2019 Conference Videos

Semantics is linguistics and natural language processing to help make sense and meaning of the world around us. In visual analytics, using principles of semantics can help improve the meaning and overall cognition of a visualization to the user. In this talk, we will discuss how we are thinking of adding semantics to help enrich various aspects of the visual analytics workflow. By incorporating and inferring general concepts to empowering users to add domain-specific knowledge, semantic governance can bring more meaning to the analytical experience.

Vidya Setlur is a manager on the Natural Language Team at Tableau Software, and works out of the Palo Alto office. Previously, she was a staff research scientist on the research team and prior to joining Tableau, worked as a principal research scientist at the Nokia Research Center for 7 years. She earned her doctorate in Computer Graphics in 2005 at Northwestern University. Her research interests lie at the intersection of natural language processing (NLP) and computer graphics, around semantics and visual interfaces. At Tableau, Vidya works on natural language interfaces to help enable analytical conversations with data.

This session explores how AI will change the consumer experience; from big data, personalized services, always-on predictions, and more. We also discuss the implications for privacy, regulation, ethics, and human-machine interaction.

Moderator - Matt Sebek, Vice President of Digital, World Wide Technology

Dheeraj Patri - Co-Founder & CTO at Label Insight

Tony Sardella - CEO, Evolve24

Michael Wojcik - VP, Enterprise Technology Services, Panera

We’re finally here! We’re living in the future we always dreamed about and that our parents never thought would ever come. We literally have machines deployed for us, representing us, and all around us … and they do stuff for us and bring us things! We trust our machines, too. We have built them to do intimate, human things: to connect us, to offer lifelines, to find us love, to understand our DNA, to make us healthier. We’re so lucky! BUT. As we use machines more and more to represent us, do we lose a portion of our own humanity? As the technologists that build these machines, do we lose more of our humanity in the delivery? Do we build machines to represent the people that we are, or do we impersonate machines? In “How to Build a Nicer Machine: The Movement to Humanize Data and Interactions” we’ll reflect upon where we are as a society of technical consumers and builders to explore the challenge of building machines more like us and to consciously, actively choose to become less like robots. We’ll explore a humanization framework that includes tangible ways to humanize the data we use to deliver meaningful digital interactions.

Christina Vallery joined Express Scripts in the summer of 2016 with a purpose-driven focus on applying a design thinking mentality to the problems facing healthcare and with a mission to do work that contributes to the broader world community. In her time at Express Scripts, she’s engaged in a long-term build of the design system of the future: one that applies human feeling in its expression.

Danielle Smith joined Express Scripts in 2016 because building a team tasked with keeping part of the healthcare experience grounded in the values, needs, and abilities of patients sounded like the kind of crazy-ambitious-noble mission that she loves. Over the past 3 years, that mission has helped to move Express Scripts that much closer to providing a service that feels human. Danielle uses her training as a social scientist coupled with her prior experiences in product market research consulting and technology development to build a cohesive approach to experience insights – uncovering and combining qualitative and quantitative insights in ways that help shape digital experiences that deliver care.

In this talk, Kay Apperson highlights the value of Smart Manufacturing which is one of the cutting-edge pillars that enable the Industry 4.0 time that we are in. In addition to honing in on the Vision AI used in a Fiber Optic Cable Defect Detection project in collaboration with MIT, she walks through key real-world use cases in Smart Manufacturing. Those use cases center around two AI solutions -- Predictive Maintenance and Defect Detection. She discusses in-depth the Big Data enterprise-grade architecture necessary for these solutions. For the Vision AI application that is powered by Microsoft Azure Cognitive Services – Custom Vision, she walks through the actual application that was built for the MIT project. Since the fiber optic problem is a more challenging problem to solve using Vision AI due to the nature of the object that is a very thin line, the demo of the application will underscore the level of success that AI could achieve to date. A goal of the Vision AI application is to categorize in real-time on the plant floor with high accuracy whether a fiber optic cable is produced correctly or it is a defect.

Kay Apperson, PhD is a Data Solution Architect and Data Scientist at Microsoft U.S. Manufacturing. She’s worked with many U.S. manufacturing and automotive companies to successfully transform their manufacturing decision making using a data driven IIoT approach. Some of the benefits the companies gain are such as preventing machine downtime, reducing or eliminating unnecessary maintenance, improving safety, improving production planning, and reducing scraps and wastes. In 2008, Kay received a PhD in Computer Engineering and Computer Science with a dissertation in data mining. During the research time, she won 1st prize winner awards from a couple of knowledge mining competitions. Some of her past employers are such as Centene, Monsanto, Harvard University, and Massachusetts General Hospital.

"A New Era of Data Responsibility, Transparency, and Stewardship" Prepare.ai CoFounder David Karandish kicks off the conference and introduces Keynote Speaker Tony Sardella. Tony has applied an arsenal of data science and behavioral research techniques to tackle complex, nonmarket issues at clients like IBM, Airbnb, Ford, and Nestle.

This is an exciting time in health care because of Machine Learning and Artificial Intelligence (AI). Cloud services and modern processing power have helped technology catch up to the research and theory behind AI. Health care organizations can now turn to the most advanced Machine Learning tools and techniques to streamline patient care workflow, identify new treatment plans, and automate diagnoses.

Mark Bennetts - Product Management, Mercy Virtual

Brandon Fischer - Practice Lead, 1904 Labs

Matt Pitlyk - Technical Lead, 1904 Labs

Women hold only about a quarter of data jobs in the United States. Why is this number so low? What challenges and obstacles stand in the way of women in high tech, and what is being done about it? We will hear from talented women that live and breathe these questions in the primary and higher educational spaces, in a high tech startup, and in a large enterprise.

Moderator - Tara Nesbitt - Experience Design Lead at Slalom Consulting

Katrina Brundage - Data Scientist & Legal Analyst, Juristat

Sherea Dunlap - Executive Director, Create a Loop

Eshe Hawash - Targeted Training Manager, Launch Code

Vicki Sauter - Professor of Information Systems, UMSL

Vidya Setlur - Manager of Natural Language Team, Tableau Software

AI and machine learning are technical fields, which can mean they are siloed to data scientists and engineers. This limits the awesome potential of AI. If we instead view AI as a new tool for everyone to use, it will lead to an explosion of creativity in AI’s uses. In this session, we will explore how companies can expand their thinking around AI’s uses and how they can activate their whole staff to be AI advocates.

Jesse Wolfersberger is the Chief Data Officer for Maritz Motivation Solutions. He leads Maritz's Decision Sciences team, a group of data scientists who specialize in merging the fields of behavioral science and artificial intelligence. Jesse's career started as a sports writer, before jumping into marketing as Director of Consumer Insights for GroupM's digital media think tank. In his free time, Jesse uses his data skills in the baseball world, where he consults for a Major League team.

Over the past 2 years the evolution of Machine Learning has made monumental advances and the changes are only accelerating. Some of these advances are due to the ability to automate the selection of the correct algorithms, which enables faster time-to-value for solutions. We will explore these ideas in the context of the Big Squid SaaS platform, which automates much of the workflow involved in training machine learning models and putting them in production.

Jorge Zuloaga got his masters in mathematics from the University of Waterloo in Canada and his PhD in computational physics from Rice University in Houston, TX. His work in computational mathematics and physics has spanned several fields, from particle physics to healthcare, and beyond.

The currency of tomorrow isn’t what you think: It’s not cold hard cash, precious metals, land or even cryptocurrency – it’s data. In the very near future, every company in the world will either buy or sell data as this corporate asset continues to gain value. But, it’s not enough to have access to vast amounts of data, you need to understand it and use it. Transforming data to business value is harder than many companies thought it would be, requiring deeper resources, more expertise and harder work than expected. This session will detail how Intel builds AI systems that can access and analyze large datasets so businesses can take advantage of the explosion of data as the fuel powering digital transformation. Melvin Greer, Intel Chief Data Scientist will describe how artificial intelligence and machine learning help transform data effectively and deliver experiences people have never seen before or imagined.

Melvin Greer is Chief Data Scientist, Americas, Intel Corporation. He is responsible for building Intel’s data science platform through graph analytics, machine learning and cognitive computing to accelerate transformation of data into a strategic asset for Public Sector and commercial enterprises. Mr. Greer has been named a 2018 AI Executive of the Year by Washington Executive. He has been awarded the 2017 BDPA Lifetime Achievement Award and the 2012 BEYA Technologist of the Year Award. Melvin is also a Professor in the Data Science program at Southern Methodist University (SMU) and Adjunct Faculty, Advanced Academic Program at Johns Hopkins University. He functions as a principal investigator in advanced research studies, including Nanotechnology, Additive Manufacturing and Gamification.

This panel of leaders in the technology investment space delves into the impact that AI is having on new ventures. Investors are expecting large returns from AI enabled business models, but how and why? And what are the pitfalls and challenges that one should keep in mind?

Moderator - Cindy Teasdale - Marketing Director, Prepare.ai

Emily Lohse-Busch - Executive Director, Arch Grants

Brian Hopcraft - Managing Director, Lewis & Clark Ventures

John True - General Partner, Cultivation Capital

The AI for Earth program applies machine learning and data science to hard challenges in agriculture, water, climate, and biodiversity. In this talk, we will discuss how the AI for Earth team, Microsoft Research, and AI for Earth grant recipients are using machine learning to enable precision agriculture, to predict outbreaks of disease, to detect poachers in real time, and to classify animals for conservation. Finally, we will briefly provide details on the AI for Earth grant program to obtain resources for everyone to work on these challenges.

Jennifer Marsman is the Principal Engineer of Microsoft’s “AI for Earth” group, where she uses data science, machine learning, and artificial intelligence to aid with clean water, agriculture, biodiversity, and climate change. Jennifer is a frequent speaker at software development conferences around the world. Since 2016, Jennifer was recognized as one of the “top 100 most influential individuals in artificial intelligence and machine learning” by Onalytica, reaching the #2 slot in 2018. She has been featured in Bloomberg for her work using EEG and machine learning to perform lie detection. In 2009, Jennifer was chosen as "Techie whose innovation will have the biggest impact" by X-OLOGY for her work with GiveCamps, a weekend-long event where developers code for charity. She has also received many honors from Microsoft, including the “Best in Role” award for Technical Evangelism, Central Region Top Contributor Award, Heartland District Top Contributor Award, DPE Community Evangelist Award, CPE Champion Award, MSUS Diversity & Inclusion Award, Gold Club, and Platinum Club. Previously, Jennifer was a software developer in Microsoft’s Natural Interactive Services division. In this role, she earned multiple patents for her work in search and data mining algorithms. Jennifer has also held positions with Ford Motor Company, National Instruments, and Soar Technology. Jennifer holds a Bachelor’s Degree in Computer Engineering and Master’s Degree in Computer Science and Engineering from the University of Michigan in Ann Arbor. Her graduate work specialized in artificial intelligence and computational theory.