October 29-November 2, 2017
New York
Delivering on the promise of data science


 Dean Abbott

Dean Abbott

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: When Model Interpretation Matters: Understanding Complex Predictive Models

Expert Panel: Q&A: Ask Dean and Karl Anything (about Best Practices)

Workshop:  Advanced Methods Hands-On: Predictive Modeling Techniques

Workshop:  Supercharging Prediction with Ensemble Models

 Colin Ard

Colin Ard

Senior Enterprise Data Scientist

Micron Technology, Inc.

Colin Ard works as a Senior Enterprise Data Scientist at Micron Technology Inc., developing and communicating powerful and interpretable machine learning solutions for business problems across sales, supply chain, and manufacturing operations. He holds a PhD in Experimental Psychology from UCSD, where he also received his postdoctoral training in biostatistics.

Prior to his current role with Micron he held a faculty position as a Project Scientist in UCSD's Department of Neurosciences, where his research focused on applications of latent variable modeling and linear mixed effects models to experimental design and analytic methodology in Alzheimer's clinical trials. In addition to publications in peer-reviewed scientific journals, including, Nature, Neuron, and the Journal of Pharmaceutical Statistics, and experience as a university instructor for courses in statistics and psychology, Colin has presented his work at leading international conferences to technical as well as industry and subject-matter experts.

Session: Demand Forecasting with Machine Learning

 Feyzi Bagirov

Feyzi Bagirov

Data Science Advisor at Metadata.io and Analytics Instructor, Harrisburg University of Science and Technology

Mr. Feyzi R. Bagirov is a Data Science Advisor at Metadata.io 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: Acquisition Funnel for Higher Education

 Vladimir Barash

Vladimir Barash

Senior Researcher


Vladimir Barash is a Senior Researcher and Engineer at Graphika. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses mainly on the intersection of social media and large-scale social phenomena, ranging from online political activism in Russia to the cross-cultural patterns of emoticon use in Twitter to leveraging social media for the prediction of emergency events.

In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.

Workshop:  Big Data: Proven Methods You Need to Extract Big Value

 Anasse Bari

Anasse Bari

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: Time Series Prediction with Twitter: A Case Study of Crime in New York City

 Leslie Barrett

Leslie Barrett

Senior Machine Learning Software Developer

Bloomberg LP

Leslie Barrett is a senior software engineer on the Machine Learning team at Bloomberg LP. Before that she lead the Search and Information Retrieval team at Theladders.com. Leslie holds a Ph.D. in computational linguistics from New York University and resides in New York City.

Session: Crowd-Sourcing and Quality: How To Get The Best Out of Hand-Tagged Training Data for Machine Learning Models

 Richard Boire

Richard Boire

Senior Vice President

Environics Analytics

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: Machine Learning vs. Feature Engineering: What should the Focus be in Attempting to Predict Customer Behaviour

 David Boyle

David Boyle

EVP Insight

BBC Worldwide

David has spent the last seven years constructing global insight capabilities to help transform the TV, publishing and music industries - helping them make quicker, smarter and bolder decisions for their brands. He joined BBC from his most recent role as SVP Consumer Insight at HarperCollins Publishers where his consumer insight work allowed the company to better understand consumer behavior and attitudes towards books, authors, book discovery and purchase. Prior to that David was at EMI Music, where he delivered insight to all parts of the business in more than 25 countries, helping to shift the organization's decision-making at all levels from artist signing to product development and brand development plans for EMI's biggest artists including The Beatles and Pink Floyd. He has previously worked to help the Labour party win their historic third term in the UK and to build infrastructure to help Democrats win elections in the US.

Session: Catchy content: What makes TV content work?

 Bob Bress

Bob Bress

VP, Analytics & Business Intelligence


Bob Bress is Vice President of Analytics & Business Intelligence in a division of Comcast Cable focused on advanced advertising technologies. In that role he leads teams of data science and analytical staff focused on using their expertise to lead the development of the next generation of advanced targeted advertising products for
television. Bob has over 15 years of analytics experience across industries including work in hospitality, energy, and at GE's Global Research Center in the Applied Statistics Lab.

Bob holds undergraduate and graduate degrees in Industrial Engineering and Operations Research & Statistics from Rensselaer Polytechnic Institute.

Session: Accelerating Data Science Innovation

 Andrew Burt

Andrew Burt

Chief Privacy Officer & Legal Engineer


Andrew is Chief Privacy Officer & Legal Engineer at Immuta, the data governance platform for the world's most secure organizations. He is also a visiting fellow at Yale Law School's Information Society Project.

Previously, Andrew served as Special Advisor for Policy to the head of the FBI Cyber Division, where he served as lead author on the FBI's after action report for the 2014 attack on Sony. A former reporter, Andrew has published articles in The Financial Times, The Atlantic, The Los Angeles Times, and The Yale Journal of International Affairs, among others. His book, American Hysteria: The Untold Story of Mass Political Extremism in the United States(Lyons Press, 2015), was called "a must read book dealing with a topic few want to tackle" by Nobel laureate Archbishop Desmond Tutu.

Andrew holds a J.D. from Yale Law School and a B.A. from McGill University. He is a term-member of the Council on Foreign Relations, a member of the Washington, D.C. and Virginia State Bars, and a Global Information Assurance Certified (GIAC) cyber incident response handler. 

Session: Regulating Opacity: Solving for the Conflict Between Laws and Analytics

 James Casaletto

James Casaletto

Senior Solutions Architect

MapR Technologies

James Casaletto is a senior solutions architect at MapR Technologies where he designs, implements, and deploys complete solution frameworks for big data. He has written and delivered courses on MapReduce programming, data engineering, and data science on Hadoop. Today, he is also teaching a graduate course in these topics for the computer science department at San Jose State University.

Workshop: Hadoop for Predictive Analytics: Hands-On Lab

 Payel Chowdhury

Payel Chowdhury

Associate Director - Data Science

The Clorox Company

Payel Chowdhury is an Associate Director-Data Science at the Clorox Company. In her current role, she leads a data science COE in the marketing function of the company. Previously, she worked as a Chief Scientist aligned to insurance and healthcare at Genpact and Assistant Vice President responsible for treasury risk (CCAR) modeling for Citigroup. She has extensive experience in managing data science projects and teams, quantitative research and teaching, and has authored several papers.

She has graduated with a PhD in Economics with specialization in applied econometrics and a MS in Statistics from University of California, Irvine.

Session: Getting Started with Data Science Driven Insights, Execution and Innovation in the CPG Industry

Dr. John Elder

Dr. John Elder

CEO & Founder

Elder Research, Inc.


John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina and Washington DC. 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, and was named by President Bush to serve 5 years on a panel to guide technology for national security.

Special Plenary Session: What to Optimize? The Heart of Every Analytics Problem

Workshop:  The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and Common Data Mining Mistakes

 Steve Fowler

Steve Fowler



Steve Fowler is ambitious, passionate about business and technology, and his purpose is to help others. He is thankful to have played key roles in some of the world's largest global technology solutions to the Fortune 500 and federal government. He writes and speaks about these experiences. Steve founded Jivoo to specialize in gaining insights from internet of things (IoT) data.

Session: Advancing Hydroponics through IoT Analytics

 Michael E. Gooch-Breault

Michael E. Gooch-Breault

Director, Consumer and Marketplace Insights

Verizon Wireless

Michael Gooch-Breault leads a team of data experts at Verizon. They analyze factors that influence the communications and technology industry, like conversations on social media, that provide critical insights to the business about brand, customer service and competition. They use data and tools to inform decision making - like large surveys, Net Promoter Scores, competitive intelligence, internal customer databases and syndicated research to ensure a maximum return on investments.

He is passionate about creating meaningful and personal customer experiences that ultimately drive growth. He is equally committed to developing people and other internal clients along the journey. "MGB" has been with Verizon for over 10 years.

Session: Predicting Brand Love with Wireless Behaviors

 William Groves

William Groves

Chief Data & Analytic Officer


Session:  Operationalizing Analytics: The Critical Last Mile to Value

 Bryan Guenther

Bryan Guenther

Qi Program Manager


Bryan joined RightShip in 2013 to enhance the capabilities of the existing Ship Vetting Information System, employing predictive analytics deliver to the commercial shipping sector a state-of-the-art risk management system RightShip Qi.

Before joining RightShip, Bryan worked at BP as a Business Project Manager and was responsible for designing, implementing and delivering BP Shipping's largest ever transformation IT project. He was also Senior Vetting Specialist and Port Information Superintendent for BP in the US and UK.

Bryan has also held the positions of Vice President - Business Development for Heidenreich Innovations, Project Manager for Optimum Logistics in New York, Director of Technology at MaritimeDirect.com, and he also established the first Maritime Assurance Program at ARCO Marine.

Bryan has a Bachelor of Science in Marine Transportation, commencing his seafaring career as a Cadet on container ships with American President Lines and later sailing as a Senior Officer on ARCO tankers.

Session: Overcoming Challenges Implementing a Risk Model in the Maritime Industry

 Hai Harari

Hai Harari

Director, Talent Intelligence and Analytics


Hai Harari is the Head of Talent Competitive Intelligence at Intel. He is leading a global organization of researchers, conducting external markets analyses, business-focused researches and people analytics. His organization charter is to drive strategies and impactful decisions via intelligence in order to grow and protect the company's most important asset - its talent.

During his 15 years HR career, Hai conducted several global HR management roles, including Systems Implementation, Projects Management, Businesses Transformation, Talent Acquisition, Marketing & Branding, Market Research and Talent Analytics. Hai has a B.Sc. in Industrial & Information Systems Engineering and did his Executives MBA, specializing in Management Technologies. Prior to Hai's HR career, he served the Israeli military for several years as a Captain, commanding the Navy Medical School.

Session: How Intel Wins the Right Marketplace Talent with Analytics

 Wayne Huang

Wayne Huang

Director of Analytics

Prudential Financial Inc.

Wayne Huang is Director of Analytics at Prudential Financial Inc. He leads a data scientist team, working with executives in Actuarial, Underwriting, Marketing, and Claims to create and implement analytics solutions that maximize business value and enhance customer experience. He has extensive experience in leading large analytics and technology projects, solving complex business problems. He is also an Adjunct Professor at Stevens Institute of Technology Graduate School of Business. He holds a PhD from Stevens Institute of Technology, an MBA from the State University of New York at Albany, and BS from National Central University. His research interests are in predictive analytics and process innovation.

Session: Value Creation Through Analytics Innovation

 Max Kuhn

Max Kuhn

Software Engineer


Max Kuhn is a software engineer at RStudio. a leading company for R software and tools. He is currently working on improving R's modeling capabilities. He has a Ph.D. in Biostatistics.

Max was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max is the author of eight R packages for techniques in machine learning and reproducible research and is an Associate Editor for the Journal of Statistical Software. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015.

He has taught courses on modeling, including many classes for Predictive Analytics World, the useR! conference, the Open Data Science Conference, the India Ministry of Information Technology, and others.

Workshop:  R for Predictive Modeling:A Hands-On Introduction

 Emilie Lavoie-Charland

Emilie Lavoie-Charland

Research & Innovation Analyst

The Co-operators

Emilie Lavoie-Charland is a research and innovation analyst for The Co-operators in Quebec City, Canada. She has a master's degree in statistics and 4 years of experience in applying advanced statistical models in health care and in insurance. She has developed cross-sale, retention and true-lift models for client engagement programs at Co-operators. To better understand the benefits and the impacts of these marketing programs she has collaborated with numerous departments within the company to develop a scorecard: a single table presenting both hypotheses related to and results of the marketing campaigns.

Session: Which Predictive Model Will Best Help Increase Retention?

 Jack Levis

Jack Levis

Senior Director, Process Management


"Through the marriage of technology, information and analytics UPS reduces cost and improves services. These advanced technologies streamline our business processes and ultimately benefit our customers."

Jack Levis, Senior Director of Process Management, drives the development of operational technology solutions. These solutions require advanced analytics to reengineer current processes to streamline the business and maximize productivity.

Under Jack's direction, UPS has completed integration of multiple operations systems, requiring extensive system engineering, usability and analytics provisions. These systems ultimately synchronize the flow of data throughout UPS, allowing the seamless movement of goods, funds and information.

Jack has been the business owner and process designer for UPS' award-winning Package Flow Technology suite of systems, a breakthrough change for UPS, resulting in 85 million fewer miles driven each year.

His team designed UPS' next generation of dispatching technologies which use advanced optimizations. The world-class optimizations and systems, UPS ORION, On-Road Integrated Optimization and Navigation, is in deployment and will provide significant operational benefits to UPS and 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.

Jack holds advisory council positions for multiple universities and associations, including the U.S. Census Bureau Scientific Advisory Committee.

In his spare time, Jack enjoys baseball, scuba diving, skiing, home electronics and Corvettes. He lives in York, Pa. with his wife and four children.

Session: UPS' Road to Optimization

 Chuan-Heng Lin

Chuan-Heng Lin

Enrolled at New York University

Chuan-Heng Lin is data scientist enrolled at New York University. His research has been focused in developing deep learning algorithms. He recently worked as data engineer at Xynosys, Inc., where he designed an enterprise analytics tool customer segmentation.

Session: Time Series Prediction with Twitter: A Case Study of Crime in New York City

 Aaron McKinstry

Aaron McKinstry

Computer Scientist

Courant Institute of Mathematical Sciences of New York University

Aaron McKinstry is a computer scientist of the Courant Institute of Mathematical Sciences of New York University. Aaron has several years of software engineering experience, he recently worked at the Space and Naval Warfare Systems Center, Pacific in San Diego, which provides the Navy with research and development of integrated control, communications, computers, intelligence and surveillance and reconnaissance (C4ISR) across all war-fighting domains. His interests include machine learning and deep learning.

Session: Time Series Prediction with Twitter: A Case Study of Crime in New York City

 Yulin Ning

Yulin Ning

Senior Director in Global Decision Management


Yulin Ning is a Senior Director in Global Decision Management, a global strategy and analytic division in Citi's Global Consumer Bank. He currently leads next generation analytics efforts within Platform and Capability function, acting as a chief data scientist, aiming to accelerate global adoption of big data and machine learning for creative business solutions. He developed expertise in digital (clickstream), text mining, voice analytics, big data, and machine learning. His most recent interests are on deep learning and artificial intelligence.

Over 18 years at Citi, Yulin has been actively involved in building some of the key decision management disciplines in the areas of price management, stress test capabilities, optimization, big data / machine learning roadmap, and data scientist disciplines. He worked with a range of financial and technology companies, vendors, and universities specializing in analytics and emerging technologies. He holds a Ph.D. in Agricultural Economics.

Session: A Modified Logistic Regression Approach Enhanced by New Interactions and Scaling Detections through Random Forests and GBM

 Claudia Perlich

Claudia Perlich

Chief Scientist


Claudia Perlich leads the machine learning efforts that power Dstillery's digital intelligence for marketers and media companies. With more than 50 published scientific articles, she is a widely acclaimed expert on big data and machine learning applications, and an active speaker at data science and marketing conferences around the world.

Claudia is the past winner of the Advertising Research Foundation's (ARF) Grand Innovation Award and has been selected for Crain's New York’s 40 Under 40 list, Wired Magazine's Smart List, and Fast Company's 100 Most Creative People.

Claudia holds multiple patents in machine learning. She has won many data mining competitions and awards at Knowledge Discovery and Data Mining (KDD) conferences, and served as the organization's General Chair in 2014.

Prior to joining Dstillery in 2010, Claudia worked at IBM's Watson Research Center, focusing on data analytics and machine learning. She holds a PhD in Information Systems from NYU.

Session: The Predictability Predicament: Your Model Overlooks the Real Target

 Daniel Porter

Daniel Porter



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: Using Rapid Experiments and Uplift Modeling to Optimize Outreach at Scale

 Kristina Pototska

Kristina Pototska



Kristina is a CMO at TriggMine, email marketing automation service. She is great when it comes to email marketing tips.

During the past 2 years, she successfully launched more than 50 email campaigns for e-commerce websites. She's also the voice of TriggMine. Kristina performed as a speaker at 100+ events in Europe & Asia. She believes that email marketing rules and data is the king.

Session: Real-Time Automation to Build Relationships & Retain Customers

 Jennifer Prendki

Jennifer Prendki

Principal Data Scientist


A former experimental particle physicist turned data scientist, Dr. Jennifer Prendki has been working on all kinds of big data problems for more than 10 years, both as an academic and an industrial researcher. Her eclectic experience in various industries including finance, advertising and ecommerce allowed her to develop an extensive understanding of a vast range of machine learning techniques as well as a solid knowledge of statistics and computer science. Her journey led her to the conviction that hard scientists have an important role to play in the predictive analytics field.

She currently leads the Metrics and Measurements effort within the Search team of @WalmartLabs, and loves to promote mathematical acuteness as a world-class player in the future of big data. She is a strong advocate for the inclusion of scientists and engineers from all backgrounds in the data science field.

Session: On the Relative Value of Implicit and Explicit Feedback in Predicting Customer Preferences

 Steven Ramirez

Steven Ramirez


Beyond the Arc


Steven J. Ramirez is the chief executive officer of Berkeley, Calif.-based Beyond the Arc, Inc., a firm recognized as a leader in helping companies transform their customer experiences by leveraging advanced analytics.

In addition to developing and executing the vision for Beyond the Arc, Ramirez leads teams of data and strategy consultants committed to client success. They analyze customer and social media data, combined with text analysis, to drive customer growth, improve customer retention, understand service breaks and build stronger customer loyalty.

Prior to leading Beyond the Arc, Ramirez served as an executive with Time Warner, where he was responsible for creating and successfully implementing marketing and corporate development strategies.

Ramirez earned a bachelor's degree and master's in Business Administration from the University of California at Berkeley. He as also created and taught courses in business management for UC Berkeley and been a guest speaker at the university's Haas School of Business.

Session: Customer Journey Analytics: Blazing Paths to Customer Success

 Tom Redman

Tom Redman

Data Quality Solutions

Tom Redman, the "Data Doc," helps companies, including many of the Fortune 100, improve data quality. Those that follow his innovative approaches enjoy the many benefits of far-better data, including far lower cost. He is the author of Getting In Front on Data: The Who Does What, (Technics Publications, 2016) and Data Driven (Harvard Business Review, 2008). His articles have appeared in many publications, including Harvard Business Review, The Wall Street Journal and MIT Sloan Management Review. Tom started his career at Bell Labs, where he led the Data Quality Lab. He has a Ph.D. is in Statistics and two patents.

Session: Three Steps for Improving Data Quality for Predictive Analytics

 Karl Rexer

Karl Rexer


Rexer 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.

Plenary Session: Industry Trends: Highlights from the 2015 Data Miner Survey
Expert Panel: Q&A: Ask Dean and Karl Anything (about Best Practices)

 Simon Rimmele

Simon Rimmele

Associate, Analytics

NYC Mayor's Office of Data Analytics

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

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

Session: Quickly Building an Analytics Environment to Address a Public Health Crisis in NYC

 Anne G. Robinson

Anne G. Robinson

Executive Director, Strategy, Analytics and Systems



Anne G. Robinson is the Executive Director of Global Supply Chain Strategy, Analytics and Systems, at Verizon, a Fortune 15 company and leading provider of wireless, fiber-optic and global internet networks and services. She is responsible for the overarching strategic vision across Verizon's end-to-end supply chain which includes the wireless consumer supply chain, network supply chain, video and internet supply chain as well as global sourcing and procurement. Additionally, her team drives supply chain excellence through world class data-analytics, process innovation, and employee empowerment to achieve a holistic, collaborative and customer centric supply chain organization, that results in improved product life cycle management, working capital optimization, and shareholder value.

Prior to joining Verizon Wireless, Anne spent several years with Cisco Systems, a high tech networking company, where her responsibilities included managing advanced analytics, business intelligence, and performance management teams across the supply chain. As the driving force for many foundational and cross-functional process innovations, she helped establish Cisco's presence and recognition as a leader in business intelligence and analytics, including being inducted into the balanced scorecard hall of fame.

Anne is originally from St. John's, Newfoundland, Canada. She has a Bachelor of Science with Honours in Mathematics from Acadia University, a Master of Applied Science in Management Science from University of Waterloo and a Masters and PhD in Industrial Engineering from Stanford University.

Anne is a Past President of INFORMS (the Institute for Operations Research and the Management Sciences), a professional organization focused on applying advanced analytical theory and practice for making better business decisions. She is a popular industry speaker and has served on several advisory boards including the advisory board for the Stevens Institute of Technology Masters Of Science in Business Intelligence & Analytics. A constant champion for analytics, Anne is the founding editor of INFORMS Editor's Cut, an online multimedia collection examining important topics in operation research and analytics. A frequent tweeter, you can follow Dr. Robinson @agrobins.

Keynote: The Right Analytics for the Job: Tips and Tricks for Success
Expert Panel: Women in Predictive Analytics: Opportunities and Challenge

 Rob Rolleston

Rob Rolleston

Manager, Data Science


Rob Rolleston is the Manager, Data Science at Paychex. Previously Rob worked at Xerox in the areas of Information Visualization, Strategy & Planning, and Color Management. He has 47 issued patents, and numerous technical publications and presentations.

He received his B.S. in Computational Physics from Carnegie-Mellon University, and his M.S. and Ph.D. in Optics from the University of Rochester. Rob recently completed an MPS Degree in Information Visualization from Maryland Institute College of Arts, and is now an instructor for the program where he teaches statistics and data analysis. Rob has also been an adjunct professor and instructor at Rochester Institute of Technology. He has served on the Executive Advisory Board for the New York State Center for Electronic Imaging Systems, the Advisory Board for the Rochester Institute of Technology Center for Imaging Science, and was chair of the Xerox University Affairs Committee.

Session: Retention Modeling in Uncertain Economic Times

 Shatrunjai Singh

Shatrunjai Singh

Senior Data Scientist

John Hancock

Dr. Shatrunjai Singh is an award winning Sr. Data Scientist who has been employing advanced statistical analysis and data visualization. His thesis work was on predictive modelling on epilepsy data to predict seizure outcomes and this won him the prestigious Ryan Fellowship award (one of highest research award in the US). He has also received awards and grants from the American Heart Association, The Epilepsy Foundation and has been a fellow of the data incubator. He has extensive experience in Python, R, SQL and Tableau. He recently won the regional Tableau championship. He currently works as a senior data scientist in the advanced analytics team at John Hancock.

Session: A Shiny Way to Operationalizing Analytics

 Seth Stephens-Davidowitz

Seth Stephens-Davidowitz

Author and NYTimes Opinion Writer

Seth Stephens-Davidowitz is a New York Times op-ed contributor, a visiting lecturer at The Wharton School, and a former Google data scientist. He received a BA in philosophy from Stanford, where he graduated Phi Beta Kappa, and a PhD in economics from Harvard. His research—which uses new, big data sources to uncover hidden behaviors and attitudes—has appeared in the Journal of Public Economics and other prestigious publications. He lives in New York City.

Session: Insights from a Master Data Storyteller - "Everybody Lies" Author

 Wanda Wang

Wanda Wang

Vice President, Fraud Data Scientist


Wanda Wang has 6+ years of experience in various data-driven roles, from successful startups(Yext) to large financial organizations(J.P. Morgan). Currently as a data scientist at Citigroup in the Global Consumer Banking group, she applies machine learning techniques to fight credit card fraud. Wanda graduated from NYU Stern in 2011.

Session: Project Management for Data Scientists

 Steve Weiss

Steve Weiss

Content Manager, Data Science and Business Analyst


Steve Weiss is content manager for the Data Science and Business Analytics course libraries at LinkedIn Learning/Lynda.com. His focus is on developing learning resources that support LinkedIn's mission in connecting the world's professionals to make them more productive and successful. He spends a lot of time building a growing network of top tech experts who have a passion for teaching; tracking an exponentially growing group of topic and sub-topic areas; and interacting with the members of the data science and analytics community to help them get sh*t done in the name of science, logical thinking, and improving the world we share and live in.

Session: The Sprint for Teaching Data Science: LinkedIn Learning, Analytics, and the New Era of Just-In-Time Skills Training

 Gen Xiang

Gen Xiang

Software Engineer

Trinnacle Capital Management

Gen Xiang is a computer scientist and researcher at NYU currently working as a software engineer at Trinnacle Capital Management, a New York-based hedge fund where he works on high frequency trading algorithms and platforms. 

Session: Time Series Prediction with Twitter: A Case Study of Crime in New York City

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