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).

Haya Ajjan, associate professor of management information systems, faculty administrative fellow for Innovation and assistant to Elon University president, director of the Center for Organizational Analytics, joined Elon University in 2010.  She teaches data analytics and information systems courses in the Love School of Business’ undergraduate business, MBA and M.S. in Management programs. 

Her research focuses on better understanding the impact of technology use on individuals, groups, and organizations, and has been published in journals such as the Journal of Business Research, European Journal of Operations Research, and Journal of Marketing Theory and Practice. She also serves as project lead for Elon’s participation in Apple’s Everyone Can Code initiative. 

During her tenure at Elon, Ajjan received the Love School of Business Dean’s Awards for Service and Scholarship, founded the Center for Organizational Analytics, and served as the faculty advisor of Elon’s Sigma Iota Epsilon chapter.

Sunil currently works as a Senior TPM at LinkedIn managing multiple teams like Standardization, Pro-ML, Notification, People You may know, Trust and Feed. He previously worked for Oracle, Citibank and State Street bank. He was also a co-founder of a travel startup called Gootli.

Gilad Barash, VP Of Analytics, has been driving innovative work on the Data Science and analytics team at Dstillery for over six years. He previously worked at a Fashion-Tech startup and held various roles at HP, including Research and Engineering at HP Labs Israel.  As a research assistant at Tufts, he worked to improve personalized healthcare. He holds a B.S. and and M.S. in Computer Science from San Diego State University.

Vladimir Barash is Director Graphika Labs. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.

In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.

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

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.

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

Valerie Carey joined Paychex in 2018, and focuses on exploratory analysis and client-facing analytics.  Prior to Paychex, Valerie was employed as a data scientist and a business analyst in healthcare related fields.  In addition, she has worked writing automated tests for a Unix operating system, and has a PhD in biophysics from Cornell University. 

While enjoying the fun of data munging and the joy of discovery, Valerie’s deepest passion is building trust in data products and processes.  She prefers a comprehensive approach to data projects, emphasizing education and communication, automated testing, and iterative feedback.  Valerie believes that explainable AI is just one part of a journey to a comprehensible and useful model. 

Clayton Clouse is a Data Science Manager at FedEx where his team explores and implements artificial intelligence solutions to solve business challenges.  In his six years at FedEx Clayton has developed and implemented many advanced analytical structures, organized cross-operating company research and science collaboration groups, and spearheaded the use and expansion of artificial intelligence.

Mark runs Applied AI Product Management for Xerox at PARC where he works with developers and research scientists to bring Artificial Intelligence from the lab into the marketplace. He previously founded Rank Dynamics which developed AI to enhance the relevance of search results. He has an EE degree from MIT and an MBA from Harvard.

At the forefront of AI and machine learning since the late 1990's, Antonia de Medinaceli has created and deployed predictive models for fraud detection, credit scoring, natural language processing, computer vision, and crime prediction problems, among many other applications. She has worked with both commercial and government clients to ensure that their analytics efforts are impactful to the goals of the organization. Antonia also spent time in advertising technology, heading up an R&D team of data scientists and mathematicians. She is a frequent speaker on analytics at conferences and seminars. Antonia holds degrees in Computer Science and Systems Engineering. Her woman-owned small business, Augmented, specializes in AI applications for both the public and private sectors.

Kunal is a Product leader with more than 15 years of experience building successful, innovative and customer­-focused products.  During his career, he has delivered products that drive user and business growth. As the Director of Product Management at Walmart eCommerce, he continuously looks at analytical data to identify ways to improve user experience and engagement. He has a track record of managing high traffic consumer web sites with millions of users. Previously he has held positions at Snapfish and Oracle and is well versed in both the B2C and B2B space.

As Director of Advanced Analytics and Decision Sciences at Sam's Club, Markus Dmytrzak and his team are responsible for delivering marketing measurement, targeting design, model development, automation, visualization and building simulation tools. Markus started his career at PepsiCo Germany in brand management and worked as an Analytics consultant for retailers in the United States (Costco, Meijer, Giant Eagle) and in Japan (Aeon). He got his MBA from the University Bremen in Germany and completed a Data Mining Certificate program at the University of California San Diego focusing on Predictive Analytics.

Rich Dutton is the Head of Machine Learning for Corporate Engineering at Google, where he leads a team of 15 engineers and data scientists across NYC and Austin. Prior to this role, Rich was a tech lead in Bigtable at Google following a 15 year career working in data and analytics across both tech and finance in the US (New York and Seattle), Europe and Asia.

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.

Hamza has over a decade of experience in leading Data Science/ Machine Learning teams. His tenure spans over three continents and seven countries across APAC, Middle East and Africa and North America and multiple industries, namely, Tech, Telecommunications, Finance and Retail. He is currently working at Google as a Research Scientist and is also serving as an Adjunct Professor at University of Minnesota.

Mohamed Fawzy is senior manager and tech lead at Facebook. In his six years at the company, he's worked on its distributed storage system and was part of the team that developed cold storage, Facebook's exabyte archiver storage system that keeps your memories safe. More recently, he started the Distributed Training Group to build large-scale distributed training infrastructure for deep learning at Facebook.

Kevin Feasel is a Microsoft Data Platform MVP and Engineering Manager of the Predictive Analytics team at ChannelAdvisor, where he specializes in T-SQL and R development, fighting with Kafka, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL (https://curatedsql.com) and author of PolyBase Revealed (forthcoming). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.

Jason is Associate Director of HR Analytics at Bristol Myers-Squibb, where he partners with HR leaders to address strategic business concerns using data and analytics, as well as designs data infrastructure in the cloud to enable firm wide HR reporting and analytics.

Jason has held similar roles in S&P Global, Tata Consultancy Services and JetBlue Airways, where he created and oversaw analytical models and business intelligence applications that helped leaders identify and monitor trends, as well as understand the importance of their people on the quality of their products and satisfaction of their customers.

Jason holds a BBA in I/O Psychology from Baruch College, an MA in Psychology from New York University, and an MS in Analytics from North Carolina State University.

Celeste Fralick, Senior Principal Engineer and Chief Data Scientist for McAfee in the Office of the CTO, is responsible for innovating advanced analytics at McAfee.  She was recently named by Forbes on their inaugural list of "Top 50 Technical Women in America", SC Media's "Women in IT Security", and Industry Leaders  "Influential Leaders in Cybersecurity". She has applied ML, DL, and AI to 10 different markets, spanning a nearly 40-year career.  Celeste holds a Ph.D. in Biomedical Engineering from Arizona State University, concentrating in Deep Learning, Design of Experiments, and neuroscience.

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.

Ryohei is the Founder & CEO of dotData. Prior to founding dotData, he was the youngest research fellow ever in NEC Corporation’s 119-year history, the title was honored for only six individuals among 1000+ researchers. During his tenure at NEC, Ryohei was heavily involved in developing many cutting-edge data science solutions with NEC’s global business clients, and was instrumental in the successful delivery of several high-profile analytical solutions that are now widely used in industry. Ryohei received his Ph.D. degree from the University of Tokyo in the field of machine learning and artificial intelligence.

Michael is the Director of Business Analytics & Insights at AppFolio, Inc., a leading SaaS provider for vertical markets based out of Santa Barbara, CA.  At AppFolio, Michael manages the company's Analytics Data Platform and is responsible for creating Analytics culture, implementing best practices, and leading Analytics initiatives to drive business growth and improve customer experience.

John Gao is a leader of data science team of Work Human Research institute at Work Human. In addition, he has worked at marketing companies, such as ConstantContact, as a director of predictive modeling team, CVS, Staples, etc., and at financial companies, suych as FleetBoston, and First Marble Head as senior statistician. He has published his research in academic conferences and journals, including, "An Asymmetric Theory of Nonlocal Elasticity Part 1 & 2" (1999) IJSS,  "A New Spline Regression Method" (2002) JSM,  "A New Method of Using Polytomous independent variables with many levels for binary outcome of Big Data analysis" (2015), SAS Global Forum, and "Financial impact analysis of New RUG-IV on Post-Acute Medicare Providers Using Monte-Carlo Simulation" (2012) NESUG.

Priyanka Gariba heads Technical Program Management for the Artificial Intelligence organization at LinkedIn. Her team's mission is to lead cross-functional technical programs focused at building products powered by AI. She is an experienced professional who has worked in both enterprise and consumer space. At LinkedIn, she has led several company-wide data science and artificial intelligence initiatives, most recently playing a dual role in leading a team of stellar TPMs and leading one of the top 5 initiatives for LinkedIn Engineering organization (Productive Machine Learning Program). She is actively involved with Women in Tech community to advance women’s career in tech, particularly focused in Technical Program and Product Management discipline. She is passionate about sharing her knowledge on Technical Program Management and mentoring through external tech talks, panel and other mentoring circles.

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Enrique Gil, PhD is a scientist at Philips Research in the Netherlands responsible for data science activities in fields ranging from health and well-being applications to business analytics and marketing. In addition to data science, he is active in business development and value proposition creation for new Philips innovations. With 10 years of data science and analytics experience in academia and industry, his focus lies on the translation and leveraging of data science methods and technologies into real-world business value.

Peter Grabowski is a longtime Googler and former Nest employee. He's currently the manager of the Enterprise Machine Learning team in Austin. Previously, he managed a data engineering team at Nest and helped build the Assistant for Kids team at Google. Outside of Google, he teaches machine learning as part of UC Berkeley's Master's in Data Science, and is a managing partner of PXN Residential, LLC.

Robert Grossman is a partner at Analytic Strategy Partners and a professor at the University of Chicago.  From 2002 to 2016, he was the Founder and Managing Partner of Open Data Group, which provided data science consulting services to a wide variety of companies, including those in financial services, location services, computational advertising and cybersecurity. From 1996 to 2001, he was the Founder and CEO of Magnify, which developed predictive analytic software for the financial services and computational advertising industries.  Magnify was sold to ChoicePoint in 2003 and is now part of the RELX Group.  He is the Frederick H. Rawson Professor of Medicine and Computer Science and the Jim and Karen Frank Director of the Center for Translational Data Science at the University of Chicago, where he leads a data science research group that is developing systems and algorithms for managing, analyzing and sharing large biomedical and environmental datasets.

Jesse has been an executive in the tech sector for more than 20 years - having led various analytics teams including data science, NLP, digital, predictive, data governance, marketing, sales, and customer. Jesse is currently Head of Analytics for Workhuman, a company that helps millions of people and organizations through Its cloud-based social recognition software. Prior to Workhuman, Jesse was Chief Analytics Officer for Endurance International Group and CAO for Constant Contact, both technology SaaS companies with millions of customers. Prior to Constant Contact, Jesse was Chief Knowledge Officer at Monster Worldwide where he helped drive revenue from $300 million to over $1.3 billion. Jesse started an international analytics division and created the Monster Employment Index that was tracked by millions of people in more than 30 countries in the United States, Europe and Asia. Prior to Monster, Jesse created an analytics consulting practice Gomez (now Compuware), where his team led projects for Internet start-ups and well-known brands. 

He has advised many private and public organizations regarding analytics, including the White House, the Department of Labor, the European Commission, the Federal Reserve, the National Governors Association, the Clinton Global Initiative, and various U.S. senators. He has authored several international publications, including the books Win With Advanced Business Analytics (Wiley) and Finding Keepers (McGraw-Hill). Jesse taught at the University of Chicago and holds an MA and a PhD in Experimental Psychology from DePaul University. He has appeared in various media outlets, including CNBC, the Wall Street Journal, the New York Times, CBS, Bloomberg, and Reuters. Dr. Harriott has won several awards, including the Hardin Analytics Award from the American Marketing Association, the Platinum Award from PR News, an Ogilvy Award, and was named by the Boston Business Journal as one of Boston’s top 40 under 40. 

Ari Kaplan is a leading figure in machine learning, sports analytics, and business leadership. In sports he created the Chicago Cubs analytics department and serving as assistant to the GM of the Orioles the past seven seasons - with three playoff appearances. In business he was President of the worldwide Oracle users group during a period of high growth including the acquisition of MySQL, Java, and PeopleSoft. He co-authored five best-selling books on analytics, databases, and baseball. He has been the recipient of Caltech's "Alumnus of the Decade" and Crain's Chicago Business "40 Under 40" awards.

Eugene is an expert in the large-scale data processing and machine learning infrastructure space. With over 13 years of experience under his belt, he had spent the last 8 as a Staff Software Engineer at Google Cloud and Google AI, before fully realizing the urgency and opportunity of climate change mitigation and leaving in Aug 2020 with his friend Cassandra Xia to pivot into climate.

Currently he’s mobilizing professionals to work on climate long-term as part of the Work On Climate community and exploring other ways to accelerate the climate solutions ecosystem.

Eric is an education industry veteran who has stayed on the cutting edge of new business models and growth markets for over twenty years in sales and sales leadership roles.

He is passionate about lifelong learning due to the impact education can have on an individual’s life. He has been fortunate to work for leaders across K-12, higher education, professional learning and corporate training including Pearson, Follett, Cengage Learning, VitalSource & Area9. He is a student of the industry, constantly immersed in understanding the key dynamics of his markets and the needs of his customers. Eric is a believer that in order to be successful in sales, you must have a strong work ethic fueled by curiosity, all while maintaining a growth mindset. He is a member of numerous industry organizations such as the Association for Talent Development, T3 Innovation Network / US Chamber of Commerce Foundation & The Society for Human Resource Management. Florida has been home for the last eighteen years with his wife and two children, but he is originally from Iowa. He attended St. Ambrose University and is an avid Iowa Hawkeye sports fan.

Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader with over 25 years of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with causal inference and is a pioneer of Uplift/True-lift modeling, a key subfield of data science.

Victor has managed teams of quantitative analysts in multiple organizations. He currently leads the AI and Data Science Center of Excellence, Workplace Investing at Fidelity Investments. Previously he managed advanced analytics/data science teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).

For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University. He has also been serving on the steering committee of the Boston Chapter of the Institute for Operations Research and the Management Sciences (INFORMS) and on the editorial board for two academic journals. He is also an elected board member of the National Institute of Statistical Sciences (NISS). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. He has co-authored a graduate level econometrics book and published numerous articles in Data Mining, Marketing, Statistics, Analytics, and Management Science literature, and is completing a graduate level book on causal inference in business.

Shingai Manjengwa is the Chief Executive Officer of Fireside Analytics Inc., an ed-tech start-up that develops customized online and in-person professional development programs that teach digital and AI literacy, data science, data visualization and computer programming. Clients include corporates, governments, higher education institutions and high schools. Data Science courses by Fireside Analytics have over 400,000 registered learners on platforms like IBMs CognitiveClass.ai and Coursera. 

A data scientist by profession, Shingai is the Technical Education Specialist at the Vector Institute for AI in Toronto, Canada and she is also the founder of Fireside Analytics Academy, a registered private high school (BSID: 886528) that teaches high school students data science and offers the data science course curriculum to other high schools. Shingai’s children’s book, ‘The Computer and the Cancelled Music Lessons’ teaches data science to kids ages 5 to 12.

Ben Martin is the Chief Data Analytics Officer at Hanesbrands Inc.  He has responsibility for advanced analytic functions globally and has spent the last decade establishing analytics as a core competency at Hanes.  He also leads the Global Planning function with global responsibility for demand planning, capacity planning, inventory planning, production planning, and material planning.

Ben received his Ph.D. from North Carolina State University and his expertise involves simulation-based optimization, process simulation, organization design & development, and critical process improvement.

Prior to joining Hanes, Ben consulted in a variety of business functions in the textile, apparel, automotive, medical device, cosmetic, semiconductor, and healthcare industries.

Natalia Modjeska is a Research Director at Omdia (part of Informa Tech) where she leads the team of analysts covering Artificial Intelligence and Intelligent Automation from processors and software to enterprise deployments.

Natalia’s journey into AI started in the late 1990’s with a PhD in NLP from the University of Edinburgh in Scotland. Since then she has worked in range of roles developing, deploying and evangelizing analytics and AI. Her diverse career includes R&D, product and program management, sales, consulting, and client advisory. She has worked with organizations of all sizes and levels of maturity across many industries and geographies helping clients to harness the power of data, advanced analytics and AI for transformative change. In the past four years she has advised 200+ organizations around the globe on topics ranging from strategy and use cases, to execution, best practices, governance, ethics, emerging trends, and vendor due diligence.

Natalia is passionate about helping clients to demystify AI/ML, deploy these technologies responsibly and achieve sustainable business benefits. As part of this effort, she also serves as an AI expert on the ISO/IEC JTC 1/SC 42 - AI Standards working group and volunteers with several non-profits to develop responsible AI certification; and to increase AI literacy and improve government through innovative technologies.

Reeto Mookherjee serves as vice president of data science, advanced analytics and business intelligence at Fandango, a Comcast/NBCUniversal portfolio company. He has over 13 years of experience in the design, development, implementation and use of analytic decision support tools, primarily in pricing, revenue management, and predictive sales and marketing disciplines in sectors such as retail, media & entertainment, e-commerce, online travel and hospitality, wholesale trade, industrial and high tech manufacturing. He has over 8 years of experience in recruiting, developing, managing and leading distributed teams of professionals across the globe for two Fortune 100 companies and has built their award-winning data science/machine learning/pricing and analytics practices from the ground up. Reeto holds a Ph.D. in operations research from Penn State and a M.S. in systems engineering from Boston University and an INFORMS Edelman laureate (2015).

Robert A. Muenchen () is the author of R for SAS and SPSS Users, and co-author of R for Stata Users and An Introduction to Biomedical Data Science. He is also the creator ofr4stats.com, a popular web site devoted to analyzing trends in data science software, reviewing such software, and helping people learn the R language.

Bob is an ASA Accredited Professional Statistician™ who focuses on helping organizations migrate from SAS, SPSS, and Stata to the R Language. He has taught workshops on data science topics for more than 500 organizations and has presented workshops in partnership with the American Statistical Association, RStudio, DataCamp.com, and Revolution Analytics. Bob has written or co-authored over 70 articles published in scientific journals and conference proceedings and has provided guidance on more than 1,000 graduate theses and dissertations at the University of Tennessee.

Bob has served on the advisory boards of SAS Institute, SPSS Inc., BlueSky Statistics, and the Statistical Graphics Corporation. His contributions have been incorporated into SAS, SPSS, JMP, jamovi, BlueSky Statistics, STATGRAPHICS, and numerous R packages. His research interests include data science software, graphics and visualization, machine learning, and text analytics.

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.

Pragyansmita Nayak is Chief Data Scientist at Hitachi Vantara Federal (HVF), a wholly owned subsidiary of Hitachi Vantara. She has over 20+ years of experience in software development and data science-related research and development. She holds a Ph.D. in Computational Sciences and Informatics from George Mason University (GMU) and Bachelor's degree in Computer Science from Birla Institute of Technology and Science (BITS), Pilani, India. Her Ph.D. thesis focused on the application of Machine Learning techniques such as Bayesian Networks for redshift estimation.

Prior to HVF, she was Principal Research Engineer with Apogee Research LLC working on DARPA (I20 and STO) projects. She was Technical and Data Architect with the Momentum Product Development team at CGI Federal Inc. for 13 years (2004-2017). She is the founder of NoVA Deep Learning meetup and Washington DC Pentaho User Group (PUG). She serves as a reviewer with ACM Computing Reviews (featured reviewer for Dec 2016), Python conference SciPy and Grace Hopper Celebration (GHC) in Computing. She is a StartingBloc Social Innovation Fellow and LeadIn member. She is a member of ACM, IEEE, Sigma Xi and AFCEA. 

She has presented her work as part of AFCEA WEST 2020 (also published in AFCEA Signal), FDA Innovation Day 2019, Enterprise Analytics Online 2017-19 (Keynote for 2019), BayesiaLab User Conference, Smart Data Online 2016-18, PyData DC 2016 and Splunk GovSummit 2016. She is an avid hackathon participant including winning the AngelHack 2016 HPE Haven OnDemand challenge, presenting at the White House "Hack the Pay Gap" challenge of 2016 and the CERN ThePort Social Innovation global hackathon. She has volunteered as an Election Officer for Loudoun County and as a mentor for Data Community DC and Fairfax Public School system.

For more information on Pragyan's professional experience, please visit her LinkedIn profile at https://www.linkedin.com/in/pragyansmita and Twitter profile at https://twitter.com/SorishaPragyan.

Venkata Pakkala is a Staff Data Scientist at Samsung Electronics America. In his current role, Venkata leads a team of data scientists developing cutting edge data products that primarily focuses on optimizing marketing initiatives and enhancing customer experience. Before joining Samsung, Venkata held top data analytics positions at Fortune 500 companies. Venkata holds a Ph.D. in Theoretical Chemistry from Duquesne University.

Kumaran Ponnambalam is a technology leader with 20+ years of experience in AI, Big Data, Data Processing & Analytics. His focus is on creating robust, scalable AI models and services to drive effective business solutions.  He is currently leading AI initiatives in the Emerging Technologies & Incubation Group in Cisco. In his previous roles, he has built data pipelines, analytics, integrations, and conversational bots around customer engagement. He has also authored several courses on the LinkedIn Learning Platform in AI and Big Data.

Satish Prabhu has been part of the Paychex family since 2018. He graduated from Clemson University with a Masters in Electrical Engineering, specializing in ML algorithms and their underlying math. Prior to Paychex, he worked as a data scientist for a start-up that developed wearable technology. He is at the core of problem-solving; someone who understands business and is very passionate about data. He has the knack to uncover insights from data and translate that into actions and business outcomes. He is a big advocate for explainable AI, so as to build trust in black box models across all the Paychex teams.

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.

Jennifer Redmon joined Cisco in 2009 and serves as its Chief Data Evangelist. Her charter is to enable an increasingly data-driven culture through globally-scaled data platforms, services, and community enablement. Her team has trained over 6,000 employees in the areas of data science, artificial intelligence, data storytelling, data engineering, and lean six sigma. Her Data Evangelism group also hosts Data Symposiums serving Cisco's data science and AI communities of practice around the world, bi-annual Kaggle-style data science competitions, internal data science collaboration platforms, and Cisco's Data Science for Good program.

Jennifer holds an international MBA from Duke University with a concentration in Strategy and Bachelor's in Economics and Art History from UC Davis.

Gil Reich is a Data Developer for the Wix Data Science team. He spends his days working with Data Scientists to get them the data they need. Gil was a founding member of Answers.com, where he led the Engineering and Product Management teams. He has a B.S. in Engineering from the Cooper Union (1990) and an M.S. in Management from Ben Gurion University (1991)

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.

Bio forthcoming

ndraneel Sheorey leads the BI, Analytics & Data organization at Fandango, the ultimate digital network for all things movies.  In his role he is responsible for the product & technical direction of Fandango 360, a machine-learning-based movie marketing & content recommendations platform, as well as providing insights & enterprise reporting across all of Fandango’s digital brands.  Indraneel has 15 years of experience in predictive analytics and data-driven Software-as-a-Service (SaaS) applications in both the B2C and B2B spaces, working on problems including retail pricing/promotion optimization, customer acquisition/cross-sell/churn prediction, and analytics/marketing for free-to-play mobile games.  After obtaining his BA in Computer Engineering from Dartmouth College, Indraneel started as a data analyst using SQL to extract insights and model customer behavior from retail data sets, and has been honing his data-wrangling skills ever since.

Mohammad is currently a Senior Data & Applied Scientist at Microsoft, and Instructor at Stanford University. He is a former Data Scientist at Apple and previously worked for Samsung, Bosch, General Electric and UCLA Research Labs. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is the author of the book, ‘Applications of Mining Massive Time Series Data'. He has also been a keynote speaker at more than 40 Data Summits/Conferences around the globe. 

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. Simon is serving as the chief analytics officer (CAO) in the science and technology directorate.  He is responsible for implementing the Artificial Intelligence (AI) and Machine Learning (ML) strategy, having served as its lead technical author.  He is also the chief data & analytics officer (CDAO) for a large technology organization, building the data strategy and driving integration on cutting edge analytics in network and cyber security, biometrics, and behavioral modeling.  

He previously served as the Agency’s Technical Director for Data Science and Editor of the CIA’s in-house peer-reviewed methodology journal.  Dr. Simon is an award-winning bridge-builder between technical and non-technical teams, between social, natural, and computational science fields, and between research and development (R&D) and application.  He is an advisor to investors and researchers on cyber security, predictive modeling, and AI, with successful prior work experience in banking, education, financial services, and health.

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.

Dan Steinberg, Ph.D. Harvard University (Econometrics) was the founder of Salford Systems, one of the world’s first software companies in the field of machine learning.  Working closely with Leo Breiman and Jerome Friedman since 1990 Salford introduced commercial software based on Friedman’s proprietary code for the CART decision tree, MARS regression splines, and the first gradient boosting machine (TreeNet) and Breiman and Cutler’s Random Forests.  Dan led the teams that won the KDDCup 2000 predictive modeling competition and also the 2002 Teradata/Duke Churn modeling competition and was involved in a number of other subsequent competition winning efforts. Besides software development Dan has been involved in major consulting projects for some of the world’s largest banks and has published in economics, statistics, and computer science journals.

Salford Systems was acquired by Minitab in 2017 and as of March, 2020, Dan is an independent consultant.

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.

Charles is an Enterprise Data and Analytics leader who maximizes the impact Data, Insights, and Artificial Intelligence have on business results, operational efficiency & effectiveness, and fact-based cultural change.  A rare three-time Chief in the data domain, he’s led large scale data and analytics efforts for brands such as HP, USAA (where he was its first Chief Data and Analytics Officer), and Wells Fargo (its first Chief Data Officer and Head, Enterprise Data & Analytics).

He has expertise leveraging data to drive strategy across B2B and B2C segments, digital and traditional routes to market, multiple regions, and industry verticals such as energy, high-tech, pharma, retail, financial services and automotive.

Charles is committed to increasing the role of "Activist Analysts" in organizations, and driving a diversity and inclusion agenda in technology, particularly in the Data Sciences.  He formerly sat on the University of California at Berkeley’s School of Information advisory panel and currently serves as a Director at the United Negro College Fund, Inc. in Washington, DC.

He holds a PhD in Sociology (with a concentration in Organizational Behavior & studies in Quantitative Methods) from Yale University, is headquartered in Detroit, and lives in Austin with his wife and two children. 

Dr. Vazirabadi (Vazeerabaadi), received her PhD in Psychological Measurement and Quantitative Research Methods from University of Denver, in Denver, CO in 2010. She has been contributing to the workforce analytics field since 2005 and was directly responsible for her team's achievement of their first industry award in 2008 from IQPC for Best HR Metrics and Analytics. Since then, she has been key in the analytics strategy, development, and execution of number of mid-size and large organization where through her work she was responsible for significant cost savings, business process improvement and HR effectiveness measures. She has received multiple industry awards for her work, published in peer reviewed journals and taught at colleges and universities in her field of expertise. For the past six years she has been working for Bristol Myers Squibb as a subject matter expert in HR Analytics, where she designs measurement techniques, analyzes data, interprets results, and provides action plans and next steps for her HR executives.

Thomas M. Warden joined EMPLOYERS as Senior Vice President, Chief Data and Analytics Officer on May 22, 2017. He is responsible for data science, business intelligence and data governance across the company. He works closely with business partners and information technology to improve revenues and profitability through the application of predictive modeling, analytics and business intelligence to decision making. Mr. Warden brings to EMPLOYERS 30 years of insurance industry experience from Allstate, AIG and private consulting. Mr. Warden holds a Bachelor of Science degree in Accounting from The Ohio State University and an MBA from Harvard University. He is a Chartered Financial Analyst and is a member of the board of directors of Junior State of America.

Karl is a Developer Advocacy Manager from Google's Developer Relations Artificial Intelligence and Machine Learning team.  Karl has worked extensively in data science and cloud computing, and was a contributor to one of the first AI-based crossword puzzle solvers that is still referenced today. He holds a BS in Computer Science and Economics from Duke University, and an MBA from the University of Texas-Austin.

Co-founder of MIM Solutions. A graduate from the University of Warsaw with a Ph.D. in Informatics and double master's degree in Informatics and Mathematics. Assistant professor at the University of Warsaw. Experienced both in the theoretical and commercial aspects of machine learning. His principal focus is on delivering deep learning solutions in socially important areas, predominantly medicine.

Allen Yu is Director of AI at Lineate Labs where he leads a team of AI engineers, solution architects, and data scientists to identify and tackle the business problems for clients in ad tech and marketing using machine learning techniques. His expertise in AI product solutions spans from product recommendations for retail customers to real-time ML predictions in advertising.