Co-Founder and Chief Data Scientist
Dean Abbott is Co-Founder and Chief Data Scientist of SmarterHQ, 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 of 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).
Session: The Revolution in Retail Customer Intelligence
Q&A Session: Ask Karl and Dean Anything (about Best Practices)
Workshop: Advanced Methods Hands-on: Predictive Modeling Techniques
Workshop: Supercharging Prediction with Ensemble Models
Global Director Analytics & Insights Solutions
Johnson & Johnson
Elena is an analytics and technology leader with a strong track record in building and growing analytics capabilities. She has experience in multiple industries, including telecommunications, healthcare, media, publishing and information services. As Global Director of Analytics and Insights Solutions for J&J Consumer, Elena and her team are responsible for building industry-leading analytics technology capabilities to enable rapid insight generation and decision support through the consistent use of traditional and advanced analytics practices in the commercial domain. Before J&J, Elena led multi-channel analytics capabilities for GSK Pharma, including their global multi-channel analytics platform implementation. Prior to that Elena held analytics, data and technology roles of increasing responsibility at Novartis (agency side) and The Wall Street Journal and Dow Jones & Company.
Session: Analytics at the Speed of Global Business: Delivering an Analytics Technology Platform
Chief Business Officer, 592 LLC
Analytics Instructor, Harrisburg University of Science and Technology
Mr. Feyzi R. Bagirov is the Chief Business Officer (CBO) at 592 LLC and an Analytics Instructor at Harrisburg University of Science and Technology.
Mr. Bagirov has an extensive experience as an online educator, developing and teaching courses on Data Science, Data Analytics, Game Analytics and Data Mining subjects in a number of online undergraduate and graduate programs. He has participated in the creation of the graduate Master of Science in Data Analytics at the University of Maryland University College, and was a Founding Director of an undergraduate program (Bachelor of Science in Data Science) at Becker College.
Mr. Bagirov is a former US Marine. For the past 4 years, Mr. Bagirov worked on various analytical and educational projects and startups in the United States and overseas (Azerbaijan, Tunisia, Senegal and Mozambique). In addition, he is the founder of the Big Data Behavioral Analytics Boston meet-up.
He holds a bachelor's degree in international economics from Azerbaijan University in Baku, Azerbaijan, and an MBA with a focus in entrepreneurship from Babson College in Wellesley, Mass.
Session: Enhancing the Quality of Predictive Modeling on College Enrollment
University Professor of Computer Science
New York University
Anasse Bari (Ph.D.) is data mining expert and a university professor of computer science at NYU who has many years of predictive modeling and data mining experience. Bari has recently worked closely with leadership of the World Bank Group as a data scientist where he was leading the design of enterprise data analytics projects. Bari is the co-author of the book "Predictive Analytics for Dummies", Wiley.
Session:Predicting Changes in Rental Prices in New York City Using Online Restaurant Reviews
In his role as Data Scientist at MapR, Joe assists customers in solving their big data problems, making efficient use of the Hadoop ecosystem to generate tangible results. Recent projects include debit card fraud & breach detection, lead generation from social data, customer matching through record linkage, lookalike modeling using browser history and real-time product recommendations.
Prior to MapR, Joe was the Chief Scientist for Optum (a division of UnitedHealth) and the principal innovator in analytics for healthcare. As a Sr. Fellow with OptumLabs, he applied machine learning concepts to healthcare issues such as disease prediction from co-morbidities, estimation of PMPY (member cost), physician scoring and treatment pathways. As a leader in the Payment Integrity business, he built anomaly detection engines responsible for saving $100M annually in claim overpayments.
Session: Sentiment Unchained: Accelerating Analytics to Understand Customer Behavior
Senior Vice President, Boire Filler Division
Richard Boire, B.Sc. (McGill), MBA (Concordia), is the founding partner at the Boire Filler Group, a nationally recognized expert in the database and data analytical industry and is among the top experts in this field in Canada, with unique expertise and background experience. Boire Filler Group was recently acquired by Environics Analytics where I am currently senior vice-president.
Mr. Boire's mathematical and technical expertise is complimented by experience working at and with clients who work in the B2C and B2B environments. He previously worked at and with Clients such as: Reader's Digest, American Express, Loyalty Group, and Petro-Canada among many to establish his top notch credentials.
After 12 years of progressive data mining and analytical experience, Mr. Boire established his own consulting company - Boire Direct Marketing in 1994. He writes numerous articles for industry publications, is a well-sought after speaker on data mining, and works closely with the Canadian Marketing Association on a number of areas including Education and the Database and Technology councils. He is currently the Chair of Predictive Analytics World Toronto.
Session: Developing an Analytics Discipline in Recognizing Model Overstatement
Sr. Director, Product Management & Analytics
Bob Bress is Senior Director of Product Management and Analytics at Visible World. In that role he has applied his expertise in data and analytics to lead development of the next generation of advanced targeted advertising products for television. Bob has over 15 years of business analytics experience including work in the energy industry, providing advanced analytics services for innovative demand-side energy programs and at GE’s Global Research Center in the Applied Statistics Lab where he worked on cutting edge statistical applications for a variety of GE businesses. Bob holds undergraduate and graduate degrees in Industrial Engineering and Operations Research & Statistics from Rensselaer Polytechnic Institute.
Session: What Shall I Watch Now? Ensuring the Right TV Ads Are in Front of the Right Audiences
Global Asst. Vice President of Data Science
Matthew is currently the Global Asst. Vice President of Data Science for Citibank who focuses on Big Data and Data Science across geographies and businesses. Working both directly for banks and as a consultant, Matthew has spent his career pushing the envelope in practical uses cases such as marketing, operational analytics, and outlier analysis.
Session: Graph Database for complex problems - Creating Personalized Food Item Recommendations at Restaurants
Senior Architect Research Scientist
Michael Cole is a research scientist at LexisNexis in New York City. He received a Ph.D. in Information Science from Rutgers University where he did research on information search personalization. That research focused on the information seeking process and representing the user's experience of search to support the development of systems that can learn to cooperate with searchers. At LexisNexis he is working at the intersection of information science, cognitive science, machine learning, and AI to bring cognitively-centered design into next-generation information retrieval systems.
Session: Predicting the Fate of Legislative Bills and Finding Effective User Analytics for Business Decision Making
Lawrence is a Partner at the Cicero Group, a leading data-driven strategy consulting firm located in Salt Lake City, UT. Lawrence has spent the last eight years building Cicero's analytics practice where he has experience helping Fortune 500 firms solve real business challenges with data, including attrition, segmentation, sales prioritization, pricing, and customer satisfaction. Lawrence is also an expert in choice modeling (choice-and menu-based conjoint), having successfully deployed and implemented more than 50 studies in his career at Cicero, relying upon Hierarchical Bayesian and Latent Class analysis to derive accurate market based scenarios. Lawrence holds a Master's of Science in Predictive Analytics from Northwestern University, an MBA with an emphasis in Business Economics from Westminster College, and a BA from Brigham Young University.
Session: Maximizing Net New Deposits of a Promotional Email Campaign with Predictive Analytics
Professor, Stern School of Business & Center for Data Science, NYU
Editor-in-Chief, Big Data journal
Vasant Dhar is Professor at the Stern School of Business and the Center for Data Science at NYU. He is also Editor-in-Chief of the Big Data journal. For the last 20+ years, a core part of Professor Dhar's research has addressed the following question: when do computers make better decisions than humans? His June 2015 editorial in Big Data answers this question in the financial arena, namely, Should You Trust Your Money to a Robot? Dhar's created the Adaptive Quant Trading (AQT) program in 2009, a data-driven learning machine that trades the world's most liquid futures contracts systematically for institutional investors. He has written over 100 research articles and dozens of opinion editorials in media including the Financial Times, Wall Street Journal, Forbes, and Wired Magazine.
Session: When Should We Trust Robots with Decisions?
Dr. John Elder
CEO & Founder
John Elder leads America's most widely experienced Data Science consultancy. Founded in 1995, Elder Research (www.elderresearch.com) has offices in Charlottesville VA, Washington DC, Baltimore MD, and Raleigh NC. The team has solved problems in investments, business, and science by analyzing data in tables, text, and links. Dr. Elder co-authored 3 books (on data mining, ensembles, and text mining), two of which won "book of the year" awards in Mathematics or Computer Science. John has created analytics tools, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. Dr. Elder earned Engineering degrees from Rice and UVA and is an Adjunct Professor of Systems Engineering at UVA. He was honored to be named by President Bush to serve 5 years on a panel to guide technology for national security.
Special Plenary Session: Doing Space-Age Analytics with Our Hunter-Gatherer Brains
Expert Panel: Data Prep: Overcoming the Bottleneck and Nailing It
Workshop: The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and Common Data Mining Mistakes
Associate Department Head, Applied Software Engineering
The MITRE Corporation
Richard F. Eng is the Associate Department Head of Applied Software Engineering at the MITRE Corporation. He is an adjunct professor of the Computer Science and Software Engineering at Monmouth University. He has over 25 years of industry experience in telecommunications and software systems. His areas of interest are quantitative methods to improve business, IT processes, and software quality. He is a frequent speaker on quality improvement and data analytics. Richard is an ASQ Certified Software Quality Engineer, Reliability Engineer, and Quality Engineer. He is a certified Projects in Controlled Environments (PRINCE2) Practitioner and a PMP. Richard earned a M.S. in Data Analytics from the University of Maryland. He graduated from Georgetown University with an MBA. Richard graduated from Brooklyn Polytechnic Institute with a M.S. in Bioengineering and B.S. in Chemistry.
Session: Applying Machine Learning Techniques to Improve Quality
Chief Data Officer
Usama M. Fayyad, Ph.D. is Group Chief Data Officer at Barclays in London where his responsibilities include building and delivering the data infrastructure for BI, data warehousing, BigData and analytics/insights technologies across the Barclays Group globally as well as data governance, and enterprise Data Architecture. He also took on an additional role at Barclays as CIO of Risk, Finance, and Treasury Technology. He is Chairman of Oasis500 in Jordan following his appointment in 2010 by King Abdullah II of Jordan to be the founding Executive Chairman. Oasis500 a tech startup investment fund that runs an accelerator, entrepreneurship training program, and angel investment network aiming to fund 500 Internet and Technology startups in the MENA Region. From 2011-2013 he served as Chairman & CTO of BlueKangaroo, a mobile search engine to help consumers benefit from the vast offers environment that is difficult to search and benefit from. 2008: founded Open Insights: data strategy/technology firm to help enterprises develop data strategy & BigData solutions to effectively grow revenues. 2004-2008: Yahoo!'s chief data officer & Executive VP of Yahoo!'s global BigData systems/policies & data scientist group using Big Data for content/ad targeting: growing Yahoo! revenues from targeting by 20x in 4 years while processing 25+ Terabytes of data/day. Founder of Yahoo! Research Labs: the premier scientific research organization to develop the new sciences of the Internet.2003: co-founded/led DMX Group, a data mining/data strategy company -- acquired by Yahoo! in 2004. In early 2000: co-founder/CEO of Audience Science (digiMine, Inc.) the leader in Behavioral Targeting & ad networks.1995-2000: led Data Mining & Exploration group at Microsoft Research, built data mining products for Microsoft's server division. From 1989-1996: held a leadership role at NASA's JPL in analysis of Big Data in Science earning him the top research excellence award from Caltech, as well as a U.S. Government medal from NASA.Fayyad's Ph.D. in engineering is from the University of Michigan, Ann Arbor (1991). He holds BSE's in both EE & CSE (1984); MSE in CSE (1986); and M.Sc. in mathematics (1989). He published over 100 technical articles, holds over 30 patents. A Fellow of AAAI (Association for Advancement of Artificial Intelligence), Fellow of ACM (Association of Computing Machinery), editor two influential books on data mining; Founding editor-in-chief of primary scientific journal in field (Data Mining and Knowledge Discovery) and of SIGKDD Explorations Newsletter, Chairman of ACM SIGKDD which runs the world's premiere data science, big data, and data mining conferences: KDD. He is an active angel investor in U.S., EU and Middle East specializing in early-stage tech companies.
Special Plenary Session: The Rapidly Changing Big Data Landscape: Balancing the Power with the Dangers of Confusion
Matt Flynn is Sr. Director of the Science Department at AIG. He has been active in analytics and modeling in financial services, primarily Property & Casualty Insurance for a number of years. He has been active participant and presenter in both industry and software conferences for a number of years. He enjoys model building in SAS and R.
Session: Parametric Uplift Regression Models
Manager, Advanced Analytics
Miles & More GmbH
Alexander Funkner has been with Miles & More since 2012 in his role as Manager Advanced Analytics. In this function he is responsible for target group selections and the analysis of the implementation and the performance measurement of direct marketing campaigns. In this context he is dealing with the development of models to predict customer interests and behavior in order to improve marketing communication in terms of efficiency, target orientation and relevance. He discovered his deep interest for data analytics while studying Business Mathematics and writing his Master Thesis from a practical perspective with SCHUFA Holding AG.
Session: Using Predictive Models for Demand Simulation - Purchase, Response and Uplift Modeling in Practice
Chip Galusha is a data scientist at Paychex Inc., a leading provider of integrated human capital management solutions for payroll, HR, retirement, and insurance services. As a member of the data science and predictive analytics team, Chip harnesses the power of big data and statistical modeling to provide data driven intelligence that enhances strategic decision making. Chip has spent the greater part of the last 10 years working with data in a variety of fields, from e-commerce to public health. This has helped him develop a full view of data driven solutions, from ETL processes through model deployment. He holds a Master of Science in Statistics from the University of Vermont.
Session: Predicting Employee Churn with Anonymity
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.
Session: Five Best Practices for Deploying Analytic Models into Operations and Five Common Mistakes
Dominique Haughton, PhD
PhD Professor of Mathematical Sciences
Dominique Haughton (PhD MIT 1983) is Professor of Mathematical Sciences and Global Studies and Graduate Coordinator for Business Analytics at Bentley University in Waltham, Massachusetts, near Boston, and Affiliated Researcher at the Université Paris 1 (Pantheon-Sorbonne) and Université Toulouse 1, France. Research interests include applied statistics, business analytics, global analytics, music analytics, data mining, and model selection. Professor Haughton's work concentrates on how to best leverage modern analytics techniques in order to address questions of business or societal interest. United States co- Editor of Case Studies in Business, Industry and Government Statistics (CSBIGS). Author of three monographs, a Springer brief, and of over sixty articles which have appeared in journals such as The American Statistician, Computational Statistics and Data Analysis, Journal of Interactive Marketing, Telecommunications Policy, Economic Development and Cultural Change, Studies in Family Planning, Journal of Population Economics, Journal of Biosocial Science, Annals of Statistics, Sankhya, Journal of Statistical Computation and Simulation, Communications in Statistics, Statistica Sinica. Ecole Normale Superieure Graduate. Fellow of the American Statistical Association.
Session: Causality in Business Analytics: Uplift Models and Directed Acyclic Graphs
Associate Director Advanced Analytics
Miles & More GmbH
Thomas Klein is Associate Director Advanced Analytics at Miles & More, Europes leading frequent flyer and loyalty program. He is heading a team responsible for turning data into insights, knowledge and actions to create better customer experiences and optimize multichannel marketing campaigns. Thomas studied sports and computer science at the TU Darmstadt and likes to think and act in an interdisciplinary manner to develop creative solutions to complex problems.
Session: Using Predictive Models for Demand Simulation - Purchase, Response and Uplift Modeling in Practice
Digital Strategist & Analyst
Rita is the Digital Strategist and Analyst of The Hive
, a special project unit at USA for UNHCR. She is currently leading the application of data science to tackle one of the most pressing humanitarian crises today, the global refugee crisis. Rita uses predictive data to develop new ways of engaging Americans through unconventional digital engagement and acquisition projects.
Session: The Data Set You Can No Longer Ignore: Consumer Engagement with Social Issues
The Data Incubator
Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, and routinely accepts just 1% of applicants. Employers engage with the Incubator as hiring partners.
Previously, Michael worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves.
Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events. You can find out more at www.thedataincubator.com
Senior Technical Staff, Supply Chain Analytics
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: Integrating Analytics and Design Thinking Approaches for Sales Order Propensity Prediction
Chief of Staff
As Change.org's Chief of Staff, Duncan leads on clarifying company strategy and driving execution in line with it. Duncan is originally from Australia, moved to New York almost three years ago, and is passionate about the potential for mission-centered corporations to show us a new way of doing business. Before Change.org Duncan worked as a strategy consultant, first with McKinsey & Co and then focused on the non-profit sector with Social Ventures Australia. He also previously served as Deputy CEO at The Oaktree Foundation, an Australian non-profit focused on providing educational opportunities for young people in developing communities across the Asia-Pacific, and building a movement of Australians acting like global citizens.
Session: Anatomy of a Social Movement: Using Analytics to Change the World
Senior Vice President, Big Data Analytics & Information Management
In the application economy, every enterprise is turning into a software company. Saum Mathur is a seasoned leader who transforms traditional companies into digital powerhouses. Currently he is leading the digital transformation at CA technologies through the use of big data analytics.
Prior to joining CA technologies, Saum spent 14 years at Hewlett Packard. Over this time he served as CIO of the Personal Computing division, CIO of Software business, and CIO of Americas region. During his tenure at HP, Saum implemented industry's leading big data platform, developed the strategy for and launched HP's enterprise mobile platform, and transformed HP's digital commerce.
An astute business executive, Saum guided the launch of HP's big data offering, HAVEN, and the mobile platform offering, HP Anywhere, in the market.
As a modern CIO, Saum, in addition to managing technology, also participates actively in helping the company grow revenues. He helped forge strategic alliances between HP, a large systems integrator in India, and a prominent big data company.
As a thought leader, Saum has served on advisory boards of MapR, a Hadoop Company, and Clique Intelligence, a startup technology company. He has given seminars on application modernization, and big data transformation to hundreds of executives around the world. In addition, his ideas have been referenced by authors of technology and management books. He has a patent pending.
Saum was named as the top 100 CIOs in 2006 by the Computerworld magazine.
KEYNOTE: The Impact of Analytics and Digital Transformation on Humans
Head of Client Engagement, Data Science
He and his team works with clients across the world to ensure their success using DataRobot to solve their business problems. Prior to joining DataRobot, Greg has led modeling teams at Travelers and Regions Financial. He earned his Ph.D. in applied statistics from the Culverhouse College of Business Administration at the University of Alabama. Greg lives in Charlotte, NC with his wife and four children and their pet tarantula.
Diamond Sponsor Presentation: An Introduction to DataRobot Machine Learning Platform
Principal Architect, Data Science
Mohan Navaratna has been working as Principal Architect: Data Science in Equinix Inc. Mohan leads the Data Science team and is in the forefront of data science initiatives in Equinix, Inc.He has been working in data science field in the last five years with varied exposure to B2B and B2C companies.
Session: Churn Prediction for B2B Customers: Steps and Missteps in the Journey
Gary Neights is a Senior Director at Elemica responsible for supply chain automation and integration with global process manufacturing companies. He has over 30 years of experience consulting in process improvement and automation with large global corporations including BASF, Coca Cola, Dow, ExxonMobil, and P&G. His current focus is on large scale supply chain integration and through this he sees large opportunities to derive customer value from the data being integrated.
He started his career as an officer in the USMC and after his service worked at GP Strategies (formerly RWD Technologies). Gary holds a BS in Mechanical Engineering from Penn State and an MS in Business Administration from Boston University.
Session: Predicting and Managing Behavior In Process Industry Supply Chains
Consulting Research Scientist
Gene Osgood is a consulting research scientist at LexisNexis. He focuses on mining legal content in order to build better products for the legal markets. This includes the use of natural language processing and machine learning on legal data, primarily legal text. He works to build predictive analytics applications that can help lawyers make decisions. Prior to LexisNexis, he worked at Thomson Reuters. Gene's background is in computer science.
Session: Predicting the Fate of Legislative Bills and Finding Effective User Analytics for Business Decision Making
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 he 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.
KEYNOTE: Persuasion Modeling in Presidential Campaigns and How It Applies to Business
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: Best Practices Enhancing Contextual Experience with Predictive Analytics
Karl Rexer founded Rexer Analytics, a Boston-based analytic consulting firm, in 2002. He and his teams have delivered analytic solutions to dozens of companies. Solutions include fraud detection, customer attrition analysis and prediction, advertisement abandonment prediction, direct mail targeting, market basket analysis and survey research. Karl is a leader in the field of applied data mining. He has served on the organizing committees of several international conferences; is on the Board of Directors of Oracle's Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group; has served on IBM's Customer Advisory Board; is an Industry Advisor for Babson College's Business Analytics program; and is in the #1 position on LinkedIn's list of Top Predictive Analytics Professionals. Rexer Analytics conducts and freely distributes the widely read Data Miner Survey. The survey has been written about and cited in over 12 languages.
Ask Karl and Dean Anything (about Best Practices - for Financial Services and Beyond)
Co-Founder and Chief Scientist
Talent Analytics, Corp.
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: Predictive Job Maps: Optimizing a Workforce with a Network of Predictive Models
Satadru Sengupta is a Senior Engagement Director, Data Science at DataRobot. In this role, Satadru leads the data science engagement team in the US East Region and he works hands-on with the organizations in the NYC area (healthcare, financial and insurance industry) to integrate DataRobot machine learning platform in their problem-solving environment. Previously, Satadru worked with AIG Science Team as a Senior Manager leading quantitative modeling for global distribution. Prior to that, he worked with Liberty Mutual Insurance and Deloitte Consulting. Satadru holds a Master of Science in Actuarial Science and a Master of Science in Statistics. Satadru lives in Washington, D.C. with his wife.
Expert Panel: Data Prep: Overcoming the Bottleneck and Nailing It
Dr. Eric Siegel, Ph.D.
Predictive Analytics World
Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Predictive Analytics 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 Al Jazeera America, 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.
KEYNOTE: Weird Science: How to Know Your Predictive Discovery Is Not BS
Session: Uplift Modeling: Optimize for Influence and Persuade by the Numbers
Mike has 20+ years experience developing advanced analytic, technical, and business process solutions to solve complex marketing problems. Mike has been instrumental in driving key innovations in the automotive marketing and analytics services sector including advanced safety recall, analytically driven real time marketing, retail marketing analytics and customer communications, and extending traditional CRM into the digital, multi-channel ecosystem. Mike is a frequent speaker on advanced automotive marketing and analytics including JD Power AMR, DMAD Automotive Integrated Symposium, TLS Customer Centricity, and WardsAuto's Dealer Business. Mike received his BS from the University of Michigan and has a Kellogg MBA.
Session: Predicting Consumer Review Engagement and Sentiment Using only Readily Available Social and Demographic Data
Senior Software Engineer
Islam Tawfik is a computer scientist and currently senior software engineer at recently acquired startup Learnvest where he works on their financial simulation engine. Prior to Learnvest, he spent time at Morgan Stanley as a software engineer and eight years at Credit Suisse as a quantitative analyst working on structured product valuations. Islam holds an MS in Computer Science from New York University, Courant Institute of Mathematical Sciences.
Session: Predicting Changes in Rental Prices in New York City Using Online Restaurant Reviews
Richard Wendell is the CEO of Tellic, a data science membership organization for MidSized Pharma companies. He is also a founding Member of the Board of Directors of MIT's International Society for Chief Data Officers (ISCDO). In this role, Mr. Wendell is helping create of the de facto community of senior executives responsible for capturing the opportunity of data-driven decision making. Prior to Tellic & ISCDO, Mr. Wendell spent two and one half years as the Vice President, Data Science and Strategic Analytics for TE Connectivity (TEL), the $14B global electronics manufacturer. Mr. Wendell was brought into the company to construct the data science team from scratch and to pioneer the company's move into advanced analytics. In this role, Mr. Wendell accelerated data-driven revenue streams by executing a data strategy to deepen customer insights and relationships. Before TE Connectivity, Mr. Wendell was Vice President, Global Strategy & Business Development at American Express, where he led the company's move into analytics-driven business models.
Session: How $1B Companies are Scaling the Chief Data and Analytics Officer Function
Director of Institutional Research
Yun Xiang, Ph.D. is the director of Institutional Research at Becker College. Dr. Xiang and her team aim to transform data into clear, timely, and digestible information that inspires a culture of data-informed decision-making.Dr. Xiang received her Ph.D. in Educational Research, Evaluation, and Measurement from Boston College and her master's degree in Curriculum Instruction from Boston University. Prior to joining Becker College, she worked as the Director of Research and Development at Dipont Education Management Group and as a research scientist at Northwest Evaluation Association. Previously, Dr. Xiang worked as a college consultant to construct longitudinal data sets and provide trend analysis and predictive analysis.
Session: Enhancing the Quality of Predictive Modeling on College Enrollment
Pini Yakuel, founder and CEO of Optimove, a profitable and rapidly-growing business, has over a decade of experience in analytics-driven customer marketing, business consulting and sales. His passion for understanding what drives customer behavior led him to spearhead the development of Optimove, the industry’s leading Customer Marketing Cloud, empowering brands to maximize their customers’ value. Optimove is used by 180+ businesses, including Zynga, 1-800-Flowers, Adore Me, Lucky Vitamin, and Outbrain.
Expert Panel Data Prep: Overcoming the Bottleneck and Nailing It
Meina Zhou is a data scientist at Bitly. She mainly focuses on the applications of data science in the business analytics and predictive modeling fields. She utilizes both her business acumen and data science skills to solve business problems. She also has experience in big data analytics and enjoys making data visualizations. Prior to Bitly, she received her Master of Science in Data Science from New York University.
Session: Predictive Analytics for Different Business Types: Optimize All the Funnels