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



 Dean Abbott

Dean Abbott

Chief Data Scientist

Abbott Analytics

@deanabb

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

Session: 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

Senior Machine Learning Engineer

Booz Allen Hamilton

Feyzi Bagirov is currently a Senior Machine Learning Engineer with Booz Allen Hamilton and a PhD in Data Sciences Candidate at Harrisburg University of Science and Technology. He is a former Senior Data Science Consultant at NATO ACT. He is also a part-time Analytics Instructor at Harrisburg University of Science and Technology and Columbia University.

Session: Acquisition Funnel for Higher Education

 Vladimir Barash

Vladimir Barash

Chief Scientist

Graphika

Vladimir Barash is Director Graphika Labs. 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 on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.


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

Dr. Anasse Bari, Ph.D.

Dr. Anasse Bari, Ph.D.

Professor of Computer Science - Director of the AI and Predictive Analytics Lab

New York University

Anasse Bari is a professor of computer science and director of the Predictive Analytics and AI research lab at New York University. Prof. Bari teaches computer science and leads a multidisciplinary research team that designs specialized Artificial Intelligence to help solve problems in healthcare, business, finance, politics and social good.

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

 Leslie Barrett

Leslie Barrett

Senior Software Engineer

Bloomberg LP

Leslie Barrett is a Senior Software Engineer at Bloomberg LP's Bloomberg Law division specializing in NLP and Machine Learning applied to legal and government text. Before Bloomberg she was Director of Search Technology at The Ladders Inc, an online resource for executive jobseekers and recruiters. Previously, she was Director of Language Technology at the Financial Times where she managed groups creating new online news search products and electronic news alerts. Leslie holds Ph.D. in Computational Linguistics from New York University. She has over 20 published papers in the fields of Natural Language Processing and Information Retrieval and holds 2 patents. She serves on the Program Committees for the International Conference on Computational Linguistics and Intelligent Text Processing and the International Workshop on Big Data for Financial News.



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

 Richard Boire

Richard Boire

President

Boire Analytics

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


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


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


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


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


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

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

 Bob Bress

Bob Bress

Head of Data Science

Freewheel, A Comcast Company

Bob Bress is Head of Data Science at Freewheel, a Comcast Company focused on advanced advertising technologies. In that role he leads teams of data science and analytical staff using their expertise to lead the development of the next generation of advanced targeted advertising products for television and premium video. 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

PhD Candidate

UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR

James Casaletto is studying bioinformatics and biomedical engineering at UC Santa Cruz.  Previously, he worked at MapR Technologies where he designed, implemented, and deployed complete solution frameworks for big data. He has written and delivered courses on MapReduce programming, data engineering, and data science on Hadoop to thousands of students around the world.

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

Tracie is the U.S. Retail  Sector Analytics and IoT Lead for Deloitte bringing breadth and depth of services to the Retail market in the areas of Technology Strategy, Analytics & Information Management, Cloud and IoT solutions. She is the National  Analytics & Information Management & Analytics Alliance Leader, and has seventeen years of business consulting experience focused on retail, consumer and industrial products clients.  Tracie also leads creation of the Retail Internet of Things strategy and solution development.


Tracie has deep experience in information management & analytics, master data management and governance, and data integration projects .  She manages and delivers complex global data & analytics projects. She bring business and IT together to deliver analytics and data strategies,  data quality, governance, and drive insights at the speed of business. Tracie has strong technology delivery experience and communication skills combined with a proven leadership record in the Technology and Analytics arena.

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, Ph.D.

Dr. John Elder, Ph.D.

Founder & Chair

Elder Research

@johnelder4

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

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

Dr. Alwin Haensel

Dr. Alwin Haensel

Founder and Managing Director

Haensel AMS

Alwin is the Founder and Managing Director of the data analytics and technology boutique Haensel AMS – Advanced Mathematical Solutions, with offices in Berlin and New York. He holds a Phd in Applied Mathematics and studied in London, Berlin and Amsterdam. His main fields of interest are the modeling of individual customer purchasing behavior to optimize pricing and marketing strategies. Most recently, he concentrated on eCommerce topics such as: multi-touch attribution, dynamic pricing.

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 – Loven Systems

Krishna Kallakuri is President & founder of Loven Systems, the creators of diwo®.  Krishna’s visionary leadership and delivery of transformational BI and Analytics initiatives to leading Fortune 500's has landed the practice he has founded on the Midwest’s Fastest-Growing list. With 20 years of expertise in technology and executive management, Mr. Kallakuri’s passion for advanced analytics, cognitive technologies, and artificial intelligence has led to pioneering work—most recently the launch of diwo®, which was developed from the ground up as a “business-first” platform to address the adoption issues common with other transformative initiative

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

 Vishwa Kolla

Vishwa Kolla

AVP

John Hancock Insurance

Vishwa heads Advanced Analytics function at John Hancock Insurance. He is passionate about combining math and data to drive Business outcomes. Towards this end, he led several engagements that use ML and AI methods across 6 industries and in over a dozen F100 firms.


Vishwa is a thought leader and regularly speaks at conferences on a variety of topics - Analytics Architecture & Strategy, Internal and 3rd Party Data, Big Data Best Practices, Advanced Methods - opportunities & Pitfalls, AI-Led transformations, C[A, AI, D] O series - operating models, Underwriting Risk Analytics, Marketing Analytics and Mix Modeling, Fraud Analytics.


Vishwa received his 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

Formerly UPS (retired), now Chief Product Strategist

ESP Logistics Technology

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


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


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


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


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


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


Jack believes ESP can deliver similar gains to its customers. 


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


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


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


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


The role Jack enjoys the most is Grandpa.

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

Product Lead

Walmart Global Tech

Julia is a Fraud Detection and Risk Management expert, innovator, startup advisor, mentor and a speaker. Currently she is a Product lead at Walmart Global tech focusing on mitigating fraud for Mobile payments and Marketplace. Prior to this, Julia worked with Fiserv, Signifyd, ThreatMetrix, LexisNexis Risk Solutions and helped Fortune 50 Tech and E-Commerce companies such as Microsoft, Intuit, Ebay, Chegg and others to save millions of dollars in fraud losses.

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 Diploma from Stanford University.

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

VP of Machine Learning

Figure Eight

Jennifer has spent most of her career creating a data-driven culture wherever she went, succeeding in sometimes highly skeptical environments. She is particularly skilled at building and scaling high-performance Machine Learning teams, and is known for enjoying a good challenge. Trained as a particle physicist, she likes to use her analytical mind not only when building complex models, but also as part of her leadership philosophy. She is pragmatic yet detail-oriented. Jennifer also takes great pleasure in addressing both technical and non-technical audiences at conferences and seminars, and is passionate about attracting more women to careers in STEM.

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

Dr. Karl Rexer

Dr. Karl Rexer

President

Rexer Analytics

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

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

Chief Strategy Officer

Kinaxis

@agrobins

As Chief Strategy Officer, Anne is responsible for accelerating Kinaxis strategy development to add further value to customers. She and her team collaborates closely with customers, external stakeholders and the rest of the senior executive team to drive the strategic roadmap, thought leadership and identify emerging technologies and new industry opportunities.


A proven leader in analytics and digital transformation, with expertise in operations, supply chain, and strategy, Anne has extensive experience in managing supply chains for complex, global organizations. As Executive Director, Global Supply Chain Strategy, Analytics and Systems at Verizon, Anne was responsible for the strategic vision of the company’s global end-to-end supply chain, driving excellence through world-class data-analytics, process innovation and employee empowerment. Before Verizon, Anne spent several years at Cisco where she was responsible for managing advanced analytics, business intelligence and performance management teams.


Anne is a past president of INFORMS (the Institute for Operations Research and Management Sciences), a seasoned industry speaker and has served on several advisory boards. Originally from St. John's, Newfoundland and Labrador, Anne has a BScH from Acadia University, MASc from the University of Waterloo and an MSc and PhD in Industrial Engineering from Stanford University.

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

Dr. Eric Siegel

Dr. Eric Siegel

Conference Founder

Machine Learning Week

@predictanalytic

Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.


Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

Session:  Conference Chair Welcome
Session:  Uplift Modeling: Optimize for Influence and Persuade by the Numbers

 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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