October 29-November 2, 2017
New York
The premier machine learning conference
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Speakers



 Dean Abbott

Dean Abbott

Co-Founder and Chief Data Scientist

SmarterHQ

@deanabb

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

Graphika

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

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

 Bob Bress

Bob Bress

VP, Analytics & Business Intelligence

Visible World, a division of Comcast Cable

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

Immuta

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

 Tracie Coker Kambies

Tracie Coker Kambies

Principal | Retail Technology and Analytics

Deloitte Consulting LLP

The U.S. Retail Sector Technology Lead for Deloitte bringing breadth and depth of services to the Retail market in the areas of Technology Strategy, Data &Analytics, and Cloud solutions. Also, the National Information Management & Analytics Learning Leader, and has seventeen years of business consulting experience primarily focused on retail, consumer and industrial products clients. 

Co-leads creation of the Retail Internet of Things strategy & solution development. Bring more than 10+ years of experience in Information Management & Analytics focusing on analytics strategy, organization change, master data management, governance, quality and data integration services. With strong technology delivery experience and communication skills combined with a proven leadership record across the technology landscape. 

Expert Panel:  Women in Predictive Analytics: Opportunities and Challenge

 Ron Cowan

Ron Cowan

Founder

Snowforce Data

Ron Cowan is a Business Intelligence veteran with over 25 years of data management experience and Founder of Snowforce, LLC, a boutique business intelligence and Salesforce.com consulting firm based in Los Angeles, CA.  As Global Sales Operations Leader, at ZimmerBiomet, a Fortune 500 Medical Device Manufacturer he was Lead Architect of a Global Business Intelligence (B.I.) Data Warehouse and 4,000+ user Salesforce.com implementation. Prior to ZimmerBiomet Ron was founding Vice President of Sales of Ineto, Inc. (acquired by Oracle), Director of Sales at Acuity, Inc. (acquired by Lucent Technologies) and has held senior management positions at Keystone Expositions, Inc., ISearch and Lexi International, Inc.


Ron holds an MBA from Rice University as well as an MS in IT (Business Intelligence).

Session:  Using Mileage Logs to Predict Successful Sales Behavior

 Mark Davenport

Mark Davenport

Senior Director of Analytics

The Trade Desk

Mark Davenport is the Senior Director of Analytics at The Trade Desk, a global demand-side platform in the $5B real-time bidding industry. In his role at The Trade Desk, Mark leads the strategy and execution of all of the statistical modeling behind all of the data products inside the platform.

Mark is also responsible for working directly with The Trade Desk's clients to help them understand and harness the power of their own data.

Mark worked in finance prior to joining The Trade Desk. He holds a B.S. in Systems Engineering and Economics from Washington University in St. Louis and a Master's degree in Statistics from the University of Chicago. He lives and works in New York City.

Diamond Sponsor Presentation:  The Spooky Side of Predictive Analytics: Opaque Models

Dr. John Elder

Dr. John Elder

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 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: Machine Learning Methods and Common Data Science Mistakes

 Kelley Gazdak

Kelley Gazdak

Global Vice President Data & Analytic Solutions

Dun & Bradstreet

Kelley Gazdak is passionate about helping businesses solve complex business challenges and find new sources of growth with data and analytic solutions. Kelley leads Dun & Bradstreet's team of global Data & Analytic experts that are part of the company's Advanced Analytic Services business unit.

In a career that spans two decades, Kelley has built relationships with the leading Fortune 100 companies and consistently driven strong results. With expertise in the business application of advanced analytics, marketing, master data management, risk and supply management. Kelley brings a unique, customer-centric approach to the art and science of analytics.  In the last four years she has built a global team of analytic experts that are highly skilled in helping companies leverage innovative, data-driven analytics to answer their most critical business questions.

Kelley is a graduate of the University of Florida (GO GATORS!!) where she earned her Bachelor's degree in Finance.  A long time resident of New York City, Kelley lives in downtown Manhattan with her husband and two children.

Diamond Sponsor Presentation:  Move Beyond Basic Targeting and Accelerate Sales with Help from Machine Learning

 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

 Sandeep Gopalan

Sandeep Gopalan

Pro Vice-Chancellor (Academic Innovation)

Deakin University, Melbourne, Australia

Sandeep Gopalan is the Pro Vice-Chancellor for Academic Innovation at Deakin University. Previously, he served as the Dean of Deakin Law School. Before joining Deakin University, Professor Sandeep Gopalan was the Dean of the Law School at the University of Newcastle. Prior to this, he served for four years as the Head of the Department of Law at the National University of Ireland Maynooth. He has held positions previously as an Associate Professor of Law in the United States and in the United Kingdom for several years.

Professor Gopalan worked as an investment banker on Wall Street, and as a lawyer in California before embarking on his career in academia. He graduated with a Gold Medal from the National Law School of India, and went up to Oxford (where he was a Rhodes Scholar) for his B.C.L., and D.Phil. degrees. He was appointed to the Arizona Aerospace and Defense Commission by the Governor of Arizona, and he served as Chairman during 2006-07. He has served as Co-Chairman of the American Bar Association (ABA) Aerospace and Defense Industries Committee, as Vice-Chairman of the ABA International Secured Transactions and Insolvency Law Committee, and as a Member of the ABA Commission on Immigration.

Professor Gopalan's research has been published by leading law journals in the United States, including at Columbia, Vanderbilt, U.Penn., Northwestern, George Washington, and St Louis. Some of his papers can be downloaded at http://ssrn.com/author=386877. He has published a number of opinion pieces in newspapers including the New York Times, the Wall Street Journal, the Australian, the Huffington Post, the Irish Times, and the Irish Independent. Gopalan has also appeared on a number of TV and radio shows as an expert commentator on a variety of legal issues.

Session:  Legal Ease: Applications of Predictive Analytics in the Law

 William Groves

William Groves

Chief Data & Analytic Officer

Honeywell International

Bill Groves is Chief Data & Analytic Officer at Honeywell International, a Fortune 1000 connected industrial leader. He is responsible for leading data strategy and advanced analytics to monetize data across Honeywell. He heads a global team of 50+ distinguished data scientists and strategists with deep backgrounds in machine learning, industrial analytics and big data to uncover new value for Honeywell customers.

Bill has almost two decades of industry experience in building and managing world-class analytic organizations that drive business growth. Prior to joining Honeywell, Bill served as the Chief Data & Analytic Officer at Solera where he built and ran a $500M Data and Analytics business.  He has also held executive-level roles in Data and Analytics at Fortune 500 companies including Chief Analytics Officer at Dun & Bradstreet and Analytic Consulting Leader at Fair Isaac and MBNA America.  

Bill was previously a Board Director for the Buro de Credito in Mexico and currently serves as a Board Advisor for BizEquity, the leading provider of business valuation knowledge. 

Bill graduated from the University of Delaware with a Master's degree in Technology and Innovation. He lives in Delaware with his wife and two boys. He enjoys coaching and participating in football, lacrosse and ice hockey in his spare time.

Session:  Operationalizing Analytics: The Critical Last Mile to Value

 Bryan Guenther

Bryan Guenther

Qi Program Manager

RightShip

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

 Alwin Haensel

Alwin Haensel

Business Analytics & Founder

HAMS

Alwin Haensel is the Founder and Managing Director of the Big Data & Analytics company Haensel AMS - Advanced Mathematical Solutions. He holds a Phd in Applied Mathematics and studied in London, Berlin and Amsterdam. His main fields of interest are the modeling of customer purchasing behavior, data prediction and optimization under uncertainty.  Most recently, he concentrated on eCommerce topics such as: Conversion Attribution, optimal SEA bid strategies, recommendations, dynamic pricing, as well as specific data mining and forecasting projects.

Session:  Leveraging Machine Learning Techniques for Realtime Pricing in B2B Truck Logistics

 Hai Harari

Hai Harari

Director, Talent Intelligence and Analytics

Intel

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

 Doug Howarth

Doug Howarth

CEO

MEE Inc

Doug Howarth spent over three decades for the famed Skunk Works division of Lockheed Martin, where he worked as the F-117A manufacturing program manager and retired as head of their Parametric Analysis group.  He founded MEE Inc. in 2011.  He discovered 4D, 5D, ND and ND+T constructs and coordinate systems, Financial CAT Scanning, Profit as an Independent Variable (PAIV), Demand as An Independent Variable (DAIV), Economic Trajectory Analysis (ETA) and developed the Law of Value and Demand.  Collectively, these phenomena describe all of the world’s markets simultaneously and over time.  Mr. Howarth published ten peer-reviewed works through journals issued by the Royal Aeronautical Society (RAeS), the Society of Automotive Engineers (SAE) and the Institute of Electronic and Electrical Engineers (IEEE), among others.  His book on Multidimensional Economics, the discipline he revealed, awaits publication.  He holds a Bachelor of Arts degree in Economics from Washington State University.     

Lunch and Learn: 4D Today, 5D Tomorrow

 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

 Krishna Kallakuri

Krishna Kallakuri

President

diwo

Prior to founding diwo, Krishna was a founding member of DataFactZ, one of the fastest-growing analytics company in the Midwest. He brings more than 15 years of expertise in the IT industry as well as senior management experience. Krishna has a strong passion for delivering unique business solutions that leverage global delivery model.

Session:  Opportunity - Driven Enterprise; Turning Business On Its Head

 Vishwa Kolla

Vishwa Kolla

Head of Advanced Analytics

John Hancock Insurance

Vishwa is the head of Advanced Analytics (AA) at John Hancock Insurance (JHI). AA at JHI involves Descriptive, Predictive, Prescriptive, Nudge, Cognitive and Experimental Analytics.

He is a seasoned leader, speaker, collaborator, mentor and a coach in several areas including Advanced Analytics, Data Science, Big Data and in Communication. He oversees the transformation of John Hancock and continues to turn it into an Data, Analytics, Insight, Model and Action rich organization.

Vishwa helped F5-500 companies on a variety of problems using Predictive Analytics as a means. Select clientele includes Deloitte, Walmart, Caterpillar, AIG, AT&T, Cablevision, HP, Cardinal Health and Orlando Health, IBM, and Sun Microsystems (now Oracle).

Vishwa has an MBA from Carnegie Mellon University, an MS from U. Denver and BS from BITS Pilani, India.

Session: A Shiny Way to Operationalizing Analytics

 Max Kuhn

Max Kuhn

Software Engineer

RStudio

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 Machine Learning: 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

UPS

"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

Machine-Learning Engineer

Pienso

Chuan-Heng (Henry) Lin, is a Machine Learning engineer at Pienso. An artificial intelligence startup building a platform to democratizes machine learning. He holds a master’s degree in data science with a focus on smart cities from NYU and has experience across various New York tech startups that concentrate on Natural Language Processing and probabilistic machine learning applications. In 2016, he won first place in a human-trafficking hackathon with software that enhances analyst case management for the New York Defense Attorney office.

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

 Julia Minkowski

Julia Minkowski

Risk Analytics Manager

Signifyd

Julia is an accomplished professional with experience in Software Development, Business Intelligence, Risk Management and Data Analysis in both large corporate environments and start-ups. Currently she is a Principal R&D in Fraud Analytics at Signifyd, saving millions in fraud for global E-Commerce. Prior to this, Julia held various positions at Telecom and Banking/Financial Industry such as Fiserv and Verizon Wireless, evolving from managing the Billing Operations through Software Development, Analysis and Reporting, Data Warehouse into Predictive Analytics in Identity Fraud Detection. 

Julia holds a Bachelor's Degree in Sociology and Geography from the Hebrew University of Jerusalem, Software Programming Certificate from John Bryce Institute, MBA from HaUniversita Ha-Ptuha of Israel, and Strategic Decision and Risk Management Certificate from Stanford University. She is native of Russia and is based in the Silicon Valley.

Expert Panel:  Women in Predictive Analytics: Opportunities and Challenges

 Yulin Ning

Yulin Ning

Senior Director in Global Decision Management

Citigroup

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

Dstillery

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

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

 Jennifer Prendki

Jennifer Prendki

Head of Data Science

Atlassian

Dr. Jennifer Prendki is the Head of Data Science at Atlassian, where she leads all Search and Machine Learning initiatives and is in charge of leveraging the massive amount of data collected by the company to load the suite of Atlassian products with smart features.  She received her PhD in Particle Physics from University UPMC – La Sorbonne in 2009 and has since that worked as a data scientists for many different industries.  Prior to joining Atlassian, Jennifer was a Senior Data Science Manager in the Search team of Walmart eCommerce.  She enjoys addressing both technical and non-technical audiences at conferences and sharing her knowledge and experience with aspiring data scientists.  

Session: Predicting Customer Churn from Product Usage at Atlassian

 Steven Ramirez

Steven Ramirez

CEO

Beyond the Arc

@beyondthearc

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

President

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

Verizon

@agrobins

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

Paychex

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

 Satadru Sengupta

Satadru Sengupta

General Manager of Insurance

DataRobot

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.

Session:  Machine Learning Automation: Large Scale Adoption of Predictive Analytics

 Rajesh Shekhar

Rajesh Shekhar

Data Scientist

DataRobot

Currently working as Data Scientist at DataRobot with more than 19 years of experience in the area of Artificial Intelligence, Distributed Computing and Advanced Analytics. He was Executive Vice President of Capital Business Credit, where he successfully started a small business lending business for the company. He brings extensive experience from financial services and technology industry and worked for companies like Oracle, Moody's and AIG. He has Master in Mathematics of Finance from Columbia University and a Masters in Engineering from Purdue University. He has a graduate certification from Stanford University in Quantitative Finance and Risk Management and is CFA and FRM charter holder.

Lunch & Learn:  How to start on Machine Learning and Predictive 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: The Limits of Surveys and the Power of Google Search Data

 Wanda Wang

Wanda Wang

Data Scientist - Investment Management Fintech Strategies

Vanguard

Wanda Wang has 6+ years of experience in various data-driven roles, from successful startups (Yext) to large financial organizations (J.P. Morgan and Citi). Currently she is a Data Scientist within the Investment Management Fintech Strategies team at Vanguard. Wanda graduated from NYU Stern in 2011.

Session: AI: From Prototype to Production

 Steve Weiss

Steve Weiss

Content Manager, Data Science and Business Analytics

LinkedIn

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

 Jade Xi

Jade Xi

Cslt-Pred/Presc Analytics

Verizon

Jialin (Jade) Xi joined Verizon in April of 2016, working on advanced analytics projects in Consumer & Marketplace Insights. Jialin graduated in December 2015 with a Master's in Business Intelligence and Analytics from Stevens Institute of Technology. She also holds a Master's and Bachelor's in Information Engineering from Xi'an Jiaotong University. She previously spent 3 years in China as a management consultant, including a stint consulting for China Mobile.

Session:  Predicting Brand Love With Wireless Behaviors 

 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

 Pallavi Yerramilli

Pallavi Yerramilli

Senior Product Manager

The Trade Desk

Pallavi Yerramilli is a Senior Trading Specialist at The Trade Desk, a global technology platform for buyers of advertising.  In her role, Pallavi manages a diverse portfolio of programmatic agency clients, working closely with them to optimize and drive performance for their campaigns. In addition, she partners closely with the analytics team at The Trade Desk to build data driven tools to enhance performance based on her clients' needs. Pallavi has a background in electrical engineering and worked as a fixed income trader prior to joining The Trade Desk.

Expert Panel: Women in Predictive Analytics: Opportunities and Challenge

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