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).

Vivek Agarwal is the CEO of D&B Technologies and Executive Director of PrADS Inc, where he leads a team of economists, statisticians, industry experts and technologists working on analytical models and risk management solutions that enable organizations increase sales, reduce costs and manage risk better. He also works with several credit bureaus and rating agencies in emerging markets with a vision of creating more transparent credit & business environment and robust economies.

Prior to this, Vivek was part of the founding team of Saksoft, a mid-size public listed technology company specializing in analytics and business intelligence solutions. Before starting Saksoft, he worked with P&G, Diageo and Oriflame, where he built advanced analytical and optimization models for marketing, finance and supply chain functions. Vivek holds BS in Mechanical Engineering and MS in Industrial Engineering & Operations Research from prestigious National Institute of Industrial Engineering (NITIE), Mumbai.

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.

Curt studied computer science at the University of Illinois at Urbana-Champaign and mathematics at the University of Minnesota. After building too many websites and client/server systems, he turned to data mining and statistics and never looked back. A good day is spending the morning building models in R and Stan and the evening playing bridge or jazz.

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.

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.

Kristen Burton is the Director of the Enterprise Data Science Office and Digital Process Transformation organization at Cisco Systems. She has responsibility for delivering fully featured analytical solutions for Cisco’s top digital priorities, delivering an enterprise Insights as a Service strategy in partnership with IT, developing enterprise standards for analytical lifecycle management and delivering a portfolio of educational offerings to Cisco’s employees to build digital readiness skills in data science and process engineering.

Kristen has been in Operations at Cisco for 18 years, having held leadership roles in Supply Chain Operations, Customer Operations, Sales Operations, IT and currently in Operations Architecture.

She is an Industrial Engineer by degree and believes that a customer centric and process oriented approach to digital process engineering along with advanced analytics capabilities are critical foundational enablers of digital transformation.  She is driven by the opportunity to deliver insights in simple, digital processes to improve business performance. She promotes an inclusive, energetic and innovative culture that values diversity of thought and taking creative approaches to problem solving and is tenacious about delivering digital solutions that provide value to Cisco's customers, partners and employees.

James Carson is a Data Science Team Leader at Quicken Loans, the nation's largest mortgage lender, based in Detroit, Michigan. At Quicken, James and his team focus on building industry-leading financial and risk models, particularly for hedging and bond trading. James has a MSc in Political Economy from the London School of Economics, a Masters of Public Policy from Michigan State University, and a BA in English from The University of Michigan.

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.

Wes Chaar is the Senior Vice President of Analytics, Data and Decision Sciences at Turner. Wes attained his Ph.D. from the University of Texas at Austin. He has more than 20 years of expertise in the Analytics, Data and Decision Sciences fields. He has applied his Big Data, Machine Learning, and AI skills to work on various Revenue Management, Pricing, Channel Distribution, Consumer Choice Modeling, Scheduling, CRM and other problems. He has published in various journals and proceedings (e.g. IEEE Transactions, M&SOM, AAS, etc.) and presented at various conferences. His work experience covers the Airlines, Hospitality, Online Retail, Marketing and Media sectors, where he held various research, consulting, management and leadership positions. He is a member of IEEE, INFORMS and I-COM, where he serves as a board member.

Menghan Chen is a People Data Scientist at Twitter, where her primary role is using statistical analysis to uncover employee insights for making effective data-based people decisions. Her work focuses on conducting predictive analytics in areas such as employee attrition, engagement, performance/productivity. Menghan earned her MS in Statistics from Carnegie Mellon University and BS in Mathematics and Statistics at University of Washington and. Her areas of expertise include exploratory data analysis, statistical models, data mining, data cleaning, survival analysis, model validation and database management.

Daniel is a Data Scientist at Atlassian, part of the Search and Smarts Engineering group that develops search capabilities and smarts algorithms to power the suite of collaboration products like Jira, Confluence, and Stride. His current research focus is around collective user behavior tied to human collaboration and productivity. His aim is to develop datasets, insights, and experimentations to measure the success of smarts algorithms aimed to better serve relevant content, such as recommendations and notifications. Previously, he was part of the growth team and has since pivoted his knowledge of user engagement and churn towards understanding what drives the users to accomplish their tasks effectively.

A Quantitative Consultant turned a Social Data Startup Founder and now a Data Scientist, Daniel has extensive experience working with user activity data and had previously built risk models for segmenting and predicting customers at risk of participating in fraud and money laundering. He looks to continue innovating and disrupting the consumer / social data space and is a productivity enthusiast.

Gabriel Commeau is a software engineer who has been working for Comcast for the last 7 years on BigData projects and real-time processing platforms. He is interested in cutting-edge technologies, especially in the domains of distributed systems, artificial intelligence and information security.

Gabriel currently provides architecture leadership for Comcast’s data platforms in order to manage the wide range of data streams generated by Comcast’s systems, which a special focus on our enterprise Stream Data Platform, Data Lake, Meta-Data Management system and Data Quality Framework.

As SVP of Data Analytics for Altair, Mark is responsible for the global strategy for the Data Analytics business unit. This includes sales, pre-sales, support, consulting/services and product guidance. Altair's Data Analytics suite is focused on helping organization leverage AI and machine learning to make better business decisions.Mark possesses over 15 years of sales experience with a distinct focus on business intelligence, data mining and analytics. His deep understanding of Predictive Analytics and Machine Learning coincide with his need to nurture and maintain strong business relationships. He is passionate about collaborating with different organizations to discover the best solution to their specific challenges across multiple channels.

Eric M. Dunleavy, Ph.D., is the Vice President of Employment and Litigation Support Services at DCI Consulting Group, where he is involved in equal employment opportunity audit and litigation consulting. Eric’s primary areas of expertise are in employee selection, employment testing, validation research, adverse impact analyses and other quantitative methods. His most recent work has focused on conducting independent expert reviews and related research across a wide variety of selection procedures, including those that leverage machine learning techniques to analyze data. . Eric received his M.A. (2002) and Ph.D. (2004) in Industrial/Organizational Psychology with a concentration in data analysis from the University of Houston.

Barbara Eckman is a Principal Data Architect at Comcast. She leads data governance for an innovative, division-wide initiative comprising near-real-time ingesting, streaming, transforming, storing, and analyzing Big Data. Barbara is a technical innovator and strategist with expertise in scientific data architecture and integration. Her experience includes technical leadership positions at a Human Genome Project Center, Merck, GlaxoSmithKline, and IBM. She served on the IBM Academy of Technology, an internal peer-elected organization akin to the National Academy of Sciences.

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.

Dr Tashi Erdmann is Manager of HR Analytics at Shell, a team of data scientists providing strategic and analytical insights to senior management, HR and Shell's businesses by combined analysis of HR data and business data. Previously, he was consultant in Shell's Statistics & Data Science team, and econometric advisor for Shell Scenarios. Prior to joining Shell, he delivered Lean Six Sigma training, coaching and consultancy for various organizations. He holds a PhD in statistics and an MSc in econometrics from the University of Amsterdam.

An engineer by education and a numbers nerd by heart, over the years Carmen has dabbled in all aspects of tech consulting including analytics, project management, client services, talent acquisition and sales. Her zen is when innovation meets data-driven decision making. She currently leads Centric Consulting’s Cloud and Artificial Intelligence practices. Also: Cancer Survivor, Moon Shot Believer, and Donut Mile Champion.

Bill Franks is the Director of the Center for Statistics and Analytical Research at Kennesaw State University. He is also Chief Analytics Officer for The International Institute For Analytics (IIA) and serves on several corporate advisory boards. Franks is also the author of the books Winning The Room, Taming The Big Data Tidal Wave, The Analytics Revolution, and 97 Things About Ethics Everyone In Data Science Should Know. He is a sought after speaker and frequent blogger who has over the years been ranked a top global big data influencer, a top global artificial intelligence and big data influencer, a top AI influencer, and was an inaugural inductee into the Analytics Hall of Fame. His work, including several years as Chief Analytics Officer for Teradata (NYSE: TDC), has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations.  You can learn more at http://www.bill-franks.com.

Brandy Freitas is a Senior Data Scientist at Pitney Bowes, where she works to develop data-driven solutions for a broad range of industries. She is a physicist-turned-data scientist, who specializes in machine learning for predictive analytics.

Brandy completed her undergraduate degrees in Physics and Biochemistry at the Rochester Institute of Technology, where she was awarded the Goldwater Fellowship for excellence in undergraduate research. As a National Science Foundation Graduate Research Fellow in Biophysics at Harvard University, Brandy specialized in single particle cryo-electron microscopy, with a focus on machine learning in automated protein structure determination.

A strong advocate for women in STEM, Brandy dedicated her time post graduate school to developing and delivering curriculum for the Boston-based non-profit, Science Club for Girls, helping to foster excitement, confidence and literacy in STEM for girls from underrepresented communities.

Coming soon!

Matt Hayes is the Director for Baptist Health Medical Group’s Practice Optimization team, and lives in Louisville, Kentucky.  He holds a BS in Accounting and Business Administration from the University of Kansas, and an MBA in Marketing and Corporate Strategy from Indiana University’s Kelley School of Business. 

A self-proclaimed data geek, Matt is Lean and Six Sigma Black Belt certified, and has spent 17+ years working in analytic functions at three Fortune 200 companies.

When Matt is not knee-deep in data, you might find him in the driveway helping his son Braden with his jump shot, teaching his daughter Avery the finer aspects of Impressionist painting, or practicing Wing Tsun (pronounced Wing Chun) at the local dojo.

Although seemingly disparate, Matt’s passions are connected by one central idea.  “Everyone has greatness inside of them.  No exceptions.  It is my job to help others discover, understand, and capitalize on that greatness.”

Doug Herman is the Director of Data Science with the Global Business Intelligence and Analytics Department at Ingram Micro. He is responsible for leading a diverse group of intellectually curious Ph.D. and Master's level scientists - economists, geographers, statisticians, mathematicians, engineers, and data infrastructure experts - working on some of the most challenging and complex problems in the tech and ecommerce space.  The team works with cutting edge statistical, machine learning, econometric, and mathematical models to drive deep insights for Ingram Micro and our Global partners with immediate and long-term relevance. We are passionate about data, understanding what drives market dynamics and behavior, and developing nudge incentives. 

Doug has a Ph.D. in Economics from the University of California, Santa Barbara. Prior to working for Ingram Micro, he held positions at The Walt Disney Company, The Federal Trade Commission, The World Bank, and was an adjunct Professor at Georgetown University.

Andy started at Caterpillar in June of 2015 as part of the Analytics Professional Development Program; a program designed to teach new analysts about the company and let them work in different parts of the business before returning to the core analytics group that services the entire organization. During this time he worked in business units including the Caterpillar eCommerce group as well has the small construction products group.  

He currently works as a Data Scientist with a focus in marketing. He has participated in projects related to cross - channel reporting, marketing attribution, eCommerce and predicting purchasing behavior in the small construction product space.   

Andy has a master's degree in quantitative finance from Bradley University in Peoria, Illinois.  

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

Cetin is the Global Head of Quant Technology and Analytics Core Strategies at BP.  

Peter Karpiuk, Ph.D., began his career in academia as a psychophysicist modelling human judgements, specifically decision making and the underlying of sensations and feelings that give rise to and influence our decisions.

During this time Dr. Karpiuk has been featured in the New York Times and has authored publications in Nature, Perceptual and Motor Skills; and Choice, Decision and Measurement ranging on topics from epigenetics to autism.

His industry efforts continue to focus on decision making, more specifically those that result in purchasing and preference behavior.

Central to all of his work, is his passion for uncovering the nature of observable and measurable 'behavior' through rigorous research methodology, statistical and predictive modeling.

Peter travels extensively as an independent business management advisor focusing on data enabled decisions with quantifiable and measurable outcomes often beginning with straightforward a Return on Investment objective.

Ajay Khanna is Founder and CEO of Tellius, an innovative Search-driven and AI-powered Analytics platform.  Tellius empowers business users to ask questions using an easy-to-use search-driven interface and to effortlessly uncover hidden answers from data at scale. Ajay has over 20 years of extensive experience in building big data analytics platforms, as well as managing world-class, agile, distributed teams.  Prior to starting Tellius, Ajay was CTO at Celcite, a global leader in telecommunications analytics and network management solutions, which was acquired by Amdocs.

Jim specializes in executing analytic projects for clients seeking to become more customer-centric. His career spans more than 25 years developing marketing strategies, analytic teams and data-driven solutions to improve marketing programs.  His strengths lie in improving business effectiveness with disciplined analytics, solving complex data issues and developing actionable consumer insights.

Jim earned a BA in Marketing and an MBA from Western Carolina University and has completed additional graduate coursework in statistics at The Ohio State University.

Kirit Kottam is a Data Science Director and heads the Marketing and Customer Journey Analytics function at John Hancock Insurance. As a Business Implementer, he oversees both the build and embedding of sophisticated Advanced Analytics models in Marketing and Distribution functions. Prior to Hancock, Kirit advised on and solved business problems in marketing, finance, operations and engineering functions at several F500 clients. He holds an MBA from Cornell, an MS degree from Rutgers and a BS from IIT Bombay in India.

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.

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.

Robert Lanning has spent the past 31 years delivering proactive research, insights, and analytic solutions across the entire enterprise across multiple industries including People Resources.  Robert's leadership results in fully engaged, developed, and focused teams that produce and are recognized as the best in class.   When he's not analyzing, you'll find Robert at home with his family or at his church, where he serves as Assistant Pastor / CFO.  

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).

Peter Lenz is a geographer and data scientist with Dstillery, a data insights company that builds behavioral profiles from billions of observations of human behavior every day using AI. Specializing in geographic big data and data storytelling, Peter can dive anywhere into the data pipeline from writing code, training models, to discovering insights in the data. He built up skill set working in the urban planning world, first at a consulting firm and later with an agency of the Department of the Interior. A native of New York City, today he and his family live in the Hudson Valley.

Sharon Lin is the staff data scientist at Okta, a cloud security and identity management company based in San Francisco. At Okta, Sharon works on building data analytics for products and leads the efforts in developing predictive analytics solutions. Previously, she has worked in several analytics roles at different start-ups, ranging from mobile gaming to marketing analytics, in the Bay Area. She holds a BA in statistics and economics, and a Master of Information and Data Science from the UC Berkeley.

Sam Lipson is a Sr Dir. Measurement, Data Scientist & Data Engineer at Viacom.  In this role Sam focuses on using a wealth of data to optimize business outcomes for Viacom, from tune-in and marketing optimization, to content acquisition optimization.  Prior to Viacom Sam gained extensive experience developing new attribution techniques for ad/media agencies, as well as refining traditional advertising analytics for a modern tech-stack.  Sam studied at Carnegie Mellon, where she earned degrees in Theatre Production Management, and Social Decision Science.  

Haoan Liu is a Data Scientist at Ingram Micro Global Business Intelligence and Analytics Department. He utilizes statistical modeling and analysis to drive actionable insights from various data sources. His work focuses on customer segmentation, market analysis and customer behavior modeling. 

Haoan holds an MS in Financial Engineering from USC, an MS in Statistics and a BS in Actuarial Science from Purdue. His areas of expertise include data mining, natural language processing, financial modeling, and machine learning.

Ricky Loynd is a member of the reinforcement learning research group in the Microsoft Research AI labs in Redmond, Wash. He has 25 years of experience with neural networks, and 11 years of experience in reinforcement learning. Ricky is currently focused on creating deep RL agents with more general, human-like intelligence. As a lead mentor for the Microsoft AI School Advanced Projects course, Ricky has helped teams throughout the company incorporate deep learning systems into their work.

James McCaffrey, who annually leads the full-day deep learning workshop at Machine Learning Week, works for Microsoft Research in Redmond, Wash. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Olaf serves as a Senior Data Scientist in the Decision Analytics team at Pacific Life in Newport Beach, California. He focuses on the design of data driven approaches to improve business decision making and customer experience. Most frequently, he uses tools from time series analysis, machine learning automation and data visualization. To maximize the performance of his models and the measurable impact of his analyses, he enjoys working with internal and external collaborators to formalize facts, to calculate new metrics and to explore new data sources.

Olaf started his career in academia, implementing scientific web tools and conducting research based on ecological, meteorological and geographical data. He has also worked as a Predictive Analyst in the Global Analytics department at Ingram Micro in Irvine, California. He received a M.Sc. in Bioinformatics from Friedrich Schiller University in Germany and a Ph.D. in Geographic Information Science from University of California, Santa Barbara.

Vishal Morde is a VP of Data Science at Barclaycard US where he serves as a catalyst for developing new analytic capabilities in Big Data, Machine Learning and Data Science. He leads advanced analytics initiatives for building state-of-the-art predictive models and developing actionable consumer insights using modern analytic tools/methodologies. In addition, Vishal is responsible for driving Barclays’ innovation agenda, managing new technology/data initiatives and delivering strategic recommendations to the senior management and other key stakeholders. Prior to joining Barclays, he worked at Discover Financial Services and HSBC, where he held leadership positions in Credit Risk, Marketing Analytics, and Pricing Strategy.

Vishal has a bachelor's degree in Production Engineering from University of Mumbai (India), a Master of Science in Industrial and Systems Engineering from Virginia Tech and an MBA from Kellogg School of Management.

Haig R. Nalbantian is a Senior Partner at Mercer and a founder/leader of Mercer's Workforce Sciences Institute. A labor /organizational economist, he has been instrumental in developing Mercer's unique capability to measure the economic impact of human capital practices. Those capabilities have been applied in numerous projects he has directed for leading companies in the U.S. and abroad across a broad range of industries, including energy, high technology, manufacturing, consumer products, financial services, media and information services, telecommunications, and professional services. He has also consulted to organizations in the public and not-for-profit sectors. In recent years, Haig has worked extensively with high-profile organizations in the Middle East, with particular focus on strategic workforce planning, workforce strategies and metrics.

Haig came to Mercer from National Economic Research Associates which he joined in 1989. Earlier, he was on the faculty of economics at New York University and was a research scientist at its C.V. Starr Center for Applied Economics. He is an internationally recognized expert in incentives, human capital measurement and management and their links to organizational performance. He has published widely on these topics in books and articles in leading academic and professional journals, such as the American Economic Review, The Journal of Labor Economics, The Harvard Business Review, Compensation and Benefits Review, WorldatWork, among many others. His HBR article, "Making Mobility Matter," received the Academy of Management's 2010 award for "Outstanding Practitioner-oriented Publication" in 2009.

Nalbantian co-authored the prize-winning book on human capital measurement and management, Play to Your Strengths (McGraw Hill, 2004). He is also editor of and chief contributor to the book, Incentives, Cooperation and Risk Sharing and is a frequent speaker before industry groups, professional associations and academic audiences across the globe. He led the research team and co-authored the 2012 World Economic Forum/Mercer study of global talent mobility, "Talent Mobility Good Practices: Collaboration at the Core of Driving Economic Growth."

Haig earned his BA in English and Economics at New York University and his graduate degrees in economics from Columbia University. He is a member of the American Economic Association.

As a Sales Director at DataRobot, Paul O'Rourke helps organizations realize the benefits of automated machine learning through the use of the DataRobot platform. Paul previously held similar roles in the Business Intelligence (BI) space through his work with Qlik Inc., and spent 10 years with Gartner prior to that.

Konrad is currently the Key Account Manager at Appsilon Data Science. He has experience as a consultant, helping companies add machine learning to their company as well as increasing their pitching skills. He was also Head of Artificial Intelligence at Technologies Capital, a spin-off of ITACO Trading. Konrad was a mentor at the Startup Hub Poland Accelerator. He co-founded and was COO at Craftinity, an AI startup. He also has experience in astrophysics research at the Center for Solar-Terrestrial Research.

I lead  a large team of analytics professionals at Northwestern Mutual across a number of teams: Data Sciences, Insight Services, Data Engineering, and Business Engagement and Advisory.  We deliver a full spectrum of analytics to our business partners ranging from ad-hoc data requests to sophisticated model development.  I have had a long career in IT at NM and more recently, for the last four years in Data Science and Analytics building NM's data science team from scratch.  I hold an Master of Science degree from Marquette University in Mathematics, Statistics, and Computer Science where I specialized in machine learning and optimization. 

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.

Dr. Jennifer Lewis Priestley, Ph.D., is a Professor of Applied Statistics and Data Science at Kennesaw State University, where she is the Director of the Center for Statistics and Analytical Services. She oversees the Ph.D. Program in Advanced Analytics and Data Science, and teaches courses in Applied Statistics at the undergraduate, Masters and Ph.D. levels. In 2012, the SAS Institute recognized Dr. Priestley as the 2012 Distinguished Statistics Professor of the Year. She served as the 2012 and 2015 Co-Chair of the National Analytics Conference. Datanami recognized Dr. Priestley as one of the top 12 "Data Scientists to Watch in 2016."

She has authored dozens of articles on Binary Classification, Risk Modeling, Sampling, Applications of Statistical Methodologies for Problem Solving as well as several textbook manuals for Excel, SAS, JMP and Minitab. Prior to receiving a Ph.D. in Statistics, Dr. Priestley worked in the Financial Services industry for 11 years. Her positions included Vice President of Business Development for VISA EU in London, where she was responsible for developing the consumer credit markets for Irish and Scottish banks. She also worked for MasterCard International as a Vice President for Business Development, where she was responsible for banking relationships in the Southeastern US. She also held positions with AT&T Universal Card and with Andersen Consulting.

Dr. Priestley received an MBA from The Pennsylvania State University, where she was president of the graduate student body, and a BS from Georgia Tech. She also received a certification from the ABA Bankcard School in Norman, OK, and a Certification in Base SAS Programming, and a Business Analyst Certification from the SAS Institute.

Tauseef Rahman is a principal in Mercer's Workforce Strategy & Analytics practice. He is responsible for developing and delivering projects which enable organizations for growth through the use of analytics which combine engagement, career, and rewards information.

Currently based in San Francisco, he has also been based in Mercer's Los Angeles, Dubai, Melbourne and Houston offices.

His recent projects include the integration of an annual pay equity analysis into a company’s yearly business cycle for a global consumer technology company, and an employee survey using conjoint analysis which resulted in changes to parental benefits at a global financial services and investments company.

Tauseef has presented at industry conferences, including WorldatWork Total Rewards and National Association of Stock Plan Professionals on the use of analytics in pay, and regularly speaks at forums on the future of work and the implication of artificial intelligence on the workforce.

Tauseef holds a bachelor's degree in economics from Claremont McKenna College, in Claremont, California.

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.

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.

David Russell is an analytics professional who currently holds responsibility for running DataRobot's Sales & Operations across the Western US, Canada, and LATAM, markets. David has over 18 year experience focused on successful enterprise deployments in big data, predictive analytics, business intelligence, and high performance data-warehousing solutions. David's core focus is on assisting customers in growing top-line revenue and/or decreasing operations overhead by leveraging data as a strategic asset. Currently, David is helping forward thinking organizations leverage DataRobot's modern, disruptive machine learning platform to create competitive advantages across a wide spectrum of data-drive use cases.

Will has been with Caterpillar for the last 17 years.  His current role is focused on driving the use of data and analytics into Caterpillar’s global dealer distribution network with the goals of driving sales, operational efficiencies and increased analytics maturity.  The analytics solutions are tailored based on the dealer’s analytic readiness.

Prior to his current role, Will was the Marketing Analytics Manager responsible for applying analytics to achieve the sales & marketing goals for the extended Caterpillar enterprise.  Typical projects in this space included predictive analytics to identify readiness to purchase, sales forecasting, customer clustering & intelligence, website & social media listening and other projects.

Prior to Will’s roles in the analytic arena, he worked in the eCommerce department deploying online solutions for customers to shop and purchase Caterpillar parts.  Will started his career at Caterpillar in the IT area developing & deploying websites for the Caterpillar dealer network.

Will has a degree in Psychology from Illinois State University and spent several years working in the social services sector assisting families & children.

Nishant is the Director of Predictive Analytics at Charter Communications, the second largest cable provider in the US. Nishant leads the development of various predictive models and strategies to expand fiber network at Charter, market analysis, sales optimization and marketing analytics.

Before coming to the telecommunications industry, Nishant worked in credit/collateral and catastrophe risk management in the mortgage and reinsurance industry. Models and scorecards created under Nishant’s leadership formed key part of underwriting procedures for auto loans and mortgages, and loss estimation forecasts for clients in the events of hurricanes, earthquakes or terrorism.

Nishant has a master's degree in Operations Research from The Ohio State University and a bachelor's in Mechanical Engineering from MITS India.

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 Applications Summit, 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.

Dr. Marc A. Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research. He contributes to the open and free NodeXL project (http://nodexl.codeplex.com) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions. Smith has published research on social media extensively, providing a map to the landscape of connected communities on the Internet.

Tarek is an analytics lead at Google for technical services team. In his role, Tarek focuses on decision analysis to enhance user experience and operational excellence across Google consumer products. Prior to Google, Tarek was an analytics consultant for companies including Comcast, Cox Communications, and Cost Plus World Market. Tarek earned a doctorate degree in information systems with analytics emphasis from Cleveland State University. Tarek's research investigates users interaction with advanced analytics to find ways to enhance insight generation through creative decision making.

Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and head of Skymind Labs the Machine Learning research lab affiliated with DeepLearning4J.  He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters of Science in Data Science degree and oversaw the company's transformation from co-working space to Data Science organization.  Mike began his career in academia serving as a mathematics teaching fellow for Columbia University before teaching at the University of Pittsburgh. His early research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.

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.

Kelly Trindel, Ph.D., served as Chief Analyst at the EEOC. She provided analytic support for systemic investigations and case development since 2010. She specializes in 'big data' issues, including changing human resource models and technology, people analytics, and employment screens of credit history and criminal background. Prior to joining EEOC Kelly was employed as a Professor of Research Psychology, teaching various courses in social science, research methods, and statistics. She has presented at many events, including academic conferences, EEOC outreach events, and internal and cross-agency training sessions, on such topics as social science research, employment screens, people analytics, and employer self-analysis of demographic data. She has over fifteen years of experience in quantitative research including theory building, data collection, and analysis. Kelly earned a Ph.D. in Experimental Psychology from the University of Texas at Arlington.

Ryuichi Umeda is a data scientist at Central Pacific Bank in Honolulu. His role focuses on applying predictive analytics to support revenue growth and customer retention initiatives. Prior to joining CPB, Ryuichi was a quantitative analyst in the Financial Institution Supervision and Credit Division of the Federal Reserve Bank of San Francisco. He has also held an analyst position at Collateral Analytics where he developed property valuation models and analytic tools to support financial institutions. Ryuichi holds a Bachelor’s degree in Economics and a Master’s degree in Financial Engineering from the University of Hawaii at Manoa.

Linda van Leeuwen is an HR Analytics Analyst in the HR Data & Analytics department in Shell International. She holds a bachelor's degree in business administration (Rotterdam School of Management, Erasmus University) and a master's degree in econometrics and management science (Erasmus School of Economics, Erasmus University). After finishing her eight-month internship program, she joined Shell International in April 2016. Her work on the multidimensional measurement of diversity is yet to be published but has already received awards in multiple research competitions, including Wharton's People Analytics conference.

Morgan Vawter is the Global Vice President of Data & Analytics at Unilever. Formerly the Chief Analytics Director at Caterpillar and Data Management Practice Lead at Accenture, she has spent her career driving top and bottom line impact through digital, data and analytics, supporting more than 40 Global Fortune 500 companies. She works from a sense of purpose to activate the positive impact of exponential digital technologies, such as big data and AI, on business and our society.

Marco Vriens has a PhD in marketing analytics and is a globally recognized expert on advanced analytics and marketing research.  He has applied a wide range of analytical methodologies including conjoint, regression, marketing mix models, brand models, switchable consumer, segmentation, audience measurement and optimization, text analytics, machine learning, multi-dimensional scaling, etc.

He is the author/editor of 3 books: The Insights Advantage: knowing how to win (2012), Handbook of Marketing Research (Sage, 2006), and Conjoint Analysis in Marketing (1995).  He published more than 50 papers in both academic journals and industry publications, including the Journal of Marketing Research, Marketing Science, Marketing Insights magazine, etc. His new book: From Data to Decision: Handbook for the Modern Business Analyst will appear in the Fall of 2018.

Phil Winters is known internationally as The Father of Customer Intelligence. An independent business advisor, author,  keynote lecturer and workshop leader with 35+ years' experience working with some 300 companies, he focuses on Customer Intelligence and championing the customer perspective to help organizations raise customer value through outstanding customer experience.

Haifeng Wu is a data scientist at Central Pacific Bank, a retail bank headquartered in Hawaii. At CPB, he is responsible for building statistical and machine learning models to drive the consumer loan portfolio growth and to reduce risk. He is passionate about making decision using data in his personal life. Haifeng earned his PhD in statistics from the University of South Carolina. He lives in Hawaii.

Dan Yang is a Senior Data Scientist of IBM Market Development & Insights. In her current role, she's responsible for transforming the voice of the market into actionable insights and marketing strategies using advanced analytic techniques. Prior to joining IBM, Dan worked as a data and analytics expert for McKinsey & Company and Bank of America. She received IBM Outstanding Contributor Award, Eminence & Excellence Awards, Manager's Choice Awards, and Bank of America Medallion Awards. Dan holds a Bachelor's degree in Telecommunications Engineering from Beijing University of Posts and Telecommunications, and a Master's degree in Mathematical Finance from the University of North Carolina at Charlotte. Dan is also a certified Six Sigma Master Black Belt and has one issued patent.