May 14-18, 2017
San Francisco, CA
Delivering on the promise of data science
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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, in San Diego, California. Mr. Abbott is an internationally recognized data science and predictive analytics expert with over three decades of experience. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming in 2020. He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Session: The Revolution in Retail Customer Intelligence

 Anwar Adil

Anwar Adil

Data Engineer

MapR

Anwar is a data engineer for MapR, where he is working on solving day to day big data problems. For the past six years, Anwar has worked in software development and data analysis for a variety of companies, including Stanford University, DST, USDA, and NIPR. Anwar's main interests are in the fields of data science, data engineering and software engineering. Anwar holds a Master's Degree in Computer Science from the University of Missouri in Kansas City.

Session: Hadoop for Predictive Analytics - A Data Scientist's Secret Weapon Against Malware Threats

 Matt Bentley

Matt Bentley

Founder

CanIRank.com

@matt_bentley

Matt Bentley is the Founder of CanIRank.com, an online marketing tool that uses predictive analytics to determine the highest impact online marketing opportunities for any website. He is also the Founder of Pretarget.com, a customer profiling and lead scoring service focused on the internet services industry. Matt stumbled upon predictive analytics in 2009 thanks to a fortuitous meeting with Dean Abbott of Abbott Analytics, and since then has focused his career on developing or assisting startups leveraging predictive analytics to make data more actionable.

In the dark ages before discovering predictive analytics, Matt was CEO of Sedo.com, a domain name marketplace and monetization service where he developed expertise in online ad targeting and revenue optimization, among other less useful skills. Matt studied Decision Analysis at Stanford University and International Finance at École Supérieure de Commerce de Marseille Provence.

Session: Predicting Online Marketing Success: Five Lessons Learned

 Julian Bharadwaj

Julian Bharadwaj

Data Scientist

Google

Julian is a Data Scientist supporting the Marketing teams in Google. His primary focus is using ML Models to solve difficult problems in the Marketing space. He holds a Bachelor's degree in Mechanical Engineering and a Masters in Industrial Engineering from Texas A&M University. He currently resides in California.

Session: eCommerce Churn - from Definition to Prediction to Reactivation

 Joseph Brandenburg

Joseph Brandenburg

CEO and Chief Data Scientist

Analytics4Retail

Joe Brandenburg is the current CEO and Chief Data Scientist at Analytics4Retail, a leading advanced analytics firm serving the Retail and CPG industries based in Skokie, Illinois and Dallas, Texas. Prior to Analytics4Retail, Joe was the Chief Data Scientist and Predictive Analytics Practice Leader at Dunn Solutions Group and the former President of JB Strategic Research. Joe has managed and performed predictive analytics and advanced analytics for some of the largest banks, insurance, CPG and retailers in the world. Joe has also headed the marketing mix practice for IRI and invented many of their technologies. Throughout his professional career, Joe has won many awards and often published for his work in Marketing Mix and Predictive Analytics and strives to be on the cutting edge of technology in the area of predictive analytics. Joe is an expert in data mining, marketing mix, price optimization, media mix, demand forecasting, customer segmentation, and predictive modeling. Joe holds an MBA in Business Research and Marketing from Western Illinois.

Session: Caught in The Act: Loss Prevention Rules Firing & Alerts

 Clinton Brownley

Clinton Brownley

Data Scientist

WhatsApp

@ClintonBrownley

Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

Session: Predictive Analytics on the Command Line

 Clement Brunet

Clement Brunet

Director, Research & Analytics

The Co-operators

@ClemBrunet

Clement Brunet is the Director of Research and Analytics at The Co-operators Insurance in Canada, where he is responsible for all research and development related to analytics for risk modeling, response and attrition modeling, pricing, operational process optimization, and other data driven applications. He has 17 years of experience in BI and holds a bachelor degree in mathematics from University of Montreal and an MBA from HEC Montreal. He founded and managed analytics competency centers in two of the top 10 major Canadian insurance companies.

Session: Developing an Analytics Practice and a Science Culture in Insurance

 Peter Bull

Peter Bull

Co-founder

DrivenData

Peter is a co-founder at DrivenData, whose mission is to bring the power of data science to the social sector. Recently he has worked on projects in smart school budgeting, predicting trends in women's healthcare, and improving public services by using novel data sources. He earned his master's in Computational Science and Engineering from Harvard in 2013. Previously he worked as a software engineer at Microsoft and earned a BA in philosophy from Yale University.

Session: Predicting Restaurant Violations via Yelp Reviews: Crowdsourcing for Social Good

 Lawrence Cowan

Lawrence Cowan

Senior Partner & COO

Cicero Group

@Cicero_Group

Lawrence is Senior Partner, COO and Customer Insights & Advanced Analytics practice leader with Cicero Group. Lawrence has spent the last decade building Cicero's analytics practice where he has experience helping Fortune 1000 firms solve real business challenges with data, including attrition, segmentation, sales prioritization, pricing, and customer satisfaction. He also leads the firm in predictive analytics and Big Data related engagements, applying Cicero’s deep expertise in strategy execution to ensure data delivers ROI.  He has partnered with companies to help them to shift from reactive to predictive analytics by collecting and analyzing real-time information and distributing it across the organization— allowing management to make better, faster decisions that move the business forward.


Lawrence holds a Master’s of Science in Predictive Analytics from Northwestern University, an MBA with an emphasis in Business Economics from Westminster College, and a BA from Brigham Young University

Session: Predicting the Extent and Cost of Online Attacks to Help Sell Security Software

 Gourab De, PhD

Gourab De, PhD

Vice President of Data Science

DataRobot

Dr. Gourab De is the Vice President of Data Science at DataRobot, where his primary focus is helping customers improve their ability to make and implement predictions. Previously, De was part of the data science team at Ginger.io focusing on behavioral analytics in mental health. His professional experience includes statistical genetics, clinical trials, retrospective claims analysis, chart review studies, predictive modeling and pharmacoeconomic modeling. De graduated with honors from the Indian Statistical Institute in Kolkata, India, and received a Ph.D. in Biostatistics from Harvard University.

Diamond Sponsor Presentation: DataRobot: Better Prediction. Faster

 Paul DiMarzio

Paul DiMarzio

Worldwide Portfolio Marketing Manager, z Systems Analytics

IBM

@PaulD360

Paul has 30+ years experience with IBM focused on bringing new and emerging technologies to the mainframe. he is currently responsible for developing and executing IBM's worldwide z Systems big data and analytics portfolio marketing strategy, including the role of z Systems in IBM's Cognitive and Internet of Things (IoT) businesses.

Lunch & Learn: Using Apache Spark on the Mainframe to Reduce Fraud in the Financial Sector

 Pedro Domingos

Pedro Domingos

Professor

University of Washington

@pmddomingos

Pedro Domingos is a professor of computer science at the University of Washington in Seattle. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. He is a Fellow of the Association for the Advancement of Artificial Intelligence, and has received a Fulbright Scholarship, a Sloan Fellowship, the National Science Foundation's CAREER Award, and numerous best paper awards. He received his Ph.D. from the University of California at Irvine and is the author or co-author of over 200 technical publications. He has held visiting positions at Stanford, Carnegie Mellon, and MIT. He co-founded the International Machine Learning Society in 2001. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science, including scaling learning algorithms to big data, maximizing word of mouth in social networks, unifying logic and probability, and deep learning.

Session: The Five Tribes of Machine Learning, and What You Can Take from Each

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: Doing Space-Age Analytics with Our Hunter-Gatherer Brains

 Ken Elliott

Ken Elliott

Global Director of Analytics

Hewlett Packard Enterprise

@ken_e_elliott

Ken has over 25 years of experience delivering analytic solutions. He started his career in analytics at SPSS, where he served for 14 years most notably as the Vice President of Analytic Solutions and Professional Services. From there, Ken co-founded an analytics consulting practice focused on the convergence of Market Research and Enterprise Data for holistic customer intelligence.


For the past 12 years, Ken has been with Hewlett Packard holding leadership positions within Global Business Intelligence IT, Global Analytics and Enterprise Services. He is currently the Global Director of Analytics within Hewlett Packard Enterprise Services. Ken holds a Ph.D. in Industrial Psychology (with a focus on analytics of course).

Session: Operationalizing Analytics: 10 Key Process Areas for Embedding Predictive Analytics into Business Operations, Applications and Machines

 Vladimir Giverts

Vladimir Giverts

Senior Director of Engineering

Workday

Vlad Giverts is a Sr Director at Workday where he runs the teams building machine learning and advanced analytics applications for the company\'s HR and Financial management products.

He is also a Partner at Workday Ventures where he focuses on Machine Learning startups.

He was previously the CTO at Identified, a predictive analytics startup in the recruiting space acquired by Workday in early 2014.

Vlad holds a bachelor's degree in Computer Science from UC Berkeley.

Session: Time-Series Feature Engineering Done Right

 Anthony Goldbloom

Anthony Goldbloom

Founder & CEO

Kaggle

@antgoldbloom

Anthony Goldbloom is the founder and CEO of Kaggle. In 2011 & 2012, Forbes Magazine named Anthony as one of the 30 under 30 in technology, in 2013 the MIT Tech Review named him one of top 35 innovators under the age of 35 and the University of Melbourne awarded him an Alumni of Distinction Award. He holds a first call honors degree in Econometrics from the University of Melbourne. Anthony has published in the The Economist and the Harvard Business Review.

Session: What's possible at the cutting edge of predictive modeling

 Ivan Judson

Ivan Judson

Senior Software Engineer

Microsoft

@irjudson

Ivan R. Judson is a Senior Engineer at Microsoft. While at Argonne National Laboratory he built high performance computing systems, large format projection displays, and advanced collaborative workspaces. At Montana State University he taught undergraduate and graduate Computer Science and created the Research Computing Group to consolidate, stabilize, and productionize compute and data management services for the $100M research enterprise. He left the university to open an office for Workiva (formerly WebFilings) in Bozeman, MT recruiting 40 of the top developers in the area and establishing five product teams. Ivan has also worked in wireless and mesh technology, earning his Doctorate for work in Resource Allocation Algorithms in Cognitive Wireless Networks. Ivan's current focus is in Mesh Networking, Edge Computing and the Internet of Things, with a focus on connecting devices and extracting actionable knowledge from the data through machine learning.

Session: Predictive Analytics @work inside Microsoft: Revenue Modeling & Predictive Maintenance

 Kim Larsen

Kim Larsen

VP of Data

ThirdLove

Kim Larsen is the VP of Data at ThirdLove. Kim has experience working in the software and consulting industries, as well as e-commerce and financial services. Throughout his career, he has managed a wide array of data mining and analytical problems including price optimization, media mix optimization, demand forecasting, customer segmentation, and predictive modeling. Kim frequently speaks at data mining conferences around the world in the areas of segmentation and predictive modeling. His main areas of research include additive non-linear modeling and net lift models (incremental lift models).

Keynote: Keys to Growing a World Class Data Science Team - Some Observations from Stitch Fix

 Joshua Liberman

Joshua Liberman

Executive Director Research, Development, and Dissemination

Sutter Health

Since 2012, Josh has provided strategic and operational leadership for RDD, focusing on designing and implementing a variety of health care solutions, emphasizing the use of data and advanced analytics, technologies, and workflow redesign to help make health easy and affordable. Prior to Sutter, Josh was the VP, Research Operations for Geisinger's Center for Health Research and the VP, Strategic Research, CVS Health. Josh received his PhD in Epidemiology (Bloomberg School of Public Health); Master of Health Science in Occupational & Environmental Epidemiology; and Bachelor of Arts in Natural Science—Public Health, all from The Johns Hopkins University.

Session: Overcoming Big Data Bottlenecks in Healthcare: A Predictive Modeling Case Study

 Gian Merlino

Gian Merlino

Co-founder

Imply

Gian is a committer on the Druid project and co-founder at Imply. Previously, as a senior software engineer at Metamarkets, he was responsible for the infrastructure powering real-time data processing and ingestion. Gian holds a BS in computer science from the California Institute of Technology.

Session: Open Source Lambda Architecture with Druid, Kafka, Samza, and Hadoop

 Avishkar Misra, Ph.D

Avishkar Misra, Ph.D

Chief Data Scientist, Big Data Pursuit Team

Oracle

As the Chief Data Scientist with Oracle's Big Data Pursuit Team, Avishkar Misra helps customers realize the value Big Data and predictive analytics can bring to their organization. His research & development experience spans online retail and advertising, cloud computing, defense and flight simulation & training, as well as medical research. Prior to Oracle he was a machine learning scientist at Amazon, building real-time predictive modeling systems for advertising and product recommendations. Avishkar holds a PhD from University of New South Wales, where he developed techniques to incrementally engineer medical vision systems, enabling them to learn and improve over time.

Diamond Sponsor Presentation: Enabling Data Science for Lambda, Lakes and Bases
Expert Panel: Data Prep: Overcoming the Bottleneck and Nailing It

 Mukund Mohan

Mukund Mohan

Director

Microsoft Strategy

@mukund

Mukund Mohan helps startups at Microsoft Ventures. He founded and sold BuzzGain in 2011. He has founded and successfully sold 3 Silicon Valley startups in the Internet & Enterprise software markets. Mukund has held executive and management roles in Hewlett Packard (Mercury), and Cisco Systems. He studied at the University of Maryland, Baltimore County pursuing a Master's degree in Computer Science and holds a Bachelor's degree in engineering and computer science from the University of Mysore in India. Mukund blogs at http://www.bestengagingcommunities.com.

Session: Predicting Startup Success: Finding the Unicorns among Wildebeests

 Tatsuo Nakamura

Tatsuo Nakamura

CEO

VALUENEX

Dr.Tatsuo Nakamura is the founder and CEO of VALUENEX, Inc., created after almost 20 years as a distinguished consultant and thought leader in Japan's scientific establishments. He worked as a consultant in the prestigious Mitsubishi Research Institute for 15 years, focusing on his specialties of operations research, intellectual property, and data mining. Additionally, he was an Assistant Professor at the University of Tokyo and Waseda University. During his time as a consultant, he developed the algorithm that eventually became XLUS TechRadar, a panoramic view analytics and researching tool that provides a radar visualization of patent similarities. This was a dramatic innovation in the area of intellectual property. He established VALUENEX as one of the leaders in this field with a long list of clients that includes over 50 top companies in Japan. In 2014, he established VALUENEX,Inc. in Menlo Park, CA, to lead the company's entry into the USA market.

Gold Sponsor Presentation: How Can We Find the Future on the RadarMap of Big Data?

 Ming Ng

Ming Ng

Principal Data Scientist

Ming is a Principal Data Scientist at Linkedin, where she and her team are responsible for building and delivering a wide variety of analysis focus on understanding, increasing growth, retention and engagement at Linkedin. Prior to joining Linkedin, she worked at Cisco System, AT&T and University of California at Santa Barbara. Ming holds a Masters in Computer Science from the State University of New York at Stony Brook, where she studied automated theorem proving.

Session: Leveraging an Erroneous Treatment. Did We Wake Sleeping Dogs, Reactivate Engagement or Do Nothing at All?

 Haile Owusu

Haile Owusu

Chief Data Scientist

Mashable

@hailekofi

Haile Owusu is Chief Data Scientist at Mashable where his main responsibility is the development and refinement of the company's proprietary Velocity technology, which predicts and tracks the viral life-cycle of digital media content. Haile specializes in statistical learning as applied to predictive analytics and has a background in theoretical physics, including a Ph.D from Rutgers University, a Masters of Science from King's College, University of London and a B.A. from Yale University.

Session: Understanding Viral Diffusion: Data Science at Mashable

 Paddy Padmanabhan

Paddy Padmanabhan

CEO

Damo Consulting, Inc

@PaddyPadmanabha

Paddy Padmanabhan: CEO of Damo Consulting Inc, an advanced analytics consulting company focused on healthcare.Prior to founding Damo Consulting, he was a part of Accenture's Healthcare practice. He has also been in two silicon valley start-ups focused on healthcare analytics. Paddy is a frequent writer and speaker on information technology in healthcare.

Session: Overcoming Big Data Bottlenecks in Healthcare: A Predictive Modeling Case Study

 Rebecca Pang

Rebecca Pang

Senior Director, Channel Strategy & Analytics

CIBC

Rebecca Pang is the senior director of channel strategy and analytics for CIBC, where she leads the retail channel analytics team to develop and evaluate strategic programs or initiatives related to integrated channel strategy. Prior to the current role, Pang was working in the mergers and acquisitions, investment banking and Strategy & Corporate Development teams at CIBC. Pang has also worked as a senior manager for T-Mobile USA, an investor relations officer for China Netcom in Beijing and a business analyst for McKinsey and Company in Hong Kong.

Pang earned her honours bachelor of business administration from the Chinese University of Hong Kong, and then served as an HSBC scholar at Columbia University. She received her MBA from Stanford University's Graduate School of Business and later earned her Chartered Financial Analyst and Chartered Business Valuators designations.

Session: Driving the Omnichannel Experience with Predictive Analytics

 Ruban Phukan

Ruban Phukan

CoFounder & Chief Products and Analytics Officer

DataRPM

Ruban is a serial entrepreneur and technologist with rich and diverse experience in data science, product, technology and business. As a data scientist in Yahoo, Ruban's role involved data mining and analyzing several big data sets of Yahoo and coming up with strategic business insights. His projects influenced several products & business strategies and led to tens of millions of dollars of positive revenue impact. He co-founded Bixee, a leading vertical search company in India where his patent-pending CrawlX technology revolutionized vertical specific information retrieval from unstructured data. He also created Pixrat, a social photo sharing destination. Ruban sold Bixee and Pixrat to Ibibo, a Naspers Group company, where he became the Vice President of Social Media and helped grow Ibibo to become one of the leading social media destinations in India with several millions of active users, prior to co-founding DataRPM.

Gold Sponsor Presentation: Cognitive Data Science for Predictions

 Jim Porzak

Jim Porzak

Principal

DS4CI.org

Jim is a semi-retired data scientist specializing in data-driven customer insights. He is currently engaged by One Medical (San Francisco), Li and Fung (Hong Kong), and Leitersburg Cinemas (MD). In 2015 he focused on Lynda.com (a LinkedIn/Microsoft company). Past experience includes Minted.com, Ancestry.com, Responsys, LA Times, 24 Hour Fitness and Sun Microsystems, to name a few.

Jim specializes in using customer behavioral and demographic data to predict propensity to purchase and/or churn, do uplift modeling, segment customers based on cluster analysis, and do routine marketing analytics. Jim is very active in the open-source community; particularly with R-the open-source software environment for statistical computing and graphics. He is a frequent speaker at conferences in the US & Europe.

Session: Leveraging an Erroneous Treatment. Did We Wake Sleeping Dogs, Reactivate Engagement or Do Nothing at All?

 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: How Well Do You Really Know Your Customer?
Q+A: Ask Karl and Steven Anything (about Best Practices)

 Karl Rexer

Karl Rexer

President

Rexer Analytics

Karl Rexer founded Rexer Analytics in 2002.  He and his teams provide predictive modeling and analytic consulting to clients across many industries.  Recent clients include PwC, Boston Scientific, Redbox, ADT
Security, Interamericana University, MIT, A.S.Watson, 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.  Several software companies have sought Karl's input, and in 2008 and 2010 he served on SPSS's (IBM) Customer Advisory Board.  He also served 11 years on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group.  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
Q+A: Ask Karl and Steven Anything (about Best Practices)

 Yohai Sabag

Yohai Sabag

Chief Data Scientist

Optimove

Yohai Sabag is Optimove's Chief Data Scientist,responsible for Optimove's data lab, where he leads a team of data scientists developing advanced customer modeling algorithms and predictive analytics technologies. He is a distinguished data expert with extensive experience in both the academic and business worlds, applying the fields of business intelligence and advanced data analytics to practical business challenges. He has conducted thousands of hours of research in the fields of machine learning, data science applications and advanced statistics. Yohai, previously a member of faculty in the engineering department at Israel's Ben Gurion University, holds degrees in applied statistics, machine learning and information systems.

Expert Panel: Data Prep: Overcoming the Bottleneck and Nailing It

 Babacar Seck

Babacar Seck

President

LEADS AEROSPACE

Avid traveller, coffee drinker, car sports follower, cinephile, and techie. I have a passion for bringing products to life and turning ideas into reality. I'm currently focused on developing start up companies that create substantial value by attracting and federating highly skilled and motivated people and partners around innovative projects.

I'm currently leading a high technology company specialized in developing innovative and secure mobile communications solutions using the most advanced satellites constellations and ground networks. Our primary market is Aviation - Air transportations Industry, Defense and Aerospace.

With nearly 18 years developing strategic innovative projects applied to Information technology, mobile telecom services and critical satellites communications solutions for leading European companies, my experience ranges from business planning to strategic implementation through cross-functional leadership positions.

Session: Optimizing Model-Based Risk Management in the Aviation Industry

 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.

Expert Panel: Data Prep: Overcoming the Bottleneck and Nailing It

 Michael Spadafore

Michael Spadafore

Analytics Director

Marketing Associates

Mike has 20+ years experience developing advanced analytic, technical, and business process solutions to solve complex marketing problems. Mike has been instrumental in driving key innovations in the automotive marketing and analytics services sector including advanced safety recall, analytically driven real time marketing, retail marketing analytics and customer communications, and extending traditional CRM into the digital, multi-channel ecosystem. Mike is a frequent speaker on advanced automotive marketing and analytics including JD Power AMR, DMAD Automotive Integrated Symposium, TLS Customer Centricity, and WardsAuto's Dealer Business. Mike received his BS from the University of Michigan and has a Kellogg MBA.

Session: Predicting Consumer Review Engagement and Sentiment Using only Readily Available Social and Demographic Data

 Peter Stansbery

Peter Stansbery

Audit Analytics Manager

GE Corporate

Peter Stansbery is an Audit Analytics Manager in GE's Corporate Audit Staff and an experienced change agent driving transformation and analytics adoption in Internal Audit organizations. He is a predictive analytics professional with a background in connecting analysis to business outcomes. He began his career at KPMG Advisory as an Internal Audit Consultant, where as a core member of the National data analytics initiative, he was a leader in the training and enablement pillar for analytics capability within the firm's Risk Consulting Practice.

At GE, he is a member of the Data Analytics Center of Excellence, serving as a hands-on project leader and contributor, technical coach and Digital cultural leader in the transformation of analytics for the Corporate Audit Staff. His career has been focused primarily in the manufacturing and retail sectors, and his technical expertise is focused on text mining and prediction, risk identification and automation.

Session: Advanced Analytics and the Corporate Audit Function

 Adam Sugano

Adam Sugano

Head of Predictive Modeling and Advanced Analytics

Autodesk

Adam Sugano serves as the Head of Predictive Modeling and Advanced Analytics at Autodesk. In this role, he leads a team of both internal and external data scientists charged with delivering innovative, actionable data driven solutions that help empower Autodes's customer retention and engagement optimization efforts across the customer lifecycle.

Prior to joining Autodesk, Adam was the Director of Analytics for Experian Marketing Services™ Cross-Channel Marketing organization where he leaned on his quantitative marketing background to help clients understand the value of customer intelligence and delivered tailored marketing analytics solutions. He has also worked as a statistician at MySpace and Farmers Insurance, a lecturer within UCLA's Department of Statistics, as well as a consultant to the Los Angeles Dodgers.

Adam holds a B.S. in Mathematics, a M.S. in Biostatistics, and a Ph.D. in Statistics, all from the University of California at Los Angeles.

Session: Adopting Analytics - The Autodesk Journey

Dr. Patrick Surry

Dr. Patrick Surry

Chief Data Scientist

Hopper

@PatrickSurry

As Chief Data Scientist at Hopper, Patrick Surry analyzes flight data to help consumers make smarter travel choices. Patrick is recognized as a travel expert and he frequently provides data-driven insight on the travel industry and trends.


Patrick’s research and commentary have been featured in outlets such as New York Times, USA Today, Bloomberg Businessweek, TIME, and many others. Patrick also regularly appears on various broadcast stations to offer travel insight and tips.


Patrick holds a PhD in mathematics and statistics from the University of Edinburgh, where he studied optimization based on evolutionary algorithms, following an HBSc in continuum mechanics from the University of Western Ontario.


You can also follow Patrick on Twitter at @PatrickSurry.

KEYNOTE: Buy or Wait? Consumer-friendly Airfare Prediction or How the Bunny Saves You Money
Session: Applying Next Generation Uplift Modeling to Optimize Customer Retention Programs

 Sundar Victor

Sundar Victor

Data Scientist

GE Corporate

Sundar Victor is a Data Scientist in GE Corporate, he began his career in 2003 developing/applying analytical methods & approaches in the field of proteomics and biomedical for patient care focused on treating infectious disease at UT Medical Galveston. After joining General Electric analytics COE in 2011, he has been instrumental in infusing data science approaches, bringing the change culture in audit staff & responsible for implementing the same in audit to identify fraud, risk, & drive business process, compliance and profitability. He holds a Bachelors in Engineering & Masters in Biomedical Engineering from University of Texas Arlington.

Session:Advanced Analytics and the Corporate Audit Function

 Mario Vinasco

Mario Vinasco

Marketing Analytics Data Scientist

Facebook

Mario Vinasco has over 18 years of progressive experience in data driven analytics with emphasis in database programming and predictive models creatively applied to eCommerce, advertising, customer acquisition/retention and marketing investment. Mario specializes in developing and applying leading edge business analytics to complex business problems using big data platforms, including Hadoop, columnar and traditional relational models.

Mario holds a Masters in engineering economics from Stanford University and currently works for Facebook as data scientist in the consumer marketing group; in this role he is responsible for improving the effectiveness of Facebook's own consumer-facing campaigns.

Key projects include ad-effectiveness measurement of Facebook's brand marketing activities, and product campaigns for key product priorities using advanced experimentation techniques.

Prior roles included VP of business intelligence in digital textbook startup, people analytics manager at Google and eCommerce Sr manager at Symantec.

Session: Advanced Experimentation in Social Networks

 Nate Watson

Nate Watson

President

Contemporary Analysis

Nate became president of Contemporary Analysis in 2015. Prior to president, Nate was head of project management and business development and led the development of the political division of CAN as well as the IOT division of CAN. He specializes in helping non-technical business leaders understand what results and manages the change management necessary to implement proactive business planning, predictive maintenance, and data driven decision making into company culture.

In his free time, Nate gives back to his community by leading a city-wide cancer fundraiser each summer, serving on multiple boards, advises startups on sales growth and networking, and supports many local political campaigns. He also loves to spend time with his wife and new daughter playing in the park and going to the zoo.

 Hans Wolters

Hans Wolters

Principal Data Scientist

Microsoft

@hans_wolters

Hans Wolters is a Principal Data Scientist within the Windows and Devices Group at Microsoft. He received an M.S in Applied Math from the University of Goettingen, Germany and a Ph.D. in Computer Science from Arizona State University. Hans joined Microsoft's Xbox Division in 2012 where he was responsible for several features of the XBoxOne console. Prior roles included Sr Scientist at HP Labs, Head of Bioinformatics and Bio-statistics at XDx and Principal Data Scientist at Zynga where he built the foundations for making game play more personalized.

Session: Changing the Paradigm: The Role of Analytics in Moving to
Windows as a Service

 Jing Zhu

Jing Zhu

Risk Modeling Analyst

Paychex Inc.

Jing Zhu is a Risk Modeling Analyst at Paychex Inc., a leading provider of payroll, human resource, insurance, and benefits outsourcing solutions for small- to medium-sized businesses. Jing's main responsibility is developing models to help with strategic decisions across all aspects of the business, including effectively targeting retention strategies, assisting in dynamic cross-sell initiatives, and improving collection targets. Jing holds a PhD in Biology from the University of Rochester, where she applied statistics in biological research.

Session: Maximize Value and Retention With Predictive Analytics In Discounting

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