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Day 1

Registration & Breakfast

Chairperson Overview

Laura Hamilton Group Product Manager Groupon

Artificial Intelligence and Predictive Analytics: Optimizing the Impact of Health Care

With the vast amount of information available for each individual, organizations face the challenge of selecting the most effective contact channel to communicate with their providers and customers. There is also a challenge to decide how to segment their providers and customers for various communication campaigns. In this session, we introduce a model to predict the optimal contact channel when communicating with a physician. We also introduce an advanced analytics model that places physicians into more accurate and granular segments for optimal communication campaigns.

Tony Liu Director of Data Science American Medical Association

Building Machine Learning Based Products at Scale

Lessons learned deploying machine learning models to 50 million customers in 15 countries.

Laura Hamilton Group Product Manager Groupon

Embedding Predictive Analytics into business processes to drive operational value

While Predictive Analytics adoption has grown steadily for several years, the overall CAGR has not reached industry estimates. Most organizations acknowledge the need to leverage Predictive Analytics for improved decision-making, and businesses have made significant investments; so why has the industry not exploded? Join us to learn how QueBIT has delivered massive ROI for our clients through a unique approach to implementing AI Machine Learning solutions in areas such as Demand Planning. This approach ensures organizational goals are achieved and adoption is strong.

Dallas Crawford General Manager, Advanced Analytics QueBIT

Networking Coffee Break

Impact of Predictive Analytics beyond Predictive Maintenance on Business

There is a growing trend to incorporate predictive analytics in various fields. While industry is getting ready to collect relevant data to support the implementation of predictive maintenance as part of predictive analytics, it is of importance to know the contribution of predictive analytics beyond predictive maintenance. The talk concentrates on the role of predictive analytics in Industry, and the impact on business over and above predictive maintenance. Also, the mathematical and technical advancements required in the space of Predictive analytics.

Sheela Siddappa Global Head- Data Science Robert Bosch

Buzzword Bingo (and Three Ideas to shape your Analytics Approach)

AI, Data, Predictive Analytics… just some of the Buzzwords being bandied about these days. We are all either trying to sort out how it applies to us, or just jumping into the deep end of the pool. Join me for a quick chat as I talk about three simple concepts to help contextualize and shape how you can approach the big bad world of Predictive Data. And we’ll play some Bingo too.

MQ Qureshi Founder & CEO Xoobies

What I've Learned From Advising 100+ Data Science Projects

Throughout my career, I've had the opportunity to meet and mentor many data scientists. Along the way, I've learned a few things, like the difference between a good and a great data scientist, some data science personas to strive for and those to avoid, and what companies are starting to do to hire the best talent. During this session, I'll be sharing stories of my experiences that have led to some surprising findings.

Alice Zhao Senior Data Scientist Metis


Machine Learning & Data Analytics to Enable Amazing Voice Self-Service

Machine learning is revolutionizing work for most industries today, including breakthrough customer service innovations in areas like call center servicing. In this talk, Yi-Chen will share how Capital One has leveraged machine learning and data analytics to simplify and enhance the customer experience in this capacity. The session will cover learnings and best practices around predictive models including forming a better understanding of the customer and their needs and intents.

Yi-Chen Tu Senior Director, Data Science Capital One

How We Deliver High-Quality Data Analytics

This session will center around how to deal with bad data, how to plan and identify it, and how to maintain end-user trust despite imperfect systems with multiple points of failure.

Alex Welch Director of Business Analytics E*TRADE

Social Network Analysis in Healthcare

Social network analysis is a less frequently used tool in the advanced analytics toolkit. Understanding relationships between physicians and facilities offers insights about patient behavior and medical costs that aren’t as easily gained through other analytical means, especially when combined with predictive modeling and machine learning. We’ll also explore some interesting visualizations that can help tremendously with stakeholder buy-in.

Michael Xiao Divisional Vice President, Enterprise Analytics Blue Cross and Blue Shield Plans in Illinois, Montana, New Mexico, Oklahoma, Texas

Networking Coffee Break

Big Data and Emerging Technologies: What Your Executives Need to Know and How to Communicate it Effectively

We data professionals are center stage of a massive and accelerating transformation in the way we work. Emerging technologies and automation enabled by Big Data are simultaneously empowering human capabilities and replacing human tasks and jobs. New business models are up-ending old ones, and the competition for talent is fierce and growing. This creates huge implications for our society, economy, government, corporations and the individual, at a time when leaders are already grappling with unprecedented disruption. Is your Board of Directors and senior leadership ready for a future we can’t yet define? Do they understand the potential impact of emerging technologies and Big Data on work, the workforce and the workplace? In this talk we’ll discuss how you can help discuss this and prepare your senior leadership for a world in flux.

Marian Cook Subject Matter Expert & Head Learning Facilitator, Blockchain Technologies MIT Sloan School of Management

Adaptive Prescriptive Modeling for Personalized Medicine

Personalized medicine is the promise that by individualizing treatment to the patient we can improve outcomes. Machine learning enables us to make data informed decisions about which treatments will work best for which patients. In this talk, Sam Tideman presents a case study from Northshore Univeristy Healthsystem that combines prescriptive modeling, machine learning, personalized medicine, and a learning health system to treat common neurological disorders. This offers a blueprint that can be applied across healthcare and even across industries.

Sam Tideman Data Scientist NorthShore University HealthSystem

Overcoming the Challenges of Introducing Big Data and Machine Learning Technologies in AML Programs

Ivana Donevska Executive Director, AML Data, Analytics and Technology USAA

Chair's closing remarks

Networking Drinks Reception

Day 2

Registration & Breakfast

Chairperson Overview

Jane Urban Director, Specialty Decision Support and Reporting Takeda Pharmaceuticals

Productive Analytics: Ways to Build a Data-Driven Culture

• Explore benefits and challenges of the center of excellence (COE) model

• Implement a feedback loop between stakeholders and data scientists

• Navigate internal barriers to gain stakeholder buy-in and promote cross-functional education of value

• Develop an organizational culture to support high-quality data and seeking to understand business questions through modeling

Jane Urban Director, Specialty Decision Support and Reporting Takeda Pharmaceuticals

Utilizing Artifical Intelligence to Personalize Social Media Interaction

As price matching and commodity like pricing have become the norm in retail, the zero moment of truth is typically too late to be targeting consumers. The proliferation of social media and consumer willingness to express need before they search represents a big opportunity for retailers to reach people, not personas, which leads to better and more consistent conversion into customers.

Sean MacCarthy Executive Director Global Analytics and Store Segmentation Claire's

Recent Advancements in Natural Language Processing

Research in Natural Language Processing and Deep Learning has been evolving rapidly over the past 5-10 years. This has led to exciting developments in Word Embeddings, Text Generation, Translation and Summarization. This session will take the audience through a crash course in technical concepts including neural networks, deep learning, word2vec, RNNs, LSTMs and seq2seq.

Alice Zhao Senior Data Scientist Metis

Networking Coffee Break

Bridging the Gap Between Academia and Industry: Methods For Building Data Science Teams For Both Managers and Data Scientists

We can all agree that, however important it is, the concept of Data Science and how it fits into an organization is one of the most misunderstood and one of the biggest challenges of business analytics today. We will discuss insights that will benefit both students and managers in how best to build and lead an effective analytics team. Key topics will include skills and tools that will give students and recent graduates an advantage in today’s analytics climate, how to productionalize data science work, effective ways of team working, and strategies for leading a team of data scientists.

Lance Levenson Senior Data Scientist / Adjunct Professor Northwestern University

Applying Machine Learning in Education

Based on a survey conducted by the U.S. Department of Education, the Illinois School Board of Education (ISBE) recognized that educators in the state could benefit from an Early Warning System that identifies students at risk of missing key educational milestones. ISBE and the DoIT State Data Practice have collaborated on a study that identifies major indicators based on performance data and attending school’s demographics. A systematic stepwise correlation study and machine learning were employed to score students based on their middle and early high school academic performance to determine probabilistic drop out tendencies. These measures could provide an alert for educators and schools.

Krishna Iyer Chief Data Scientist State of Illinois

AI, Machine Learning and Deep Learning at Motorola

In this talk, I will overview recent advances happening in machine learning (ML) field, majorly on deep learning (DL). I will later cover the applications and the latest development of AI, machine learning and deep learning technologies at Motorola, including 4 major areas: AR/VR, embedded ML/DL for device AI, smart IoT and intelligent custom relation management (CRM). In detail, I will focus on our recent success in light weight DNNs for computer vision and speech recognition, products development in AR/VR and IoT, as well as examples showing how we have been addressing Intelligent CRM.

Zhengping Ji Director of Machine Learning Motorola Mobility


Panel Discussion: Leveraging BI & Predictive Analytics in the Digital Age

The need for large-scale data analytics has become crucial for organizations to tackle head on. With the multitude of information in today’s Digital Age, the need to implement effective strategies leveraging Business Intelligence to Predictive Analytics has become more crucial than ever before. Join a panel of subject matter specialists to learn about today’s current trends & strategies in addressing today’s data overload.

Simon Hunt Former Director, Product Management, New Data & Digital Business Models at BMW Industry Expert
Joel Freiburger Director, Business Intelligence, Data & Marketing Analytics Enova International
Steven Ulinkski Security Data Scientist Health Care Service Corporation
Haley Kwait Director, Business Analytics Mac & Mia

Best Practices in Data-enabled Innovation That Have Stood the Test of Time Across Industries

Buzzwords and silos get in the way of identifying common themes of what works (or does not) in our profession. I recently collated about 45 examples of data enabled innovations spread over 15 years and a mix of industry verticals. Turns out there maybe some common and consistent themes after all. I am sharing my findings and inviting colleagues and peers to do the same. If any 10 leaders did this, we would quickly more reliable findings based on hundreds of case studies.

Guha Bhagavan Director, Data Science Grainger

Networking Coffee Break

Building a Data-Driven Organization With Lean Resourcing

In a startup environment, resources are scarce and everyone must be scrappy. This seminar will dive into how we at Catch Co built our data and analytics organization from the ground up to facilitate a self service environment that allows us to push forward on sophisticated and impactful projects while ensuring our end users have access to the data they need, when and how they need it.

Geoffrey Champlin Sr. Director Strategy & Advanced Analytics The Catch Company

Creating Real Value in Real Estate Data

From energy savings to maximizing your real estate portfolio to enhanced human experiences, technology and analytics can generate significant value for an organization. Learn how your facility generates a mountain of data and how to leverage that data to enhance both employee productivity and the bottom line.

Gary Meyer Director, Business Intelligence & Analytics Jones Lang LaSalle