Siegel, Ph.D.

Eric Siegel, Ph.D.

Founding Chair

Predictive Analytics World

The president of Prediction Impact, Inc., author of the acclaimed book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Executive Editor of the Predictive Analytics Times, and the founder of Predictive Analytics World and Text Analytics World, Eric Siegel is an expert in predictive analytics and data mining and a former computer science professor at Columbia University, where he won the engineering school's award for teaching, including graduate-level courses in machine learning and intelligent systems - the academic terms for predictive analytics. After Columbia, Dr. Siegel co-founded two software companies for customer profiling and data mining, and then started Prediction Impact in 2003, providing predictive analytics services and training to mid-tier through Fortune 100 companies.

Dr. Siegel is the instructor of the acclaimed online training program, Predictive Analytics Applied. He has published over 20 papers and articles in data mining research and computer science education and has served on 10 conference program committees.

Keynote: The Prediction Effect, the Data Effect, and the Persuasion Effect

 Paul Sill

Paul Sill

Principal and Founder

Forum Analytics

Mr. Sill began his career in 1994 working in the real estate research department at Blockbuster Entertainment in Fort Lauderdale, FL helping to develop a sales forecasting tool in a geospatial environment during the peak of their global store expansion. From there he moved further into retail data mining at Sears Roebuck and Co. during the Softer-Side retail resurgence and developed a wide variety of forecasting models for a number of their off-mall concepts.

In 2001, Mr. Sill founded Forum Analytics to build upon his experience combining complex analytics with cutting edge mapping technology. In 2007, Forum conducted a successful round of private financing for its continued expansion and has since introduced numerous industry changing platforms, most notably the Strategic Integrated Mapping and Modeling System (SIMMS), Cannibalytics, and the VEXRAY site filtering module.

Mr. Sill holds a Master of Science in Geography and was an Adjunct Professor of Geography at Northern Illinois University for a number of years. He has taught retail analytic coursework at the Wharton School of Business at the University of Pennsylvania, on behalf of the International Council of Shopping Centers, and has spoken at numerous national conventions on retail and research related topics.

Expert Panel: Big Data for Predictive Analytics
Gold Sponsor Presentation: Leveraging 'Analytics as a Service' to develop consumer oriented market expansion strategies utilizing advanced sales forecasting models.

 Larry Simon

Larry Simon

Co-Founder

Managed Analytic Services Inc.

Larry Simon is a management consultant, part-time faculty member of the University of Toronto and a co-founder of Managed Analytic Services.

Larry was formerly a Senior Vice President of Ernst & Young Consulting and the CIO for Capgemini Canada. He has worked with senior management in a broad range of industries to improve the quality of their information and more effectively employ analytic techniques.

For over a decade he was also on the board of the Canadian Information Productivity Awards during which time he evaluated some 2,000 significant information management projects in terms of their measureable business value, giving him unique insight into the reality of information economics.

Larry is currently co-developing a curriculum in Management of Big Data Analytics for the University of Toronto focusing on meeting the demand for managers who can translate analytical results into business language and action.

Case Study: Filling the (Other) Knowledge Gap - Helping Analysts Communicate and Senior Management Comprehend

 John  Sipple

John Sipple

Senior Data Scientist

Sphere of Influence, Inc.

John Sipple is a Senior Data Scientist at Sphere of Influence, Inc. , currently working on multiple advanced machine learning solutions for the government and commercial clients. John has seven years experience working on machine learning on various topics ranging from missile defense to social media. He has earned bachelors and masters degrees from the University of Minnesota and Harvard University. He is working on a PhD in Computer Science in Machine Learning at the George Washington University.

Case Study: Predicting the Future Value of Automobile Service Customers

 Jim  Tesiero

Jim Tesiero

Principal Mathematician, Head of Data Science

Zeeto Media

Mr. James Tesiero, Principal Mathematican and Head of Data Science at Zeeto Media, has over 20 years of experience in data analysis and predictive modeling. Jim earned his B.A. in Physics from Syracuse University in 1985, and his M.S. and A.B.D. from the University of Maine with a concentration in Statistical Mechanics. He has created, designed, and built mathematical models for recommendation systems, search engines, tracking and detection defense systems, mortgage risk, and noninvasive medical devices. His primary research interests is the study of interactions in complex syatems, dimensional reduction in high dimensional sparse data sets, and predictive modeling.

Case Study: Graph Theoretic Ensemble Method for Targeted Advertising Revenue Maximization

 Marco Vriens

Marco Vriens

Senior Vice President

The Modellers LLC

Dr. Vriens has led analytics, research and insights teams at Microsoft, GE Healthcare, and at various marketing research firms. He has consulted many organizations as an outside consultant or as a manager within firms in a variety of industries. His insights contributed to tackling emerging new competitors, increasing marketing efficiency and customer satisfaction, and significantly increased acceptance and usage of customer and marketing insights. He has published articles in many leading academic journals such as Journal of Marketing Research, Marketing Science and numerous papers in industry magazines. He is the co-editor of the Handbook of Marketing Research, Sage Publishing (2006). This handbook won the 2006 Outstanding Title Award. His new book The Insights Advantage: Knowing How to Win will appear in 2012.

Case Study: Predictions At Work: Tools for Decision Support

 Kelly Zhao, Ph.D.

Kelly Zhao, Ph.D.

Credit Risk Analytics Manager

Fifth Third Bank

Dr. Kelly Zhao is a Credit Risk Analytics Manager at Fifth Third Bank. She has over seven years of management experience in experience in Credit Risk Management, Economic Capital Analysis, Advanced Predictive Modeling, Segmentation, Simulation, Credit Bureau data management. Her work includes developing, implementing and validating risk models across the entire credit lifecycle and for a variety of consumer loan products. Lead a variety of analytic projects, including quantitative analysis of score policies such as setting cutoffs, designing strategies for model use, and use of statistical models to aid in the pricing of loans and forecasting of credit losses.

Prior to Fifth Third Bank, Dr. Zhao held Statistical Analysis Manager positions in JPMorgan Chase. She managed statistical modeling and analytics to support credit risk, marketing, underwriting, portfolio management and collection at customer level. Realize benefits of using enterprise wide data. Dr. Zhao holds a Ph.D. in Economics from Louisiana State University.

Case Study: Modeling Practice of Risk Parameters for Consumer Portfolio

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