March 21, 2018 at The Ritz-Carlton, Uptown Charlotte 

Registration begins at 7:15 
Please download our guidebook conference app at and view speaker bios, full descriptions and pin which sessions you would like to attend!

Introduction and Welcome



Keynote: Susan etlinger, Industry analyst, altimeter 

the customer experience of AI: Fostering engagement, innovation and trust

Location: Ballroom

However we define it, whether we know it or not, most of us interact with AI daily. It is present in recommendation engines, search engines, word processing programs, messaging, personal digital assistants, social networks, and even everyday household items. In this talk, industry analyst Susan Etlinger explores how AI fundamentally changes the relationship between businesses and consumers, lays out its risks and opportunities and demonstrates emerging best practices for designing customer-centric and ethical products and services. Attendees will learn:

  • Why and how AI changes the relationship between people and organizations
  • The biggest risks—and opportunities—for business in the age of AI
  • Operating principles, recommendations and best practices for designing innovative, engaging and ethical products, services and brand experiences.



Panel Discussion - Data Analytics & IT: Advancing the charlotte Region, a public policy discussion

Location: Ballroom

Charlotte Chamber of Commerce President and CEO, Bob Morgan, will moderate a panel discussion with Charlotte City Councilman, Tariq Bokhari, and Representative Jason Saine to discuss what Data Analytics and IT means to the Charlotte region and what we can be doing to advance the region as a technology hub.




Breakout SessionS I

Responsible Artificial Intelligence: Role of consumers, businesses and Governments in fostering trust in AI
Location:  Salon I
Speaker: Amaresh Tripathy and Anand S. Rao (PricewaterhouseCoopers)

Artificial Intelligence brings great opportunities as well as risks. This talk looks at six categories of risk from AI - ranging from performance risks to societal risks - and what consumers, businesses and regulators can do to avoid and mitigate these risks. We present a framework for building robust and safe AI that addresses issues of performance, interpretability, explainability and provability. Addressing these issues are critical for consumers and society at large to develop trust in AI systems. We conclude by looking at how businesses, governments and other not-for-profit bodies can play a useful role in creating beneficial AI for the social good of all. 

Analytics: The Executive Briefing
Location: Salon II
Speaker: Geoff Ables (C5 Insight)

Data mining has evolved rapidly over the last 20 years, and is now positioned among the highest priority initiatives according to CEO surveys.  Organizations that fall behind are increasingly at risk of being disrupted by those that stay on top of emerging analytics technologies.  But executives can find it difficult to wade through the jargon to understand the strategic implications.  In this session, author Geoff Ables will share a jargon-free overview of the 5 different categories of analytics, and how global leaders are using each.  Attendees also learn about newly emerging analytics capabilities that are shaping the workplaces of the future.


Machine Learning: How to get the value and avoid the pitfalls
Location: Salon III
Speaker: Bill Kahn (Bank of America)

Machine learning, like all advanced tools, provides high value when used well but creates significant problems when not.  This seminar will explain the distinguishing characteristic of all machine learning algorithms, why they have the ability to work well, and the half dozen ways they can, and unfortunately now and then do, create big problems. While understanding each algorithm’s hyper-parameter space and sensibly searching through it is of course necessary, such actions are not sufficient.  Statistical loss functions, Bayesian priors, random effects, experimental design, and optimal control theory have always been essential, and remain essential, regardless of the underlying regression tool selected.  Despite decades of effort to automate statistical analysis, and despite the many contributions of machine learning, reliably learning from data is still a professional skill requiring theoretical understanding, practical talents, caution, and human ingenuity.

Music Illuminates Data Analytics: A Concert Pianist Demonstrates New Perspectives in Data Analytics Through Music
Location: Great Room I
Speaker:  Dr. Dylan Savage (UNC Charlotte)

Dr. Dylan Savage, concert pianist and UNC Charlotte piano professor, will use live performance at the keyboard to demonstrate critical skills and concepts shared between the fields of data analytics and music. Through a musician’s perspective, Savage will provide new insights into: story-telling, interpretation, pattern-recognition, creativity, and continuous improvement.

Computing research in data analytics in an urban university: panel discussion
Location: Great Room II
Moderator: Fatma Mili, Dean, College of Computing and Informatics, UNC Charlotte
Panelists:  Amy Aussieker (Envision Charlotte), Wenwen Dou (College of Computing and Informatics, UNC Charlotte), Darlene Heater (University City Partners), Cynthia Gibas, (College of Computing and Informatics, UNC Charlotte), Jeff Michael (Urban Research Institute, UNC Charlotte), Robert Phocas (City Manager’s Office, Charlotte), Douglas Shoemaker, (Center for Applied Geographic Information Science, UNC Charlotte)

Urban Research Universities have a unique responsibility and to focus much of their intellectual capital on the economic and social well-being of their City, their region, and their constituencies. UNC Charlotte has a number of unique characteristics and history that make it especially well positioned to create a model of effective symbiosis between a city and its university. This panel brings together representatives from the City, non-profits, and researchers to highlight successes and chart a path forward.

opening up the black box: Explainable AI
Location: The Den
Speaker: Ryan Wesslen (UNC Charlotte)

Recent advances in machine learning and deep learning have provided substantial gains in many predictive tasks like image recognition, text classification, and speech recognition. However, implementing such models in practice, especially for decision-making, can be difficult as these models are inherently opaque, non-intuitive, and difficult to interpret. This talk will explore the role of explainable systems built on top of such models to enable informed decision-making processes. Originally introduced by DARPA, the U.S. Department of Defense’s research arm, Explainable Artificial Intelligence (XAI) is an emerging field that aims to create machine learning techniques that (1) produce more explainable models while maintaining high predictive accuracy and (2) enable human users to understand, trust, and manage the outcomes from such models. This field is highly interdisciplinary and integrates machine learning with a range of fields including probabilistic modeling, causal inference, human-computer interaction, visual analytics, and cognitive psychology. This talk will explore possible industry applications of XAI as well as suggestions for executives and business managers across industries on how to apply XAI to their own business problems.




Lunch/ Keynote: Jeremy Achin, Co-founder and CEO of datarobot

enabling the ai-driven enterprise

Location: Ballroom

Artificial intelligence is rapidly transforming businesses globally. Without relentless pursuit, you will be left behind. Jeremy Achin, CEO of DataRobot, presents the last explanation you will ever need for machine learning, deep learning, artificial intelligence, and data science, and explains why automated machine learning is critical for enterprise success and survival. Understand how to optimize enterprise data scientists and subject matter experts to add direct, measurable business value.

Break through AI misconceptions and leverage immediate opportunities. DataRobot is the world’s only true automated machine learning platform, which is better and faster than 99.9% of the world’s data scientists.




Breakout Sessions II

artificial intelligence & Machine Learning: Lessons Learned and real world challenges
Location: Salon I
Speaker: Avishkar Mirsa (Teradata)

In the last five years, artificial intelligence (AI) and machine learning (ML) have seen commercial revival and expansion thanks largely to the availability of large volumes of data and low cost of computing. Despite the promise and success among innovators like Google, Facebook, and Amazon, most companies struggle with building and deploying production machine learning applications that require additional considerations and challenges beyond just the algorithm and the data. In this talk, Avi will share some of the lessons learned as part of research and deployment of AI & ML solutions to production.


Charlotte's Data analytics roadmap for advancing health and upward mobility
Location: Salon II
SpeakerMichael Dulin, M.D., Ph.D (UNC Charlotte) and Jayesh Mori (Tresata)

Charlotte lags in upward mobility opportunities for our community members living in poverty.  An underlying driving force preventing economic mobility in our community is poor health, as individuals with chronic conditions and poor health status face barriers to entering the workforce.  In addition, diminished access to preventative services including family planning services can impede the ability of individuals to achieve their educational aspirations needed to support upward mobility. To facilitate needed advances in public health and preventative care delivery, UNC Charlotte and Mecklenburg County Public Health have joined together to support a new entity designed to improve the health of our community.  This team (the Academy for Population Health Innovation, APHI) has worked over the past year to build the analytics and data infrastructure required to understand community health needs and to evaluate public health interventions.  To achieve population level impact and scalability, APHI has developed a public-private partnership with Tresata, a Charlotte-Based next-generation software company. This talk will provide: (i) an overview of national best practices around data sharing and data integration in public health; (ii) the design of the data architecture for APHI; (iii) aspects of deploying a public-private partnership needed to achieve success; and (iv) insight into specific use cases currently underway in Mecklenburg county.


Location: Salon III
Speakers: David Crespi and Jared Piedt (Red Ventures)

You’ve fit your machine learning pipeline…now what? As a data scientist, taking a model to production and scaling your process to solve other problems are two of the most difficult challenges you regularly face. As an engineer, how do you integrate machine learning into production applications and provide quick, reliable data to data scientists? This talk will explore how we leverage Apache Spark to generalize the data science workflow through three stages: data collection, machine learning, and machine learning pipeline deployment. First, we will walk through how we leverage Spark Structured Streaming to generate consistent and up-to-date data that is available at training and scoring time. Next, we will discuss how we built repeatable, scalable, data agnostic machine learning pipelines that consider a host of algorithms, objective functions, feature selection and extraction methods to scale the impact of our data scientists. Finally, we will show you how to utilize MLeap to serialize these fitted Spark ML pipelines so they can be evaluated real-time, in tens of milliseconds.


intelligent chat agents using deep learning and belief tracking
Location: Great Room I
Speaker: Samira Shaikh (UNC Charlotte)

According to a recent report by Grand View Research, the global chatbot market is expected to reach $1.23 billion by 2025. A chatbot is an intelligent computer program that can communicate with humans through text or speech input and can achieve certain, predetermined goals. In this talk, Dr. Shaikh will present her research on implementing intelligent agents using Deep Learning and AI. Recent advancements in the area of word embeddings and Generative Adversarial Networks have driven recent innovations in making chatbots more conversational, more effective and more efficient. The talk will include a short demonstration of an intelligent agent with a practical use-case scenario.


Visual Analytics of Bacterial Superbugs
Location: Great Room II
Speaker: Daniel Janies, Ph.D. and John Williams (UNC Charlotte)

Multidrug resistant bacteria, often called "Superbugs" or MDR pathogens, adversely impact health care and food safety.  In response, several US regulatory agencies have formed a network of genomic sequencing labs that collect genetic data on bacterial pathogens called Genome Trakr.  The resulting bacterial sequence datasets are rapidly scanned for the presence or genes that confer antibiotic resistance. However, the data are not fully annotated or analyzed. By combining genetic data with bacterial host, food source, time and location metadata in dashboards and graph network visualizations we enable risk analytics for the spread of MDR pathogens. As a use case, we focus on the spread of resistance to Colistin, an antibiotic considered a treatment of last resort due to toxicity. Only recently have bacteria acquired genes that confer resistance to Colistin. We find in some cases the genes that confer resistance to Colistin are spread by agricultural practices. In other cases, the spread of these genes is nosocomial. We will present detailed analyses of these results. In conclusion, by combining information on bacterial genes and metadata, we can rapidly identify various transmission pathways and thus inform practices needed to minimize the spread and burden of MDR bacteria. 


Panel: Crafting Data Driven Approaches to Combat Human Trafficking 
Location: The Den
Moderator: Tammy Harris (Redeeming Joy)
Panelists: Dr. Matthew Phillips (UNC Charlotte), Dr. Mark Cooke (Reason Analytics, LLC), Dr. Wenwen Dou (UNC Charlotte), Bryan Irwin (NC State Bureau of Investigation, Alcohol Law Enforcement Branch)

The Internet and Social Media have been embraced by the perpetrators of Human Trafficking to facilitate the targeting, recruitment and exploitation of victims.  This dependence exposes new vectors through which researchers might identify and obtain the data necessary to estimate the scope and breadth of the challenge.  When large volumes of data from this cyber-verse are combined with those from other more conventional domains, for example from law enforcement or the social services, addressed in the context of an enhanced awareness of even innocuous elements of society and addressed via the tools and expertise of modern Data Science while guided by input from diverse Subject Matter Experts then quantitative scalable approaches to combat human trafficking should be illuminated. This panel brings a diverse set of Subject Matter Experts together whose perspective encompass distinct yet complementary approaches addressing the topic.




Breakout Sessions III

Sales Volume Forecasting using Recurrent Neural Networks
Location: Salon I
Speaker: Zwick Tang (Red Ventures)
As technology in hardware continues to advance and mature, there has been a wave of renewed interests and progress in deep learning algorithms, which have brought tremendous progress in many applications including computer vision and natural language processing, and outperformed other state-of-the-art machine learning algorithms. In particular, a special type of neural networks, recurrent neural network (RNN) has shown strong performance on time series forecasting – a common problem in marketing and sales. For example, at Red Ventures, the work force management teams rely on accurate sales volume forecasting for efficient staffing and planning. Traditionally, such sales volume forecasting if often done through simple regression models which often lack of the capability of automatically take into account factors such as holidays, special events, etc. We developed a Long-Short-Term-Memory (LSTM) based RNN model that outputs weekly, daily, and intraday half-hourly forecasts every day. The algorithm has been applied to the work force management team and has greatly improved sale operation efficiency.


Distributed ledger technologies to enhance regulatory compliance
Location: Salon II
Speaker: Nitin Agrawal (Deloitte), Peter Bals (Gluetech, Inc.) and Priyanka Saxena (Deloitte)

The cost of regulatory reporting and compliance has become unsustainable.  The main Factors Driving the Increase in Compliance Costs is the pace of regulatory change, Implementation challenges and availability of resources. Blockchain offers potential solutions using Distributed Ledger Technology (DLT) to  enable network participants to validate the transfer of rights between each other and share those records in an immutable manner by utilizing cryptographic technology. This technology can be used to Simplify and Improve the regulatory compliance landscape. Internal organizations participating as autonomous nodes to enable  adoption of enterprise policies in defining accountability.  Digitizing regulatory rules across internal organizations using smart contracts is another mechanism to optimize regulatory supply chain.


draining the data swamp: how to move from a legacy data morass to analytical competitor
Location: Salon III
Speaker: Doug Hague (Analytics Executive Adviser)

When you come right down to it, most of us are not in flashy startups where we get to build a single, real-time, cloud-based data set for our company that has a purpose-built architecture for our analytical models (aka a digital native corporation).  Instead, we have a significant number of legacy systems where either the purpose they were architected for no longer exists or were slammed into a slightly different architecture to find efficiency during integration of an acquisition.  I will provide some lessons learned on the what, when, who, and how to transform your organization from a data swamp to an analytical competitor regardless of industry.  I’ll also discuss key steps and trade-offs, both technologically and politically, that are required to drain the data swamp and compete with analytics.


growing your revenue with data monetization
Location: Great Room I
Speaker:  Shikha Kashyap (Syntelli Solutions, Inc.)

Have Data? Convert it to Revenue. The ‘why’ of it seems obvious, but the question is ‘how’, and the clarity of its implications. The explosion of data has been on the rise, with the opportunity of actionable information available from each database inside every company’s four walls. Data is synonymous to wealth, if you know what to do with it. The conversation around data monetization has been traditionally focused on ‘internal benefit’, and most of the work has been done for this use-case. The other thing that presents significant opportunity is external monetization. The business challenge is to find other companies that are willing to pay for data that does not have any PII information and how to price the data. Once the business case becomes clear, what about ethics and compliance with range of rules and governance standards? What are the technical challenges associated with large volumes of data? Shikha will share her recommendations on approaches and methodologies, along with her insights on how to go about exploring monetization opportunities that exist, and how to get executive sponsorship for monetization efforts.

Location: Great Room II
Speaker: Doug Ellis (DecisionPoint)

Please join us for a discussion on the current state of funding and strategic M&A in the analytics space. DecisionPoint Advisors founder and Managing Partner, Doug Ellis, will walk through what strategic acquirers look for in an acquisition, key value drivers, case studies and trends observed in the market through the lens of an experienced dealmaker. Specifically, this session will focus on some of the hot buttons in analytics like AI and Machine Learning, Big Data and Security and will shed light on how founders and operators can position their business towards a successful outcome.


cybersecurity insider threat analytics
Location: The Den
Right now, new cybersecurity tools are being developed that act like digital antibodies to buy security teams enough time for human analysis and response. These tools blend cutting-edge mathematics, science, and technology disciplines to forge new paradigms in detecting and anticipating threats within a network. To enhance our proactive capabilities within Cybersecurity at TIAA, we leveraged machine learning algorithms to detect and alert on insider threats by identifying anomalous behavior across our big data platform. We’ll speak about how we’ve built a scalable process to incorporate in a number of behavioral attributes into a threat score, and how we’ve partnered with our Cyber Risk department to monetize the potential loss based on insider threats. We’ll also discuss the impacts that this analysis has had on the organization and the opportunities for continued analysis.





Keynote: Paul Zikopoulos, VP of big data and cognitive systems, IBM

Into the mysterious world of a "thinking" Business 

Location: Ballroom

No question about it … we live in a world that collects data: every action, reaction, and process can be instantly digitized … but does that yield knowledge? After all, Big Data without insights is, well, just a bunch of data. And if we are collecting more and more data, and we aren’t getting more and more insightful, then quite simply, we are getting dumber as organizations: we are more and more guilty about not knowing what we could already know!

Adding to the already unmanageable data deluge are new epoch technologies that will further dilute our data understanding ratio. For example, Blockchain (don’t just associate it with Bitcoin) will completely disrupt how our economy handles trust, and as a consequence, those that are paid to do it for us. What’s more, we’ve left a world where everyone talks to everyone and morphed into one where everything can talk to everything … the Internet of Things (IOT). These technologies create a confluence of factors that quite simply are giving clients a pivotal moment: LIFT, SHIFT, RIFT, or CLIFF? We’re in a world where insights are not likened to finding needles in haystacks, rather needles in stacks of needles. We’re going to need some help: enter the world of deep learning, cognitive computing, and AI.

After this talk, you’ll have a good foundation on the trends and opportunities that have created this unprecedented era of ideation, innovation, and renovation. You’ll learn about Deep Learning and AI, bots, streaming data, IOT (and a couple of other buzz words) and how these technologies have been applied across a myriad of forward thinkers. But this session won’t be just a bunch of charts. Put your seat belts on and get twisted, turned, and put in awe on how AI is changing the landscape with a number of real life demos. When you’re done … you’ll be thinking about the art of the possible and understanding that computers aren’t here to replace us (which makes for great movies and column fodder), but to assist us. This is not the era of AI, it’s the era of AI-enhanced productivity.