AI & Machine Learning Summit


Artificial intelligence (AI) and related technologies have come into its own. AI, including machine learning (ML) and cognitive computing, are revolutionizing and transforming business operations. From healthcare and financial services to manufacturing and education, every industry is profiting from implementing AI and ML initiatives. Organizations can better engage with customers and employees, transform business processes, and make better decisions with insights from deep learning and enhanced analytics. AI’s complex analysis functionality leads to the ability to create new products and optimize existing ones. In a data-driven environment, maximizing new AI and ML technologies provides important business predictions. To equip you with the knowledge to succeed, we are bringing together the leading industry experts for a 2-day immersion into the leading AI and ML use cases, strategies, and technologies that every organization should know about.


Monday, May 18

Preconference Workshops


W1. Introduction to Knowledge Graphs

09:00 AM2020-05-182020-05-18

Monday, May 18: 9:00 a.m. - 12:00 p.m.

Knowledge graphs are a valuable tool that organizations can use to manage the vast amounts of data they collect, store, and analyze. An Enterprise knowledge graph’s representation of an organization’s content and data creates a model that integrates structured and unstructured data. Knowledge graphs have semantic and intelligent qualities to make them “smart.” Attend this workshop to learn what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your data.


, COO and Co-founder, Enterprise Knowledge LLC


W2. Data Ops 101

09:00 AM2020-05-182020-05-18

Monday, May 18: 9:00 a.m. - 12:00 p.m.

DataOps has emerged as an agile methodology to improve the speed and accuracy of analytics through new data management practices and processes, from data quality and integration to model deployment and management. By leveraging automation, data democratization, and greater collaboration among data scientists, engineers, and other technologists, DataOps can help organizations improve the time-to-value of their data. Attend this workshop to hear about the key supporting technologies, real-world strategies, and success stories, and learn how to get started on your DataOps journey.


, Head of Product, Tamr


W3. Building Actionable Roadmaps for Data and Analytics

09:00 AM2020-05-182020-05-18

Monday, May 18: 9:00 a.m. - 12:00 p.m.

The starting point in developing and launching an enterprise data and analytics strategy is to understand the interrelationships that are necessary to deliver analytics capabilities. These relationships also account for skills and roles of everyone who works with data, from business executives and business analysts to data scientists. To measure and drive success, an actionable road map, with each phase focused on being lean with a business impact, is required. Attend this workshop to learn how to designate business drivers into analytic capabilities and data priorities, create and implement a road map, and deliver a compelling executive briefing.


, Principal Advisor and CEO, Radiant Advisors


W4. Data Science Best Practices

01:30 PM2020-05-182020-05-18

Monday, May 18: 1:30 p.m. - 4:30 p.m.

Data science, the ability to sift through massive amounts of data to discover hidden patterns and predict future trends, may be the “sexiest” job of the 21st century, but it requires an understanding of many different elements of data analysis. Extracting actionable knowledge from all your data to make decisions and predictions requires a number of skills, from statistics and programming to data visualization and business domain expertise. Attend this workshop for a deep dive into the fundamentals of data exploration, mining and preparation, and applying the principles of statistical modeling and data visualization in real-world applications.


, Founding President, Caserta


W5. Machine Learning Best Practices

01:30 PM2020-05-182020-05-18

Monday, May 18: 1:30 p.m. - 4:30 p.m.

Machine learning is on the rise at businesses hungry for greater automation and intelligence, with use cases spreading across industries. At the same time, most projects are still in their early phases. From selecting datasets and data platforms to architecting and optimizing data pipelines, there are many success factors to keep in mind. The advantages that machine learning offers organizations—the ability to automatically build models that can analyze huge volumes of data and deliver lightning-fast results—have also led to a growth in the availability of both commercial and open source frameworks, libraries, and toolkits for engineers. Attend this workshop for a hands-on course in the enabling technologies, techniques, and applications you need to know to succeed in today’s environments.


, Assistant Professor of Analytics, Information Management/Business Analytics, Montclair State University and Drexel University


W6. Scaling Self-Service Analytics Across the Enterprise

01:30 PM2020-05-182020-05-18

Monday, May 18: 1:30 p.m. - 4:30 p.m.

Realizing more value from data for transformation projects requires a strategy for establishing self-service data analytics. Insights from companies that have made this transformation, combined with industry best practices, provide guiding principles and recommendations to establish vibrant data communities that are intent on extending the value of analytics. Attend this workshop to determine the best self-service adoption strategies for your organization, prioritize key factors and actions, and set the right metrics for measuring and communicating your growth.


, Principal Advisor and CEO, Radiant Advisors

, Director, Editorial & Content Strategy, Radiant Advisors

Tuesday, May 19



WELCOME & KEYNOTE - Disturbances in the Data Ecosystem: How Techlash Will Become a Force in Your Lives

08:45 AM2020-05-192020-05-19

Tuesday, May 19: 8:45 a.m. - 9:30 a.m.

Lee Rainie discusses public attitudes about data, machine learning, privacy, and the role of technology companies in society. He covers how those will be factors shaping the next stages of the analytics revolution as politicians, regulators, and civic actors start to focus their sights on data and its use.


, Director, Internet and Technology Research, Pew Research Center and Author of the book "Networked: The New Social Operating System"


Sponsored Keynote presented by Oracle

09:30 AM2020-05-192020-05-19

Tuesday, May 19: 9:30 a.m. - 9:45 a.m.


Sponsored Keynote

09:45 AM2020-05-192020-05-19

Tuesday, May 19: 9:45 a.m. - 10:00 a.m.


Tuesday, May 19

Track AI: AI & Machine Learning Summit


AI101. The Journey to AI

10:45 AM2020-05-192020-05-19

Tuesday, May 19: 10:45 a.m. - 11:45 a.m.

AI is getting a lot of attention these days. Your journey to choosing and making the most of AI technologies starts with building high-value products.

What It Takes to Build a High-Value AI Product

10:45 a.m. - 11:45 a.m.

AI, ML, and analytics have become a standard stable of tools for organizations that are keen on accelerating their value creation and growth. Many companies have adopted and invested heavily in these capabilities. Some of the early adopters, those with the right culture and data strategy, are reaping wholesome benefits. Conversely, other organizations continue to endure costly resource misalignments. During this session, attendees get an opportunity to discuss what it takes to build a high-value AI product, leverage the company data asset and best practices to unleash their firm’s full productive potential, and accelerate innovation to grow wallet-share and win new markets.


, Director, Advanced Analytics, Genesis Capital - Goldman Sachs


AI102. AI in the Real World

12:00 PM2020-05-192020-05-19

Tuesday, May 19: 12:00 p.m. - 12:45 p.m.

Lots of theories about the value of AI and its relevance to problem- solving exist, but how does it work in the real world?

Enterprise AI and the Paradox of Accuracy

12:00 p.m. - 12:45 p.m.

One way to think about AI is as a very powerful “mimic.” If you show it example data or model an existing process, AI will be able to perform at massive scale, delivering dramatically increased throughput and reduced processing times. However, the most common concern with implementing AI revolves around the notion of “accuracy”: Does it perform the task accurately enough to be useful? When AI uncovers significant inconsistencies, the conclusion is often “AI is not yet smart enough to perform this task,” when in reality AI is simply uncovering existing inconsistencies in the human processes being automated. Wilde discusses the inflated expectations for AI and the need for careful definition of the inputs and outputs required for success. He outlines a set of guidelines to help users overcome these inflated expectations to take advantage of the real value that AI has to offer.


, CEO, Indico


AI103. Building Machine-Learning Apps

02:00 PM2020-05-192020-05-19

Tuesday, May 19: 2:00 p.m. - 2:45 p.m.

The slogan “There’s an app for that” is true for ML as it is for many other activities. Our app-centric world keeps expanding.

Orchestrating a Serverless Machine Learning Web App in AWS

2:00 p.m. - 2:45 p.m.

AutoDesk is leveraging a serverless AWS stack to build fully customizable web apps. Arora provides a detailed overview of what each technology can be used for and then describes a particular use case that AutoDesk solved by combining three different ML techniques to fabricate an NLP pipeline. The use case is focused on how the company used product usage/commands to identify what types of users existed for its major products like AutoCAD, Inventor, and MAYA. Arora also touches upon how his team built an app to give product managers the capability to run the ML models based on changing use cases and requirements.


, Data Scientist, AutoDesk


AI104. Optimizing Machine Learning for the Enterprise

03:15 PM2020-05-192020-05-19

Tuesday, May 19: 3:15 p.m. - 4:00 p.m.

ML has many uses within the enterprise as the technology matures and becomes more valuable to a variety of departments within organizations.

Using Machine Learning to Mine Competitive Intelligence Insights

3:15 p.m. - 4:00 p.m.

Large organizations have access to a trove of unstructured data—research and news reports generated within and outside the enterprise—that can be mined for competitive intelligence (CI) insights necessary for product development, marketing, and sales. It’s a massive undertaking, typically managed by a small team, with each member serving hundreds or thousands of internal clients. Now machine learning (ML) can be applied to read and analyze these documents to expedite the process of mining valuable nuggets of insight from vast and varied content collections. Learn about applying ML to distill and report search results, overcoming “training set” challenges, and optimizing delivery of curated insights.


, CEO, Northern Light


AI105. New Technologies for Finding Information

04:15 PM2020-05-192020-05-19

Tuesday, May 19: 4:15 p.m. - 5:00 p.m.

We hear a lot about how various AI and ML technologies are being deployed today. But what should we expect in the future? What new technologies will come into play? What new applications will we find for existing technologies? Our panel of forward thinkers, who may have their eyes on the stars but maintain their feet on the ground, shares their predictions about new technologies that will impact your organizations and your jobs going forward. Join this exciting panel to stimulate your thoughts about the future.


, President, Synthexis and Cognitive Computing Consortium


, CEO, Indico

, COO, Co-Founder, Basis Technology

Wednesday, May 20



OPENING KEYNOTE - A 2020 Vision for AI - Setting Up AI Projects to Succeed

08:45 AM2020-05-202020-05-20

Wednesday, May 20: 8:45 a.m. - 9:30 a.m.

As technology and techniques get sharper, AI capabilities are becoming more practical. But how can data professionals get business leaders to sign off on AI initiatives when past disappointments have made them skeptical? Jason Hein describes three key strategies to keep your projects on track to win.


, Director, Delivery Services, Earley Information Science


Sponsored Keynote presented by Datastax

09:30 AM2020-05-202020-05-20

Wednesday, May 20: 9:30 a.m. - 9:45 a.m.


Sponsored Keynote presented by Sumo Logic

09:45 AM2020-05-202020-05-20

Wednesday, May 20: 9:45 a.m. - 10:00 a.m.


Wednesday, May 20

Track AI: AI & Machine Learning Summit


AI201. Unlocking the Power of Machine Learning

10:45 AM2020-05-202020-05-20

Wednesday, May 20: 10:45 a.m. - 11:30 a.m.

A critical component of unlocking the power of ML is neural networks.

Using Machine Learning and Artificial Neural Networks to Optimize a Critical Utility Plant

10:45 a.m. - 11:30 a.m.

The National Institutes of Health Central Plant Optimization Software uses NOAA weather forecasting data to predict the future campus chilled water load demand. It optimizes operating decisions within a 36-hour time frame to minimize the total operating cost. The software’s decisions include choosing when and how to operate the Thermal Energy Storage (TES) tank and free cooling. The overall process is broken into two parts: Topological TES Dispatch Optimization (TTDO) and Chiller Fleet Management Optimization (CFMP). The component models are trained by the data-driven ML models. Parallel computing is implemented to provide timely results. Chill out and learn from this ML use case.


, Chief, Utilities Engineering Branch, National Institutes of Health


AI202. Diving Into NLP

11:45 AM2020-05-202020-05-20

Wednesday, May 20: 11:45 a.m. - 12:30 p.m.

Although far from a new technology, companies are finding new and interesting approaches to natural language processing (NLP).

The Power of Word Embeddings in NLP: Transfer Learning With BERT to Build a Text Classification Model

11:45 a.m. - 12:30 p.m.

NLP has seen a tremendous amount of research and innovation in the past couple of years. Text classification is extremely important in all industry sectors. Building up a text classification system from scratch for every use case can be challenging in terms of cost as well as resources, considering there is a good amount of dataset to begin training with. That’s where transfer learning comes in. Using models that has been pre-trained on terabytes of data and fine-tuning the base model based on the problem at hand is the new way to efficiently implement ML solutions without spending months on the data cleaning pipeline. This talk highlights ways of implementing the newly launched BERT and fine tuning the base model to build an efficient text classifying model.


, Data Scientist, Indellient US Inc.


AI203. The Rise of Cloud Services and AI

02:00 PM2020-05-202020-05-20

Wednesday, May 20: 2:00 p.m. - 2:45 p.m.

Most companies are in the early stages of AI initiatives. This shift will be dramatic as more move forward in the AI journey.

Cloud AI: From Data to Insight

2:00 p.m. - 2:45 p.m.

Although companies are at different stages of their AI journey, most agree that finding or developing analytic talent is a key concern and bottleneck for doing more. What if your business could take advantage of the most advanced AI platform without the huge upfront time and investment inherent in building an internal data scientist team? Google’s Ning looks at end-to-end solutions from ingest, process, store, analytics, and prediction with innovative cloud services. Knowing the options and criteria can really accelerate the organization’s AI journey in a quicker time frame and without significant investment.


, Cloud Advisor, Google


AI204. The Future of AI

03:00 PM2020-05-202020-05-20

Wednesday, May 20: 3:00 p.m. - 3:45 p.m.

Sensors, IoT devices, and high-frequency transactional systems collect and store huge volumes of very granular time series data often collected in nanoseconds, milliseconds, and seconds. This data is highly valuable to business as it contains patterns (also called motifs) that, if monitored in real time, can lead directly to significant cost savings, revenue optimization, and other beneficial outcomes. Motif governance will have an impact across all industries—patterns for machine failure in manufacturing, patterns of anti-money laundering, healthcare diagnostics, and many more. Chtilianov provides an introduction to motifs, examples of managing by patterns, the challenges in doing so, and the need for creating governed libraries of patterns.


, Principal Consultant, Capco

, Partner, Capco

Wednesday, May 20



CLOSING KEYNOTE - The Speed of Change Is a Myth

04:00 PM2020-05-202020-05-20

Wednesday, May 20: 4:00 p.m. - 5:00 p.m.

Companies are racing to develop AI and analytic models and empower self-service analytics on modern data platforms to get the most value from their data. There is an overwhelming sense of urgency as more stories come out about digital transformation, disruptive innovations, improved customer engagements, product advances, and operational efficiencies at scale. O’Brien addresses the reality of challenges that companies face, the mindset needed to achieve an analytics-oriented future, and strategies for playing the long game.


, Principal Advisor and CEO, Radiant Advisors

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