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Speakers Predictive Analytics World Boston 2014
 Dean Abbott

Dean Abbott

Chief Data Scientist

Abbott Analytics

@deanabb

Dean Abbott is President of Abbott Analytics and currently is the Bodily Bicentennial Professor in Analytics at UVA Darden School of Business. He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience solving a wide range of private and public sector problems. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013).

Session: Data Preparation from the Trenches: 4 Approaches to Deriving Attributes
Workshops: Supercharging Prediction: Hands-On with Ensemble Models
Advanced Methods Hands-on: Predictive Modeling Techniques

 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: Improving Customer Retention & Profitability

 Charles Berger

Charles Berger

Sr. Director, Product Management, Data Mining and Advanced Analytics

Oracle

Charlie Berger is Sr. Director of Product Management, for Data Mining and Advanced Analytics at Oracle. He has over 30 years of experience in data analysis software including Oracle, Thinking Machines Corporation, Bolt, Beranek and Newman, Palladian (expert systems), Automatix (robotics and machine vision), Honeywell Computers and IBM. He is responsible for product management and direction of Oracle's in-databases' data mining and predictive analytics technology including data mining, text mining and SQL based statistical functions. He holds a MS in Manufacturing Engineering and an MBA both from Boston University. He holds a BS in Industrial Engineering and Operations Research from the University of Massachusetts at Amherst.

Session: Oracle's Internal Use of Data Mining and Predictive Analytics

 Richard Boire

Richard Boire

President

Boire Analytics

Richard Boire's experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics. 


His initial experience at organizations such as Reader’s Digest and American Express allowed  him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models which targeted the acquisition of new customers based on return on investment.


With this experience, Richard formed his own consulting company back in 1994 which is now called the Boire Filler Group, a Canadian leader in offering  analytical and database services to companies seeking solutions to their existing predictive analytics or database marketing challenges.


Richard is a recognized authority on predictive analytics and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. This expertise has evolved into international speaking assignments and workshop seminars in the U.S., England, Eastern Europe, and Southeast Asia. 


Within Canada, he gives seminars on segmentation and predictive analytics for such organizations as Canadian Marketing Association (CMA), Direct Marketing News, Direct Marketing Association Toronto, Association for Advanced Relationship Marketing (AARM) and Predictive Analytics World (PAW).  His written articles have appeared in numerous Canadian  publications such as  Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics, data mining and database marketing at a variety of institutions across Canada which include University of Toronto, George Brown College, Seneca College, and currently Centennial College. Richard was  Chair at the CMA's Customer Insight and Analytics Committee and  sat on the CMA's Board of Directors from 2009-2012. He has chaired numerous full day conferences on behalf of the CMA (the 2000 Database and Technology Seminar as well as the  2002 Database and Technology Seminar and the first-ever Customer Profitability Conference  in 2005. He has most recently chaired the Predictive Analytics World conferences in both 2013 and 2014 which were held in Toronto.


He has co-authored white papers on the following topics: "Best Practices in Data Mining" as well as "Customer Profitability:  The State of Evolution among Canadian Companies."  In Oct. of 2014, his new book on "Data Mining for Managers-How to use Data (Big and Small) to Solve Business Problems" was published by Palgrave Macmillian.  In March of 2016, Boire Filler Group was acquired by Environics Analytics where his current role is senior vice-president of innovation.

Session: Embedding Predictive Analytics Within the Corporate Culture-What are the Challenges in the Big Data World?

 Field Cady

Field Cady

Senior Data Scientist

Think Big Analytics

Field is a senior data scientist at Think Big Analytics where he consults with clients on a range of verticals. He believes that good-quality software is critical for a successful, low-stress data science project.

Field graduated from Stanford University with a BS in Physics and Mathematics, and received an MS in Applied Mathematics from the Univsersity of Washington and an MS in Computer Science from Carnegie Mellon University.

Session: Python for Data Science

 Madhav Chinta

Madhav Chinta

Director, Data Science Product Development

Citrix Data Science

Bio is forthcoming!

Session: Predicting Customer Experience Risk in B2B World

 Sameer Chopra

Sameer Chopra

Chief Analytics Officer

Orbitz Worldwide

Sameer Chopra is Chief Analytics Officer (CAO) at Orbitz Worldwide, Inc., a leading global online travel company. He has almost 20 years of experience in applying data mining and predictive analytics across various business domains at both Fortune 500 firms and startups.

Before joining Orbitz, Sameer was in the senior leadership team of Intuit’s Small Business Group (SBG) where he led Marketing Analytics and Web testing. Prior to Intuit, Sameer was with eBay for many years where he served as Director of Analytics - working across different areas such as Internet Marketing, Fraud Detection, Global Site Experimentation etc. Sameer holds a Master’s degree in Operations Research from the Massachusetts Institute of Technology (MIT). He holds an undergraduate degree (Summa Cum Laude) in Mathematics with a minor in Computer Science from Allegheny College, where he graduated valedictorian.

Keynote: Blackjack Analytics: A Surprising Teacher from Which All Businesses Can Learn
Expert Panel: Necessary Skills of the Quant: Finance, Fraud, and Marketing

 Tyler Deutsch

Tyler Deutsch

Graduate Student and Senior Consultant

Northwestern University and Sagence

Tyler Deutsch is a Senior Consultant with Sagence and has over five years of consulting experience helping Fortune 500 clients in the financial services, retail, and healthcare industries in the application of analytics to discover new insights, shorten time-to-value, and drive competitive advantage.

Tyler holds a Bachelor of Science studying Operations Management and Management Information Systems from the University of Dayton, and is completing a Master of Science degree in Predictive Analytics from Northwestern University.

He is based in Chicago, IL and is a member of the Chicago Chapter of the American Statistical Association.

Session: A Fresh Look at the Effects of Promotion on Baseball Attendance Using Hierarchical Bayesian Analysis

 Pinar Donmez

Pinar Donmez

Chief Data Scientist

Kabbage, Inc.

Pinar is a data scientist with a keen focus on finding meaning in data, and turn the insights into data-driven businesses. As the Chief Data Scientist at Kabbage, she is passionately transforming raw data into valuable knowledge to improve underwriting for SMBs and help them succeed.

She is leading a world-class team of data scientists in turning unusually rich data sources on how a business operates into predictive systems that can determine the risk, capacity, and character of the business. Kabbage uses this data-driven technology to lend over $1million per day.

Prior to Kabbage, she applied her data and machine learning skills to attrition prediction and sales propensity estimation at Salesforce's Data and Analytics team, and user intention understanding through her work at Yahoo! Labs which led to patents and numerous publications.

Pinar holds a Ph.D. In Computer Science from CMU, where her main interest lied in machine learning.

Session: Data Science Approach to Small and Medium Business Lending

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.

Session: Special Plenary Session : The Power (and Peril) of Predictive Analytics

 John Foreman

John Foreman

Chief Data Scientist

MailChimp.com

John Foreman is the Chief Data Scientist at MailChimp.com, an email marketing service. John's main focus is MailChimp's Email Genome Project, which analyzes millions of email lists - and hundreds of millions of email addresses - to find stories and trends in the data. This research helps MailChimp understand the email ecosystem, prevent abuse, and create better experiences for everyone.

Keynote: Problems, then Techniques, then Toys. Keeping Your Predictive Analytics Right-side Up

 Kleber Gallardo

Kleber Gallardo

Consultant

Alivia Technology

Kleber Gallardo is a consultant working with the Massachusetts Office of the State Auditor developing its data mining and data analytics capacity. In 2009, he founded Alivia Technology, an IT service company that focuses on big data projects that delivers high performance, high quality, and scalable systems across a variety of platforms and industries.

Over the last 20 years, Gallardo has honed his craft, gained invaluable insight and knowledge, as well as practical experience by building high performance trading and back office analytic systems and approaches for many major financial institutions across multiple currencies and languages.

In his prior position, he was a founder and chief technology officer of Bonaire Software Solutions. He was responsible for the development and deployment of the number one billing system in the world for asset managers. The system is used by over 115 banks and over $5 trillion dollars are billed through the system

Session: Risk Analytics Engine at State Auditor's Office

 Aliza Heching

Aliza Heching

Research Scientist

IBM Thomas J. Watson Research Center

Dr. Aliza Heching is a research scientist in the business analytics and mathematical sciences group of the IBM Thomas J. Watson Research Center. Since joining IBM in 1998, Aliza has worked with internal IBM divisions and external clients to develop analytical models to solve business problems.

Aliza current research focuses on service operations and understanding how different factors, including work environment, social, and cultural, impact agent performance.Aliza received her doctoral degree in Management Science/Operations Research from Columbia University Graduate School of Business, NY, NY.

Aliza has filed numerous patents and has received three IBM Outstanding Technical Achievement Awards and several IBM Research Division Awards for inventions and technical accomplishments. Aliza has published a number of papers and book chapters, regularly collaborates with academics, and frequently presents at conferences.

In 2013 she received a prestigious recognition as a Master Inventor.

Session: Data-Driven Transformation in End-to-End Sales Transaction Support

 Josh  Hemann

Josh Hemann

Director - Analytic Services

Activision

Josh Hemann is a Principal Statistician in Activision’s Game Analytics Team, where he builds analytic services that support video game development studios. His industry experience in analytics spans diverse settings such as oil and gas exploration, aerospace, retail loyalty programs, recommendation systems for grocers, and massively multiplayer on-line games. Throughout these settings he has appreciated how much effective visual communication is critical for influencing decisions made by scientists and executives alike. Josh has an MS in Applied Mathematics from the University of Colorado at Boulder where he maintains involvement in air pollution research.

Session: Cheating Detection in Call of Duty

 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)."

Expert Panel: Necessary Skills of the Quant: Finance, Fraud, and Marketing

 Jeff Kosseff

Jeff Kosseff

Privacy and Communications Attorney

Covington & Burling, LLP

Jeff Kosseff, CIPP/US, is a privacy and communications associate in the Washington, D.C. office of Covington & Burling, LLP. He clerked for Judge Milan D. Smith, Jr. of the U.S. Court of Appeals for the Ninth Circuit and Judge Leonie M. Brinkema of the U.S. Court of Appeals for the Eastern District of Virginia.

He is an adjunct professor of communications law at American University, and serves on the board of directors of The Writer's Center.

Before becoming a lawyer, he was a journalist for The Oregonian and was a finalist for the Pulitzer Prize and recipient of the George Polk Award for national reporting.

Session: Predictive Analytics and Privacy by Design

 Steve Krawciw

Steve Krawciw

CEO and Head of Institutional Sales

Able Markets

Steve Krawciw is CEO and Head of Institutional Sales of Able Markets.. Mr. Krawciw is also responsible for the overall strategy of the firm. He is an experienced Product Development Executive with a proven track record of identifying opportunities for new lines of business and implementing distribution into selected clients segments. Steven's experience spans global wealth managers, start-ups and Fortune 500 organizations.

Over the course of his career, Krawciw has managed private banking products and advised executives, heads of multinational companies, and government leaders while working for CIBC Wealth Management, McKinsey and Co., and Monitor Company. Among his most memorable past projects is facilitating infrastructure development of the South African government of Nelson Mandela.

At Credit Suisse where Steven worked from 2007-2014, he led the Efficiency and Business Analytics team for Private Banking Americas. Steven drove the approval and implementation of a deposit program in Private Banking USA and successfully conceptualized and launched the non-FDIC term deposit program, the third-party FDIC deposit sweep program. This new product category has added $4Bn of assets to PB USA since 2009. He led the deployment of a futures trading platform and launched the feasibility stage of the hedge-fund feeder program. Steven also facilitated a turnaround of the family office at Credit Suisse involving a full review of products and services, customer profitability analysis, and a change in operating model.

Krawciw holds an MBA (Finance) from the Wharton School of the University of Pennsylvania and a B.Comm. with Distinction in economics from the University of Calgary. He is an avid runner, cyclist, and has scaled peaks on four continents. Krawciw lives in New York, NY.

Session: Predictive analytics for Asset Managers

 Scott Lancaster

Scott Lancaster

Vice President

State Street Corp.

Scott Lancaster, a VP at State Street, is part of the Application Development & Maintenance Governance in their IT organization and leads Performance Analytics and Estimation Center of Excellence along with other program management responsibilities.

Prior to his current role he worked in the Basel II PMO using analytics to manage the critical path. Before working for State Street, Scott worked for IBM/Rational as project manager, software services consultant, and technical field sales specialist where he assisted Fortune 500 clients in deploying improved software development and business processes.

Scott began his interest in predictive analytics and estimation over 20 years ago while working for Intel. He has a Bachelor of Science in Computer Science and expects to receive his Master of Science in Predictive Analytics from Northwestern in 2015. He has over 24 years of experience in the technology industry and is a certified Project Management Professional (PMP).

Session: How Can Predictive Analytics Help Avoid $1.2 Million in IT Project Development Costs?

 Jack Levis

Jack Levis

Formerly UPS (retired), now Chief Product Strategist

ESP Logistics Technology

“The future of Logistics is the marriage of Data, Operations Technology, and Advanced Analytics, which will reduce cost and improve services."


Jack Levis is responsible for Product Strategy at ESP Logistics Technologies. This role includes Optimization / Prescriptive Analytics. He is bringing with him 43 years of logistics and technology experience. 


Prior to joining ESP, Jack retired from UPS as a Senior Director of Industrial Engineering. During his 43-year career he was responsible for the development of operational technology solutions including digital twin infrastructure and optimization solutions. These solutions required advanced analytics to reengineer processes, streamline the business, and maximize productivity. 


Jack was the business owner and process designer for UPS’ Package Flow T


echnology suite of systems which includes its award-winning optimization, ORION (On Road Integrated Optimization and Navigation). These tools were a breakthrough change for UPS, resulting in a reduction of 225 million miles driven each year.


ORION alone is providing significant operational benefits to UPS and its customers. UPS estimates that ORION alone is reducing costs by $500M to $600M per year. 


Jack believes ESP can deliver similar gains to its customers. 


Having earned his Bachelor of Arts in psychology, from California State University Northridge, Jack also holds a Master’s Certificate in Project Management from George Washington University. 


He is a fellow of the Institute for Operations Research and Management Sciences (INFORMS), receiving their prestigious Kimball Medal and the President’s Award.


Jack is a frequently requested speaker for business executives and organizations. He has been featured in many publications and media productions including a TED talk and a NOVA show on Innovation. 


Jack has held advisory council positions for multiple universities and associations, including the United States Census Bureau Scientific Advisory Committee. 


The role Jack enjoys the most is Grandpa.

Keynote: UPS Analytics - The Road to Optimization
Expert Panel: Necessary Skills of the Quant: Finance, Fraud, and Marketing

 Pitipong Lin

Pitipong Lin

Senior Technical Staff, Supply Chain Analytics

IBM

Dr. Pitipong JS Lin is a Senior Technical Staff Member (STSM) in Enterprise Services Analytics, IBM Transformation & Operations. His expertise is in operations research, lean sigma and supply chain strategy.He received his M.S. degree in Management from Boston University and Ph.D. degree in Industrial Engineering from Northeastern University, in Massachusetts. Since 1999, he has worked on over twenty projects in IBM Global Business Services supporting internal and external business clients as a senior managing consultant.His speaking experience includes INFORMS, ISSST (aka IEEE Symposium on Electronics and the Environment), INFORMS, and Northeast Decision Sciences Institute. He regularly makes presentations across the organizations in IBM to expand the analytics community and drive business opportunities. He has served as a conference co-chair of IEEE ISSST in 2002, 2003 and 2004. He has published over thirty journal articles and proceedings on the subject of analytics and optimization.

Session: Data-Driven Transformation in End-to-End Sales Transaction Support

 Victor Lo

Victor Lo

AI and Data Science Center of Excellence Leader, Workplace Investing

Fidelity Investments

Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader with over 25 years of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with causal inference and is a pioneer of Uplift/True-lift modeling, a key subfield of data science.


Victor has managed teams of quantitative analysts in multiple organizations. He currently leads the AI and Data Science Center of Excellence, Workplace Investing at Fidelity Investments. Previously he managed advanced analytics/data science teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).


For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University. He has also been serving on the steering committee of the Boston Chapter of the Institute for Operations Research and the Management Sciences (INFORMS) and on the editorial board for two academic journals. He is also an elected board member of the National Institute of Statistical Sciences (NISS). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. He has co-authored a graduate level econometrics book and published numerous articles in Data Mining, Marketing, Statistics, Analytics, and Management Science literature, and is completing a graduate level book on causal inference in business.

Session: Uplift Modeling: Introduction, Applications, Comparisons, and Latest Developments

 Andy  McNalis

Andy McNalis

Sr. Manager - Big Data / Data Warehouse Administration

Sears Holdings Corporation

Andy is Sr. Manager of Big Data / Data Warehouse Administration at Sears Holdings Corporation. Andy is a leading member of the team that builds, deploys and manages an enterprise-scale Hadoop platform at Sears. Part of the Big Data Center of Excellence, Andy is involved in the development of design best practices for Hadoop and production-ready big data environments. Prior to working with Hadoop, Andy spent over seven years as a Data Warehouse Manager at Sears, managing Teradata, Netezza, Greenplum and other data warehouse environments.

Session:Hadoop Use Cases: Speeding Up Data Workloads

 Philip O'Brien

Philip O'Brien

MIS and Portfolio Manager

Paychex

Philip O'Brien is responsible for the predictive analytics program at Paychex Inc., a leading provider of payroll, human resource, insurance, and benefits outsourcing solutions for small- to medium-sized businesses. The predictive analytics team at Paychex has implemented models to help with strategic decisions across all aspects of the business, including effectively targeting retention strategies, assisting in dynamic cross-sell initiatives, improving collection targets for bottom line results, and driving client service progression strategies.

Philip has been with Paychex for 15 years and has served in a leadership capacity within analytics for the past ten years. For well over a decade, Paychex has developed its predictive analytics program and has earned industry recognition for its leadership in the space. The predictive analytics function at Paychex continues to grow and add value across the organization, with more than 20 models divided between four portfolios: Operations, Sales, Risk, and Strategy.

Session: Combat Client Churn with Predictive Analytics

 Gayatri Patel

Gayatri Patel

Director, Analytics Platform Strategy & PM

eBay

Gayatri manages eBay's Data and Analytics Platform Strategy. She is involved in strategic initiatives related to eBay's industry-leading data warehousing systems, map-reduce platforms, analytic products, business intelligence tools, collaboration portals, and fast analytics platforms. She has successfully launched over a dozen enterprise software products at leading organizations, such as Oracle and HP, and having founded an industry-leading complex-event processing (CEP) software company (now part of SAP), Gayatri has thrived for over 25 years on the challenge of matching innovation with high customer impact.

Session: Importance of Speed and Relevance to eBay and Our Big Data Strategies

 Roger Plourde

Roger Plourde

President

Intema Solutions

Roger Plourde contributed to the branding of several mass market retailers (Provigo, Metro...) for several years before seeing the vast marketing potential of the Internet from its early days and becoming one the few pioneers to help Canadian companies invest the digital space.

After having set up several companies in the communications and marketing fields, he transformed Intema, a family startup into a Canadian leader in digital marketing solutions.

Twenty years after pioneering in digital marketing, he is pioneering again by introducing predictive analytics to Email marketing with the Predictive Marketing Engine.

Sessionn: Predictive Analytics to the Rescue of Email Marketing

 Daniel Porter

Daniel Porter

Co-Founder

BlueLabs

Daniel Porter is the cofounder of BlueLabs, a Washington DC based analytics, data and technology company whose clients include political campaigns, nonprofits and corporations.


Prior to founding BlueLabs, Daniel was Director of Statistical Modeling for the 2012 Obama reelection campaign. His team developed individual level statistical models that were used throughout the campaign for fundraising, media buying and state strategy. These models served two primary purposes: to pinpoint which voters were most likely to take an action or hold a belief (i.e. support the President or turn out to vote) as well as to measure the influence a campaign contact had on an individual's likelihood to take such actions or change their beliefs. Combined, these measures helped the campaign optimize their targeting to maximize their return on investment.

Session: Pinpointing the Persuadables: Convincing the Right Customers and the Right Voters

 Madhusudan Raman

Madhusudan Raman

Innovation Incubator

Verizon

Madhu Raman is a practitioner who incubates beachhead market ideas that 'touch' the connected consumer. An alum of the MIT Sloan Executive Strategy & Innovation Program and an Electrical Engineer, Madhu heads Verizon's global ideation incubation services practice based out of their Massachusetts Innovation Center. His innovations include numerous granted or in-process patents leveraging Big Data contextual insight harnessing predictive models, the cloud, consumer social media, and mobility.

Madhu's experience includes establishing a successful Fortune 500 Prototyping Practice for a major startup in the 90's and since 98' co-founding, working in, and with startups as a c-level thought leader and technology board advisor. Ideation pipeline governance, systematic innovation discovery, agile market testing and product tuning leveraging native, open sourced and, acquired intellectual property continue to be a key part of Madhu's current role. He enjoys volunteering in local homeless shelters alongside his family.

Session: Third Generation Contextual Learning as a Service and Consumer Data-Haven Practice

 Jim Regetz

Jim Regetz

Sr Lead, Program Manager, Customer Insights

Citrix Data Science

Bio is forthcoming!

Session: Predicting Customer Experience Risk in B2B World

 Pasha Roberts

Pasha Roberts

Co-Founder and Chief Scientist

Talent Analytics, Corp.

@pasharoberts

Pasha Roberts is chief scientist at Talent Analytics Corp., a company that uses data science to model and optimize employee performance in areas such as call center staff, sales organizations and analytics professionals. He wrote the first implementation of the company’s software over a decade ago and continues to drive new features and platforms for the company. He holds a bachelor’s degree in economics and Russian studies from The College of William and Mary, and a master of science degree in financial engineering from the MIT Sloan School of Management.

Session: Data Science Approach to Reduce Call Center Employee Attrition

 Belinda Rushing

Belinda Rushing

Director - Customer Experience

nTelos Wireless

Belinda Rushing is Director - Customer Experience at nTelos Wireless in Waynesboro, Virginia. Belinda has held a variety of positions in customer service and marketing, always with a focus on driving customer loyalty. In her current role, she leads a team charged with reducing customer effort and increasing customer loyalty through better tools, processes and business intelligence. Belinda is a graduate of the University of Virginia.

Session: Improving Customer Retention & Profitability

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.

 Chris Simokat

Chris Simokat

Vice President - Lead Data Scientist - Big Data & Analytics Engineering

Citi

Bio is forthcoming!

Session: Predicting Hard Disk Device Failure Using Random Decision Forests

 Viswanath Srikanth

Viswanath Srikanth

Senior Program Manager, Analytics

Cisco

Sri (Viswanath Srikanth) is a Senior Program Manager for Cisco’s Digital Strategy and Analytics group. Sri is responsible for driving the Data Science practice within the Digital Group at Cisco. Sri was previously chair of the W3C Customer Experience Data Layer community group, standardizing user behavior data collection for the industry. He is based out of Chapel Hill, North Carolina.

Session: A Fresh Look at the Effects of Promotion on Baseball Attendance Using Hierarchical Bayesian Analysis

 Mike Stringer

Mike Stringer

Group Director

Citrix Data Science

Mike Stringer leads Citrix's Data Science strategy. He has held various leadership positions across Citrix, roles in IT, Services, Sales, Support, and Engineering, including recently leading an internal start-up data product team.

Session: Predicting Customer Experience Risk in B2B World

 John Whittaker

John Whittaker

Executive Director of Marketing

Dell Statistica

John Whittaker is the executive director of
marketing for Dell Software’s Information Management group, where he oversees
marketing activities for a diverse portfolio of solutions spanning database
management, data integration, business intelligence and big data analytics.
Prior to joining Dell, he was the director of product marketing for Quest
Software’s database management business. Whittaker has over 20 years of
experience with a variety of technology companies, including leadership
positions with companies such as AlertSource, Trinent Internet Solutions and
KnowledgeCentrix. His areas of expertise include database management, business
intelligence, advanced analytics, information security, business continuity and
disaster recovery planning and E-Commerce

Diamond Sponsor Presentation: Realizing competitive value in the emerging Data Economy through Big Data Analytics

 May Xu

May Xu

Marketing Analytics Manager

LinkedIn

May is a seasoned analytics practitioner and manager with over 12 years, driving meaningful business impact through thought leadership, deep analytical insight and execution.

Her experience includes both strategic and operational decision support in a wide range of business domain and analytical expertise for Fortune 500 companies such as B2B marketing effectiveness, marketing and sales alignment, online payment flow optimization, e-commerce fraud detection, credit risk management, retailer strategic planning and upstream oil exploration.

Prior to joining LinkedIn she worked in various marketing analytic roles at PayPal, eBay, Wells Fargo, Gap Inc. LinkedIn profile http://www.linkedin.com/pub/may-xu/4/693/bb0

Session: Increasing B2B Marketing Contribution through Optimal Marketing Attribution Analysis Techniques

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