May 14-18, 2017
San Francisco
Delivering on the promise of data science
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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
Workshop: Supercharging Prediction with Ensemble Models
Workshop: Advanced Methods Hands-on: Predictive Modeling Techniques

 Gary1 Anderberg

Gary1 Anderberg

SVP, Claim Analytics

Gallagher Bassett

Gary is a recovering academic with a BA from Pomona College and an MA and a PhD from Stanford University. He moved from college and university teaching into management consulting in 1976 and later joined one of his clients, a TPA, as their first vice president of data processing. He formed and later sold his own TPA then joined Travelers as part of the team that built one of the first managed care programs for workers compensation. After a stint at Zenith National as one of the designers of the SinglePoint twenty four hour program, he joined Prudential's Group Insurance operation to develop integrated disability management. After retiring from Prudential, Gary joined Broadspire to develop the e-Triage claim modeling system. He was recruited by Gallagher Bassett in 2013 to drive research and development into new technologies to improve outcomes.

Session: Finding the Waypoint: A TPA and an Actuary with Predictive Analytics Reinvent Reserving (and it's not boring after all)

 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: Enhancing the Quality of Predictive Modeling on College Enrollment

 Natasha Balac, Ph.D.

Natasha Balac, Ph.D.

CEO and Founder

Data Insight Discovery, Inc

Natasha received her Master's and Ph.D. in Computer Science from Vanderbilt University with an emphasis in Data Mining from large data sets. Her dissertation focused on creating and applying novel data mining techniques to mobile robots and real time sensor data. She has been with UCSD since 2003. She has also led multiple collaborations across a wide range of organizations in industry, government and academia. She had founded and led the Predictive Analytics Center of Excellence at the Supercomputer Center until 2016. She is currently directing the Interdisciplinary Center for Data Data Science (ICData) at Calit2/Qualcomm institute and lectures at the computer Science Department. Dr. Balac has a number of large and multidisciplinary government and research funded projects including the Center for Medicaid and Medicare Services, NASA, NSF, CPUC, Smart Grid, Smart City, etc. Dr. Balac has founded and serves at the President and CEO of Data Insight Discovery, Inc. DID's charter is enabling businesses to discover actionable insight from vast amounts of data across verticals.

Session: Identifying Unique Gamer Types Using Predictive Analytics

 Ashish Bansal

Ashish Bansal

Director Recommendations Systems

Twitch

Ashish manages Events recommendations and trends at Twitch. He uses AI/ML to generate insights from vast amounts of data and build interesting B2C, B2B and enterprise products. He has over 20 years of experience in technology ranging from founding startups to large companies. He has an MBA in marketing from Kellogg School of Management and a B.Tech from IIT BHU, India.

Session: The Quest for Labeled Data: Integrating Human Steps

 Bryan Bennett

Bryan Bennett

Professor

Northwestern Sps

Bryan Bennett is a professor for Northwestern University's School of Professional Studies where he is a predictive analytics subject matter expert and is responsible for the development and teaching of predictive analytics courses domestically and internationally. Additionally, he teaches leadership, healthcare marketing and consumer behavior courses at the graduate and undergraduate levels for other Universities.


Professor Bennett is also the Executive Director for the Healthcare Center of Excellence (healthcarecoe.org), a privately-funded healthcare research and consulting firm, where he researches and consults on transformation, advanced analytics and leadership issues for healthcare organizations. He is the author of the books, "Competing on Healthcare Analytics: The Foundational Approach to Population Health Analytics" and "Prescribing Leadership in Healthcare", as well as contributing the Data Stewardship chapter to the book "Adaptive Health Management Information Systems".


Bryan's work has appeared in several publications such as, DM News, Health Data Management, Becker's Hospital Review and Capco's Journal of Financial Transformation.

Session: Need a Data Scientist, Try Building a "DataScienceStein"

 Jennifer Bertero

Jennifer Bertero

VP, Business Analytics

CA Technologies

Jennifer Bertero is a strategic leader with visionary passion for building high-performing organizations and leading transformation. She is focused on serving the changing needs of the customer while driving growth and profitability. Her areas of business expertise include analytics and big data, business relationship and corporate development, cloud computing, product and digital digital marketing, customer engagement and sales productivity.


Jennifer is currently the VP of Business Analytics at CA Technologies where she leverages her unique blend of business expertise, advanced analytics and program development to drive strategic planning and continuous improvement horizontally across all lines of business in the company.


Prior to CA, Jennifer held various leadership roles at global software firms like Hewlett Packard, Symantec and Yahoo, helping to transform and train multi-cultural sales and product marketing teams and increase the top line for a portfolio of software products.


Jennifer holds an MA in International Studies at Boston College, Diplome from La Sorbonne in Paris and speaks several languages including Italian, French and several others conversationally. She is very comfortable in a global environment and has built a deep cross-cultural wealth of knowledge that she continues to cultivate.

Session: Redefining Analytics for Marketing

 Karan Bhalla

Karan Bhalla

VP, Analytics

EXL Analytics

Karan is responsible for the development and implementation of the IQR (an EXL Analytics company) services, marketing and business strategies worldwide. At IQR Consulting, now a part of market leader EXL Analytics, he has led complex consulting engagements for banks and credit unions. He has 16 years of experience in Financial Services but he has been instrumental in leading IQR to expand its expertise and best practices to other industries as well. He is a graduate in Management Information Systems from Virginia Tech and an MBA in Finance from the University of Maryland. He started his career spending 6 years at Capital One in their data analysis & credit review functions. He has also been a consultant at some top organizations like Fannie Mae, American Express, and British Telecom. Karan has spoken about usage of analytics at many international conferences.

Session: The What and The How Matter When Talking to Customers - Even More Today

 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: Machine Learning Models for Assessing Third Party Signals

 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: Predicting Churn - An Often Not-So-Easy Task

 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: Predictive Analytics for Yield Management

 Abhi Butchibabu

Abhi Butchibabu

Product Manager

gradient A.I.

Abhi Butchibabu is a Product Manager at gradient A.I. (formerly MillimanMax), a predictive analytics startup based in Cambridge, MA. She received her Master’s and PhD from MIT in human-AI interaction, where she studied methods to build computational models to integrate autonomous systems seamlessly into human teams, particularly in complex and safety critical domains. As a product manager at gradient A.I., Abhi is focused on leveraging machine learning as a tool to deliver impactful products to customers in healthcare and insurance sectors. She also has experience designing products in the air transportation domain for airline and corporate pilots interacting with highly autonomous and complex systems.

Session:  Finding the Waypoint: A TPA and an Actuary with Predictive Analytics Reinvent Reserving (and it's not boring after all)

 Sandip Chatterjee

Sandip Chatterjee

Vice President of Product Development Advanced Analytics & Digital

Gallagher Bassett

Sandip is a product leader at Gallagher Bassett with 20+ years of experience. In his current role, he is responsible for driving superior claim outcomes for GB clients using innovative predictive decision support solutions. Sandip also leads the Digital products solutions portfolio that drives increased end user engagement and improves overall satisfaction with the claims process.

Prior to joining GB, Sandip worked as a management consultant at Gallagher Corporate and Deloitte Consulting focusing on business transformation initiatives and new product development to drive profitable growth for clients in the Insurance industry.

EDUCATION & CERTIFICATIONS:

University of Chicago, Booth School of Business - Chicago, IL MBA – Strategy and Finance

Illinois Institute of Technology - Chicago, IL Masters - Computer Science


Session: Finding the Waypoint: A TPA and an Actuary with Predictive Analytics Reinvent Reserving (and it's not boring after all)

 Morgane Ciot

Morgane Ciot

Data Visualization Engineer

DataRobot

Morgane Ciot is a data visualization engineer at DataRobot, where she specializes in creating interactive and intuitive D3 visualizations for data analysis and machine learning. Morgane studied computer science and linguistics at McGill University in Montreal. Previously, she worked in the Network Dynamics Lab at McGill, answering questions about social media behavior using predictive models and statistical topic models.

Expert Panel: Women in Predictive Analytics: Opportunities and Challenges

 Chemere Davis

Chemere Davis

Decision Scientist

Wells Fargo Bank, N.A.

Chemere Davis is a Decision Scientist with the Enterprise Advanced Analytics team at Wells Fargo Bank in Charlotte, North Carolina. She has over 9 years of experience in analytics and business intelligence in the retail and finance industries. She has spent the past several years working to evaluate emerging analytic technologies and using innovation to improve customer experience. She is passionate about storytelling with data and designing ways to make analytics accessible to audiences of various skill levels.

Chemere holds a BS in Health & Exercise Science from Wake Forest University and an MBA with a focus in Marketing Analytics from the University of North Carolina at Charlotte.

Session: Strategic Communication: Building a Bridge From Analytics to Business

 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: Automated machine learning with Dataroboto

 Michael Dessauer

Michael Dessauer

Data Scientist

The Dow Chemical Company

Michael Dessauer has been a data scientist in The Dow Chemical Company's Advanced Analytics team since 2010. In that time, he has partnered with many Dow global businesses and functions to develop statistical and machine learning models to improve market insight and increase margins. Michael leads the text analytics project team that has created custom solutions for consumer sentiment, new market identification, and contract analysis.

Session: Listening Down the Value Chain: Using Text-based Predictive Models to Find New Opportunities for B-to-B Businesses

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

 Angel Evan

Angel Evan

Founder

Angel Evan, Inc.

Angel Evan is a marketing consultant specializing in data and analytics. His approach to marketing stems from a unique combination of degrees held in both Data Mining and Graphic Design. This complement of skills gives him the rare ability to uncover and communicate insights by blending quantitative data with visual learning methods. His experience and skill set are sought after by startups and Fortune 100 companies alike. Angel currently teaches BUS 139: Data-Driven Marketing at Stanford Continuing Studies and is a frequent speaker at industry events and conferences.

Session: Identifying Unique Gamer Types Using Predictive Analytics

 Pete Foley

Pete Foley

CEO

Open Data Group

Pete is Chief Executive Officer at Open Data Group. Pete has over 20 years of experience driving growth in the technology industry. Prior to Open Data Group, Pete was the Executive Chairman of Graphite Systems, a low latency, flash-based, big data appliance which was acquired by EMC. Pete also served as CEO of RingCube Technologies, PortAuthority Technologies, and at Infoblox (NYSE:BLOX).

Session: Technical Abstractions for Lasting Analytic Deployment Competency

 Val Fontama

Val Fontama

Principal Data Scientist Manager

Microsoft

Val Fontama, is a Principal Data Scientist Manager in the AI Data Science team in C+E Growth, Analytics, and Billing group. His last role was Principal Data Scientist in Data & Decision Sciences Group (DDSG) where he led consulting to external customers, including ThyssenKrupp and Dell. Prior to Microsoft he was a New Technology Consultant at Equifax, London, where he pioneered the application of Data Mining to the Consumer Credit industry. Val holds an MBA from Wharton Business School, a Ph.D. in Neural Networks, M.Sc. in Computing, and B.Sc. in Mathematics and Electronics. He has published 11 academic papers, and co-authored three books including Predictive Analytics with Microsoft Azure Machine Learning: Build and Deploy Actionable Solutions in Minutes (2 editions).

Session: How Microsoft Predicted Churn of Cloud Customers Using Deep Learning and Explained Predictions in An Interpretable Way

 Chip Galusha

Chip Galusha

Data Scientist

Paychex Inc.

Chip Galusha is a data scientist at Paychex Inc., a leading provider of integrated human capital management solutions for payroll, HR, retirement, and insurance services. As a member of the data science and predictive analytics team, Chip harnesses the power of big data and statistical modeling to provide data driven intelligence that enhances strategic decision making. Chip has spent the greater part of the last 10 years working with data in a variety of fields, from e-commerce to public health. This has helped him develop a full view of data driven solutions, from ETL processes through model deployment. He holds a Master of Science in Statistics from the University of Vermont.

Session:Retention Modeling in Uncertain Economic Times

 Luba Gloukhova

Luba Gloukhova

Consultant & Speaker

Luba Gloukhova leads and executes advanced machine learning projects for high tech firms and major research universities in Silicon Valley. She also preaches what she practices, serving as the founding chair of Deep Learning World – the premier conference covering the commercial deployment of deep learning – and delivering highly-rated talks at many other events as well. Luba previously supported Stanford faculty as an internal consultant at the university's Graduate School of Business, conceiving and generating innovative solutions to accelerate research.


Before that, Luba gained industry experience in high frequency trading analysis, catastrophe risk modeling, and marketing analytics. She received her master’s in analytics from the University of San Francisco and two bachelors degrees from Berkeley: applied mathematics and economics. Luba also teaches yoga and enjoys an active lifestyle.

Expert Panel: Women in Predictive Analytics: Opportunities and Challenges

 Yanai Golany

Yanai Golany

Director of Supply Chain Strategy & Analytics

Verizon

Yanai Golany is the Director of Strategy & Analytics of Verizon's Global Supply Chain, leading advanced analytics, business intelligence and planning systems. Previously Yanai held several leadership roles in Verizon's wireline and wireless supply chain organization and in the defense industry. Yanai received his graduate degrees from MIT Sloan School of Management (MBA) and MIT School of Engineering (MS) as part of the Leader for Global Operations (LGO) Program. Prior to attending MIT, he received a Bachelor of Science in Industrial Engineering and Management from the Technion - The Israel Institute of Technology.

Keynote: The Right Analytics for the Job: Tips and Tricks for Success

 Sarah Guido

Sarah Guido

Senior Data Scientist

Mashable

Sarah is a Senior Data Scientist at Mashable where she studies user behavior through data. She is the chair of the Machine Learning/Artificial Intelligence track at the 2017 SciPy Conference and is an accomplished conference speaker. She is also an O'Reilly Media author, having co-authored "Introduction to Machine Learning with Python". Community involvement is very important to Sarah, and she is a co-organizer of the NYC Python Meetup, the largest Python meetup in the world. Sarah attended graduate school at the University of Michigan's School of Information. 

Keynote:  The Centrality of a Detailed Understanding of your Audience

 Frédérick Guillot

Frédérick Guillot

Senior Manager, Research and Innovation

Co-operators General Insurance Company

Frederick holds a bachelor and a master degree in actuarial science from Laval University. Since 2004, he is working for the Co-operators General Insurance Company, where he is currently Senior manager - Research and Innovation.

Since 2009, he is also a regular lecturer at Laval University, teaching principally predictive modeling. In 2014, he founded Actulab.ca, a not-for-profit organism with the mission to facilitate collaborations between academics and practitioners by offering case-competitions to Canadian students.

Session: Defining Optimal Segmentation Territories - 10 Years of Research

 Aarti Gupta

Aarti Gupta

Advanced Analytics Group

Bain & Company

Aarti Gupta is an expert in Bain & Company's Advanced Analytics Group. She is based at the firm's San Francisco office.

Aarti has nearly a decade of experience in advance analytics and customer insights. She works with consultants at all levels and in Bain offices all over the world, providing expertise and advice on various advance analytical solutions and tools.

She holds expertise in driver analyses, multi-variate regression models, segmentations, customer satisfaction, loyalty, in-market test & learn, retention and advanced regression applications. The industries that she has worked in include financial services, telecommunications, technology, healthcare, retail, consumer goods, hospitality, industrials and insurance.

Prior to Bain, Aarti worked as a senior statistical and predictive modeling consultant for an insurance firm. She holds an MS in Statistics from Indian Institute of Technology and an MS in Bio-statistics from the University of Maryland.

Expert Panel: Women in Predictive Analytics: Opportunities and Challenges

 Scott Hornbuckle

Scott Hornbuckle

Director, Advanced Analytics

Photizo Group


Scott first joined Photizo Group in 2008. He has served in multiple roles during his tenure, providing market analysis, proprietary research and custom consulting as the director of multiple advisory services including: TechWatch and Supplies Advisory Service. Scott has also served in a client engagement role, responsible for sales and support for global clients. In his most recent role as Director of Photizo's Advanced Analytics practice, Scott is focused on combining his financial experience with industry leading data analysis to help clients achieve better business outcomes. Scott has multiple degrees from the University of Kentucky in Accounting and Finance.

Session: Reducing Wasted Toner - Huge Savings for Service Providers and the Environment

 Darryl Humphrey, PhD, PMP

Darryl Humphrey, PhD, PMP

Senior Data Scientist

Alberta Blue Cross


Darryl is the Senior Data Scientist leading the team responsible for detecting fraudulent claiming patterns in health, dental, and pharmacy benefit claims. He has published on predictive model development using large scale data sets, cloud computing adoption strategies, and the evolution of enterprise architecture as a business strategy enabler. He has 20+ years experience as a management consultant having served public and private sector clients in Canada, USA, and Europe. While with Big 4 consulting firms, Darryl was a founding member of global analytics, cloud computing, enterprise architecture, and e-commerce practices.

Session: Claim Pattern Anomalies - Making a Mole Hill Out of a Mountain

 Jason Kessler

Jason Kessler

Lead Data Scientist

CDK Global

Jason Kessler is a lead data scientist at CDK Global, where he analyzes language use and consumer behavior in the online auto-shopping ecosystem. Prior to joining CDK, Jason was the founding data scientist at PlaceIQ and worked as a research scientist for JD Power and Associates. He has published peer-reviewed papers on algorithms and corpora for sentiment and belief analysis, and has sat on program committees and reviewed for several AI and NLP conferences. Most recently, he has conducted research on identifying persuasive and influential language and the visualization of differing corpora. Jason holds an MS and PhD candidacy in computer science from Indiana University, Bloomington.

Session: Discovering Persuasive Language through Observing Customer Behavior

 William Komp

William Komp

Principal Data Scientist

Komplytics LLC

William Komp is the Principle Data Scientist at Komplytics LLC.. He has over 2 decades of experience in academia, health care, marketing analytics, transportation, logistics, Oil&Gas, Food&Beverage, environmental management, renewable energy and public utilities. He was the technical editor for Applied Predictive Analytics (J. WIley and Sons 2014). He holds a PhD Physics with areas of research in Gravitation, Cosmology and Quantum Field Theory in Curved Spacetime.

Session: Automated Retail Analytics - Omni-Channel and at Scale

 Theresa Kushner

Theresa Kushner

Formerly Sr Vice President, Performance Analytics Group

Dell EMC

@tkushner

Theresa builds world-class teams that make data and the insight it provides vital to marketing and sales organizations. She has built teams across the high tech vertical from Texas Instruments to IBM, Cisco and VMware serving as both a manager and executive in marketing and today as VP of Enterprise Information Management. Theresa held Sr. Director Customer, Intelligence and various Marketing Management roles at IBM, Unify and Texas Instruments. One wish for MO is that all MO organizations should learn to capitalize on their unique view of the customer by working closely with their corporate IT and other business functions. Theresa's pastime is solving the NY Times Crossword puzzle every day.

Expert Panel Moderator: Women in Predictive Analytics: Opportunities and Challenges

 Jules Malin

Jules Malin

Manager, Product Analytics & Data Science

GoPro

Jules Malin leads a team at GoPro responsible for smart device and IoT analytics and data science. The team discovers product and behavioral insights from GoPro's growing family and ecosystem of smart devices, driving product and user experience improvements. This includes influencing and refining data pipelines in Hadoop/Spark and developing scalable machine learning data products, metrics and visualizations that produce actionable insights. Insights that support and enable data informed decision making across 20 teams, including Executive Staff, Finance, UX, QA, Engineering, Product Management and more. Prior to GoPro Jules worked at Intel and Shutterfly in Product Management and Analytics Engineering roles. He holds a Master's Degree in Predictive Analytics from Northwestern University.

Session: Making Better Products with Predictive Analytics

 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: Predicting Customer Churn in a Subscription Business

 Tina Owenmark

Tina Owenmark

Data Scientist

Cisco

Tina Owenmark is a data scientist at Cisco where she and her team create practical solutions that empower decision-making for internal customers across the enterprise. Her career has spanned both business and IT roles using corporate data and processes to bring insights and value to Cisco's business operations. Tina and the team work to foster and spread a diverse, decisions-oriented culture that puts business value first.

Session: The Role of Decision Modeling in Creating Data Science Excellence

 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.

Keynote: The Centrality of a Detailed Understanding of your Audience

Dr. Szilard Pafka, Ph.D.

Dr. Szilard Pafka, Ph.D.

Chief Scientist

Epoch

@DataScienceLA

Szilard has a PhD in Physics for using statistical methods to analyze the risk of financial portfolios. For the last decade he's been the Chief Scientist of a tech company in California doing everything data (analysis, modeling, data visualization, machine learning, data infrastructure etc). He is the founder of the LA R and LA data science meetup, the author of a well-known machine learning benchmark on github (1000+ stars), a frequent speaker at conferences (keynote/invited at KDD, R-finance, Crunch, eRum etc.), and he has developed and taught graduate machine learning courses at two universities (UCLA in California and CEU in Europe).

Session: Data Science Hype vs Reality: "Big Data" vs Single Machine Tools

 Ash Pahwa

Ash Pahwa

Instructor

University of California Extension, Irvine, CA

Ash Pahwa, Ph.D., is an educator, author, entrepreneur, and technology visionary. He is the CEO of A+ Web Services which provides data mining services.

Dr. Pahwa has worked for General Electric, AT&T Bell Laboratories, Xerox Corporation, and Oracle. He founded CD-Gen, Inc. and DV Studio Technologies, LLC., which introduced successful products for CD-Recording (CDR), MPEG encoding, and DVD archiving. His book,CD-Recordable Bible was published in English, Japanese, and German. He is listed in Who's Who in the Frontiers of Science and Technology. He is also a Google Certified Analytics Consultant.

Dr. Pahwa teaches machine learning courses in the University of California system and Chapman University. Since 2008, he taught many courses at UC Irvine, UCLA, and UC San Diego.

Session: NFL Predictive Analytics

 Brian Platt

Brian Platt

Director, Office of Innovation

City of Jersey City

Brian Platt is the Director of the Jersey City Office of Innovation and he has worked under Mayor Steven Fulop since 2013. Prior to joining Mayor Fulop, Brian worked for McKinsey & Company, taught kindergarten in Newark, NJ with Teach For America, and ascended to the rank of Captain of his local volunteer Fire Department. Brian is currently pursuing a Masters in Public Administration at Columbia University, is a volunteer emergency medical responder, serves as President and cofounder of the Hudson County Young Democrats, is a board member of the Jersey City Youth Foundation, and teaches Olympic weightlifting at Crossfit Jersey City.

Session: Predictive Analytics and Data in City Government

 Kristina Pototska

Kristina Pototska

Growth Product Manager

RetargetApp

Kristina is a Growth Product Manager at RetargetApp, Facebook Ad intelligence. She is great when it comes to retargeting and remarketing tips.

During pasted 3 years she successfully launched more than 100 campaigns for e-commerce websites.

She's also the voice of RetargetApp.

Kristina performed as a speaker at 100+ events in Europe & Asia. Among them are Meet Magento in Netherlands, Sweden, Czech republic and Romania, Predictive Analytics World in London and San Francisco, Global Predictive Analytics Conference in Santa Clara CA, eComExpo (Spain), Webit Summit (Bulgaria, Turkey), Wolves Summit (Poland).

She believes that digital marketing rules and data is the king.

Session:7 Examples of Customer Retention with Predictive Email Marketing

 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 Predictive Analytics Can Drive Success in Fintech and Banking

Session: Q&A: Ask Karl and Steven Anything (about Best Practices)

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.

Session: Q&A: Ask Karl and Steven Anything (about Best Practices)

 John Schlerf

John Schlerf

Data Scientist

Capital One

John has a PhD in Neuroscience from the University of California at Berkeley in 2010, working for the Cognition and Action Lab under the direction of Richard Ivry. In 2012, I completed a Postdoctoral Fellowship conducting research at the Johns Hopkins School of Medicine in the Human Brain Physiology and Stimulation Laboratory under the direction of Pablo Celnik. I then worked as a Data Scientist at eBay Advertising. I currently work as a Data Scientist at Capital One in San Francisco.

Session: The Quest for Labeled Data: Integrating Human Steps

 Som Shahapurkar

Som Shahapurkar

Principal Scientist - Analytics GTM

FICO

Dr. Som Shahapurkar is passionate about analytics engineering - a term he coined for the art and science of deriving business value from analytics. He is a principal scientist at FICO and works closely with his CAO Scott Zoldi on innovation and go-to-market strategy for machine-learning and AI. Before FICO, Som deployed Big-Data/AI/machine-learning in the Industrial Internet of Things (IOT) during his 14-year tenure at Intel. He seeded the technology/business assessment on self-driven cars that subsequently led to the $15 Billion acquisition of Mobile-Eye. Som founded a startup in machine learning for energy management which won several business-plan competitions including the southwest Clean-Tech Open. Som holds a BS and MS in Electrical Engineering and a PhD in Computer Science. His patent on deploying machine-learning production systems is cited by 11 subsequent Google patents. Som is a certified Lean Six Sigma black-belt and a proponent of lean-startup principles. He prides in his ability to solve real-world problems with data-analytics and compassion. He loves to teach technical and non-technical classes:  he regularly teaches data-analytics, machine-learning, statistics, design-of-experiments as well as the '7-habits of highly effective people' leadership program. Som likes traveling with his wife and daughter, and bicycling for charitable causes.

Keynote:  Fraud Screening for 2/3rds of All Card Transactions: A Consortium and Its Data

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.

 Prerna Singh

Prerna Singh

Applied Scientist II

Microsoft

Prerna Singh is currently working as an Applied Scientist II in the Industry AI group @Microsoft where she develops machine learning-based solutions for different industrial verticals including finance and sustainability. Before joining Microsoft, she obtained her master's degree in Electrical and Computer Engineering with a concentration on Machine Learning from Carnegie Mellon University (CMU). Prerna is passionate about machine learning, NLP and deep Reinforcement Learning. Besides work, Prerna enjoys traveling, Zumba and hiking in her free time.

Keynote:  The Centrality of a Detailed Understanding of your Audience

 Craig Soules

Craig Soules

CEO & Founder

Natero

Craig Soules is Founder & CEO of Silicon Valley-based Natero, a leading Customer Success Platform for B2B SaaS companies.


Natero, founded in 2012, helps companies place actionable data directly in the hands of customer success teams through simple and intuitive interfaces. This next generation solution is the only customer success platform to merge machine learning for predicting behavior and big data analytics for deep customer insights, helping SaaS companies maximize customer lifetime value, while improving their products and processes.


Prior to forming Natero, Craig was Principal Researcher at HP Labs, where he led the team that productized Lazybase, a scalable database for processing a mix of high-speed, high-volume event data and more traditional tabular data. Today, Natero integrates with over 35 CRMs, including Salesforce, for its clients.


Craig holds a Ph.D. in Computer Science from Carnegie Mellon University.

Session: Using Predictive Analytics to Improve Customer Retention

 Paul Speaker

Paul Speaker

Senior Data Scientist

The Dow Chemical Company

Paul Speaker is a Senior Data Scientist with The Dow Chemical Company. He has been with Dow for 9 years. His work covers a wide array of analytics modeling work, but primarily covers predictive analytics for the needs of short-term and long-term corporate strategy. He holds B.S. degrees in Physics and Mathematics from the University of Dallas, a Masters in Astrophysics from the California Institute of Technology, and a Ph.D in Applied Mathematics from Michigan State University.

Session: Creating an Industrial Revolution for Analytics

 David Talby, Ph.D

David Talby, Ph.D

Chief Technology Officer

John Snow Labs

David Talby is the Chief Technology Officer at John Snow Labs, helping companies apply artificial intelligence to solve real-world problems in healthcare and life science. David is the creator of Spark NLP the world's most widely used natural language processing library in the enterprise. He has extensive experience building and running web-scale software platforms and teams – in startups, for Microsoft's Bing in the US and Europe, and to scale Amazon's financial systems in Seattle and the UK. David holds a Ph.D. in Computer Science and Masters degrees in both Computer Science and Business Administration. He was named USA CTO of the Year by the Global 100 Awards and GameChangers Awards in 2022.

Session: Semantic Natural Language Understanding with Spark, Machine-Learned Annotators & Deep-Learned Ontologies

 James Taylor

James Taylor

CEO

Decision Management Solutions

James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

Session: The Role of Decision Modeling in Creating Data Science Excellence

 Kerem Tomak

Kerem Tomak

Chief Digital Marketing and Analytics Officer

Sears Holdings Company


Kerem brings more than 15 years of experience as a marketing scientist and executive. He has expertise in the areas of omnichannel and cross-device attribution, price and revenue optimization, assessing promotion effectiveness, yield optimization in digital marketing and real time analytics. He has managed mid and large-size analytics teams in Fortune 500 companies and delivered large scale analytics solutions for marketing and merchandising units. His out-of-the box thinking and problem solving skills led to 4 patent awards and numerous academic publications. He is also a sought after speaker in Big Data and BI Platforms for Analytics.

Session: Omnichannel Measurement and Attribution as a Building Block for In-House Programmatic Solution

 Daqing Zhao

Daqing Zhao

Director, Advanced Analytics

Macy's

Daqing Zhao has over 20 years of experience in analyzing and taking actions on very large data. Trained in data analysis and simulations on molecular systems, he gained extensive expertise in customer centric marketing, optimizing for all stages of customer acquisition, conversion and retention. He has worked on segmentation and predictive modeling for banner ads, web logs, search keywords, emails, transactions, call center, and customer life time values.

Daqing is Director of Advanced Analytics at Macys.com, leading the predictive analytics, test and experimentation and data science teams. He previously held senior management and technical leadership positions at Ask.com, the University of Phoenix, Tribal Fusion, Yahoo, Digital Impact, and Bank of America. He also worked on client analytics projects for Intel, HP, Wells Fargo Bank, SBC, Dell, T-Mobile, MSN Search and Travel, Intrawest, PayPal, wine.com, MasterCard and others.

Daqing received his Ph.D. from Stanford University.

Session: Macy's Advanced Analytics in Customer Centric Strategies

 Feng Zhu

Feng Zhu

Data Scientist

Microsoft

Feng Zhu, is a Data Scientist at C+E Analytics and Insights. Prior to joining Microsoft, he was a research scientist in Transaction Risk Management and Service Team at Amazon. He received his Ph.D. degree in Electrical Engineering from University of Notre Dame in 2014. He holds the M.S. degrees in Electrical Engineering and Applied Mathematics from the University of Notre Dame, USA. He received the B.S. degree from Harbin Institute of Technology, China, in 2008. His research interests are machine learning, optimization and control theory.

Session: How Microsoft Predicted Churn of Cloud Customers Using Deep Learning and Explained Predictions in An Interpretable Way

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