Big Data Summit

BIG DATA SUMMIT

Thank you to the hundreds of you that braved the weather to attend Big Data 2019! Please take a moment to fill out our survey so we can improve Big Data in the future.

Stay tuned for videos of each panel to be posted here. In the meantime, please see notes from each panel below. 
Be sure to save the date for next year's Big Data Summit, taking place on November 12, 2020.


Big Data Summit Notes | November 12, 2019

7:45 – 8:15

Registration and Breakfast

8:15 – 8:35

WELCOME REMARKS
Laura Frerichs
University of Illinois Research Park, Director
Laura Frerichs is the University of Illinois Research Park Director.  She is responsible for managing startup company services at the EnterpriseWorks technology incubator, marketing the Research Park and supporting the University’s economic development efforts. Frerichs has developed innovative entrepreneur support programs as well as has attracted many new companies who are interested in engaging with the University of Illinois.

Robert Brunner
University of Illinois Gies College of Business, Chief Disruption Officer
Robert J. Brunner is a professor in the Department of Accountancy in the Gies College of Business and is the Director of the University of Illinois-Deloitte Foundation Center for Business Analytics. He has affiliate appointments in multiple departments and is also the Data Science Expert in Residence at the Research Park at the University of Illinois. His primary research goal focuses on the application of statistical and machine learning to a variety of real-world problems, and in making these efforts easier, faster, and more precise.

8:35 – 9:30

MORNING KEYNOTE ADDRESS: Machine Learning and Health

Sanmi Koyejo

Sanmi Koyejo, Assistant Professor of Computer Science at the University of Illinois focuses on developing the principles and practices of adaptive and robust machine learning.  Additionally, Koyejo focuses on applications to neuroscience and biomedical imaging.

During his morning keynote “Machine Learning and Health”, Sanmi discussed the potential of technology in personalized health care. Machine learning is broadly adaptable and improves with better modeling.  A synergistic approach in combining expert predictions with data can move machine learning forward.  Core technologies on the research side of development are good enough to apply to real systems, but adoption is critical.  In healthcare, it is easy to lose trust if medical data is inappropriately shared.

Sanmi walked participants through his work in improving techniques for improving tumor images.  Current models are doing a good job predicting tumor and surrounding images.  By working on these models, his research is looking into how different cancers evolve based on profile, how to better target cancer treatment and clustering patients into groups to work within separate biologic points of view.

Technologies are enabled through modeling, evaluation, privacy and trust.  Good metrics, data aggregation and believing in the machine learning model to understand what has been learned.  This then creates clear next steps and any actionable recourse necessary.

The implications of utilizing machine learning can capture large amounts of data, better scans and less radiation on patients.  Machine learning can work well and ensure privacy by never having to share data with a centralized hosting service.  Federated machine learning predictions are of the same quality as those gleaned from a centralized server.

The most vulnerable time is during the training phase where data or model poisoning could throw out bad examples to lead to catastrophic failure.  An attacker can try to get into the system to do something wrong and change the result to what they want.  Progress is being made around predicting potential attacks and understanding vulnerability is always important. Privacy is a key as machine learning for health grows. There is tension in making sure models are understandable enough and still maintains consumer trust.

Koyejo completed his Ph.D. in Electrical Engineering at the University of Texas at Austin advised by Joydeep Ghosh and completed postdoctoral research at Stanford University with a focus on developing machine learning techniques for neuroimaging data. His postdoctoral research was primarily with Russell A. Poldrack and Pradeep Ravikumar. Koyejo has been the recipient of several awards including a best paper award from the conference on uncertainty in artificial intelligence (UAI), a Kavli Fellowship, an IJCAI early career spotlight, and a trainee award from the Organization for Human Brain Mapping (OHBM). Koyejo serves on the board of the Black in AI organization, which he co-founded.

9:30 – 9:40

Break

9:40 – 10:35

THE VALUE OF ARTIFICIAL INTELLIGENCE: What Technologies Have the Most Value?
Stakeholders in the tech industry are looking for ways to effectively implement artificial intelligence into their businesses and drive value. Whether it is Natural Language Generation, Open Source Frameworks, Facial Recognition tools or AI hardware, our panelists will discuss what technologies they find the most value in for their industry sectors.

Moderator Kim Mendoza, Gies College of Business
Matt Ahrens, Verizon Media, Sr. Director, Engineering
Gui Maia, Ameren, Senior Data Scientist
David Charles, John Deere, Manager of Data Driven Innovation
Abby Scott, COUNTRY Financial, Senior Predictive Modeler

AI has a variety of definitions, but for the purpose of our panel discussion, it’s the simulation of data and human intelligence by computer systems including speech recognition and machine learning.

AI is a big deal because we’re opening ourselves up to utilizing massive amounts of data in new ways.  AI enables us to interpret and industrialize that data.  AI’s potential lies in high data quality.  It’s important to obtain information that will be most useful to drive business operations keep it simple enough to process and use it.

Technologies are valuable when used in tandem; proprietary models and open source packages, for example.  The tools most helpful are ones used to explain the data to both users and experts.

The key for maximizing use of any technology is based on need.  It’s about solving a specific problem and not finding an interesting technology and trying to find a problem to solve with it.  Anyone in the industry must listen to business trends to determine what is needed for problem solving.  You want to maximize engagement with use of any technology.

In some circumstances, AI isn’t necessary.  Utilizing human decision making as opposed to creating complex models may be most effective.   AI is still running up against limitations including explaining the importance and possibilities of Big Data to business leaders and partners.  Having business leaders understand the companies’ needs and match that with what Big Data can provide is a challenge.

Technologies that provide accurate data is critical.  At John Deere, for example, sensors provide important information like whether equipment is being operated optimally.  Some of that sensor data goes back into the manufacturing process to ensure new designs work.  Technology helps with customers and ultimately what new ways consumers are using the equipment.

Some of our panelists view success as the ability to scale complexity.  Abby Scott from COUNTRY Financial indicated that developing an AI pipeline is important to adding value to her business.  Ensure the modeling is going well and continuing to work on that data for deployment.  Ameren’s Gui Maia defines success as improving risk assessment of assets.  He values establishing probabilities of an asset to fail versus other risk areas.  Ameren is very engaged with this information and works closely with cloud tools.

Opportunities for AI will grow, especially as 5G grows.  David Charles from John Deere specifically expressed this as he discussed how they receive data back from their customers. Managing data could be enhanced when processing can be done on combines and tractors themselves, thus making things more efficient.  AI will be disruptive to many industries and can ultimately assist with workers being trained to perform faster in tasks like repairing utilities.

In order to prepare for this fast-moving world, students should be balancing technical skills and business skills.  It’s important to understand different types of computer languages but having statistical capabilities can make an individual stand out.  Panelists also discussed cultivating soft skills like being a good listener and team player. 

10:35 – 11:30

ANALYTICS AND TALENT: Developing Leaders in Data Science
Data Science has the potential to drive efficiencies, mine new insights and transform businesses, but the field needs a well-trained talent pool to meet the rapidly growing demand to process complex data challenges.  The University of Illinois and companies in the Research Park will discuss how they are working collaboratively to prepare students to move Big Data forward.

Moderator Amy Fruehling, University of Illinois Urbana-Champaign, Career Services Professional
Mohan Ayikara, CME Group, Director of Data Science, Intelligence and Analytics
Alice Delage, National Center for Supercomputing Applications, Project Manager
Ann Peedikayil, Caterpillar, Senior Digital Analyst Project Leader and Data Scientist
Jeff Rambole, State Farm, Senior Data Scientist
Misha Shah, AGCO, Site Manager

There is explosive growth in Big Data as volume, velocity and variety of data continues to rise.  The lack of skills in data analytics is hindering the potential of this industry and professionals are needed to sift through the ‘immensity of stuff’ to uncover the relationships meaningful to business.  A true solution to addressing the labor shortage would require a cohesive approach across education and industry by increasing the number of students studying in this space and providing career advice and role models.

Ann Peedikayil of Caterpillar brought specific examples of what students need to light during her remarks.  She indicated that potential employees must understand the connectivity of equipment, platforms to house data, interactions with customers and dealers, applications to serve both groups and then develop the data insights from these many inputs.  Engineering, math and statistics are talents needed to achieve this.  Caterpillar works with student organizations in very intentional and engaged ways.

CME Group’s Pritam Das understands the value of entry-level individuals and works with students from the Research Park, City Scholars Program and a rotational entry level program.

Misha Shah, Site Director at AGCO Corporation strategically interacts with students at multiple touchpoints throughout the year and not just career fairs.  AGCO’s business lines require individuals studying computer science, web design, UI/UX, augmented reality and data science.

State Farm’s Research and Development Center located at the Research Park runs the Modeling and Analytic Graduate Network or MAGNet Program. Students in MAGNet are expected to enroll in a new master’s curriculum created via a relationship between State Farm and the U of I’s Statistics Department. This program cultivates an individual’s quantitative background in math, statistics and actuarial sciences to lead to machine learning engineering.

11:30 – 12:00

Lunch

12:00 - 12:45

AFTERNOON FIRESIDE CHAT

Moderator, Laura Bleill
University of Illinois Research Park, 
Director, Communications and External Engagement
Laura Weisskopf Bleill manages the community building portfolio at Research Park. She develops strategy behind the Research Park’s events and programming; communications, branding and marketing efforts; and directs the Research Park’s efforts to grow and retain its workforce. Bleill started her career in sports journalism, where her work appeared in daily newspapers including The News-Gazette, the Fort Worth Star-Telegram, the St. Louis Post-Dispatch and others. She has a master’s and bachelor’s degree in journalism from Northwestern University.

Kingsley Osei-Asibey
Department of Intercollegiate Athletics, Director, Analytics & Football Technology
Kingsley Osei-Asibey grew up on the south side of Chicago and received his BA in Computer Science from Governors State University, IL. He has worked in technology for 6 years in the NFL prior to his arrival at Illinois. His role on the football team is to analyze data to pinpoint the opponent tendencies and also analyze their own data to see if there are any tendencies that the opponent may pick up on them.

12:45 - 1:45

ROBOTIC PROCESS AUTOMATION: Operating in a Human+ World
The explosive growth of Big Data has fueled our ability to develop automation tools to process unprecedented amounts of information. Our speakers will discuss how we utilize robotic process automation (RPA) and intelligent process automation (IPA) to streamline workflows, reduce human error and improve data quality to move the intelligence ecosystem forward.

Moderator, Lori Gold-Patterson, Pixo, CEO
Pritam Das, CME Group, Digital Business Platforms
Crystal Rhoads, AARP, Interim VP for Technology Transformation
Ujjval Patel, Synchrony Emerging Technology Center, Site Director

For the purpose of our panel discussion, the definition of RPA is the application of technology that allows employees in a company to configure computer software or a “robot” to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. According to our panelists, developing bots is most successful when dealing with a predictable task with replicable tasks that can be anticipated and needs to free up enough time to make meaningful changes in workforce and allow for transformation to work on more high value areas of work.  A background in Computer Science and programming is no longer necessary to develop bots thanks to new tools available.

CME group has a both in every department—35 bots in/going into production such as cyber security applications, auditing enterprises and one that interfaces with Salesforce. Companies today value accuracy and take data seriously; RPA helps with correcting and preventing errors. Pritam Das at CME Group highlighted the fact that Information Technology can often be done by bots based on risk.

Crystal Rhoads at AARP discussed an impressive example about their Senior Community Service Employment Program.  AARP trains 50+ people in underserved areas.  Currently it is a very manual process and once they looked to a bot to move their data, the process per individual went from 20 minutes to two minutes.  While increasing efficiencies in the workplace is a strong case to implement RPA, there are more criteria our panelists recommend.

Ujjval Patel from Synchrony shared that they are using RPA for accounting, reconciliations and governance review.  The financial industry being heavily regulated.  When tasks are automated and an error is found, their organization is very purposeful in monitoring for those situations. Automation leads to a workforce conversation and shows early wins by redeploying time saved and tasks achieved in an ethical manner.  Accounting transactions are easily automated and Synchrony’s HR is involved to help determine time savings and capture nuances.

RPA is rapidly changing; our panelists had a wide array of ways they stay up to speed on the latest trends. Not many business leaders in organizations are in tune with RPA and our panelists indicated they stay highly engaged in conferences, seminars and other events and learned the tools that were discussed.

Our panelists’ responsibilities go beyond IT and also work with business leaders and governance.  They recommend that students get a certification in something like Python and develop tools in order to build a portfolio.  Engineers should take business classes and business students should look into some engineering courses.

1:45 - 1:55

Break

1:55 - 3:00

AUGMENTED REALITY: Moving Beyond our Imagination
The latest augmented reality tools are transforming how we interact with the world around us and creating real-world utility in agriculture, health care, manufacturing and more with developments right here in Champaign-Urbana.

Moderator Dan Cermak, University of Illinois Urbana-Champaign, Informatics Lecturer
Miranda Kemp, AARP Director - The Tech Nest
Kesh Kesavadas, University of Illinois Urbana Champaign, Director of Health Care Engineering Systems Center
Jamie Nelson, Center for Innovation in Teaching & Learning, Principal, Emerging Technologies
Rachel Switzky, University of Illinois Siebel Center for Design, Director
Mani Golparvar, Reconstruct, Inc.

The latest reality tools are transforming how we interact with the world around us and creating real-world utility in agriculture, health care, manufacturing and more with developments right here in Champaign-Urbana.

This panel featured experts from academia and industry and discussed aspects of mixed, augmented and virtual realities.  For the purpose of our panel, mixed reality is the merging of real and virtual worlds to produce new environments and visualizations, where physical and digital objects co-exist and interact in real time. Augmented reality is a technology that superimposes a computer-generated image on a user's view of the real world, thus providing a composite view. And Virtual Reality is the computer-generated simulation of a three-dimensional image or environment that can be interacted with in a seemingly real or physical way by a person using special electronic equipment, such as a helmet with a screen inside or gloves fitted with sensors.

The various realities are developing quickly and our panelists have been surprised by how educational opportunities and tools have expanded.  These tools allow for time travel, visualizations, experience and accessibility. Instructors in anthropology, data visualization, language learning are all utilizing the latest technologies and students are using these tools to work on issues as wide ranging as concept design to social justice issues.

Consumer usage is widespread amongst the 50+ age demographic.  There are health and well-being issues addressed through these various realities. Virtual reality can help older adults explore places they might never travel or to environments with family and friends living far away.

The University of Illinois is a leader in developing these technologies.  The educational tools and programs important to train the next generation of leaders in the industry are coming out of programs like the Center for Innovation in Teaching and Learning.  Kesh Kesavadas of AirV Labs and Mani Golparvar of Reconstruct discussed that they look at the challenges they are facing in the health care and construction industries, respectfully, and maximize the potential found in collaborations with academia, startups and industry.  Miranda Kemp of AARP is also leveraging the high quality student talent and collaborating with startups.

3:00 – 3:50

DATA GOVERNANCE AND ETHICS: Enhancing Big Data Responsibly
AI Applications are becoming omnipresent in the workplace. As technology outpaces regulatory reform, the industry must ensure new developments avoid unintended consequences and address ethical concerns.  This panel will discuss the research around ethical questions and some of the principles being adopted around the world.

Moderator Verity Winship, University of Illinois Urbana-Champaign College of Law, Professor
Kevin Hayes, Corteva Agriscience, Global Lead of Data Science and Informatics for Strategic Communication
Sanford Hess, City of Urbana, IT Director
Elizabeth Luckman, University of Illinois at Urbana Champaign, Gies, Clinical Assistant Professor of Business
Matt Schaapveld, John Deere, Global IT Leader in Data and Analytics

Panel moderator Verity Winship is a professor at the University of Illinois College of Law.  Her work focuses on business law, regulatory enforcement and complex litigation.  She has brought her expertise in regulation and enforcement to issues in data law, presenting at university and industry data science summits and participating in panels on the law and ethics of Big Data.

The University of Illinois is cultivating strong leaders in the world of Big Data through faculty like Assistant Professor Elizabeth Luckman.  She focuses on teaching students collaborative decision making skills, avoiding group think, understanding the role of bias, importance of diverse perspectives and strong moral judgement. These skills will assist tomorrow’s employees in creating the rules and regulations of their companies’ uses of Big Data in a positive way.  In addition to being a faculty member in the Gies College of Business, Elizabeth is an R.C. Evans Data Analytics Fellow, Deloitte Foundation Center for Data Analytics, and Senior Academic Advisor for the National Center for Professional and Research Ethics.

In the meantime, we have industry and government working with unclear guidelines on how data can be culled and shared.  Matt Schaapveld, John Deere’s global leader in data and analytics, shared that as a global company, John Deere must work with different standards and practices based on government regulations. Matt is a Senior IT and data analytics leader with experience establishing enterprise level strategy for information technology, data and analytics, data governance and digitalization.

The panel also included Sanford Hess, IT Director for the City of Urbana.  Sanford oversees all technology used by the City of Urbana.  Since he started in 2013, Urbana has replaced most of its legacy mainframe systems with technology to capture more information.  Sanford discussed the role government plays in the type of data we access, with some municipalities making wide swaths of data public and others stonewalling any efforts to provide information.

3:50 – 4:00

THANK YOU AND CLOSING REMARKS

4:00 – 5:30

Career Networking Event
List of Participating Companies