Artificial Intelligence in Operations:
Transforming Supply Chains and More
November 9-10, 2023 | AT&T Conference Center
Recent interest in Artificial Intelligence and Machine Learning holds immense importance in today’s rapidly evolving business landscape, particularly in operations. These new technologies have emerged as powerful tools capable of revolutionizing how companies do business across industries.
The strategic implementation of technology can drive operational efficiency, enhance customer experiences, and enable data-driven decision-making. It can also empower businesses to automate repetitive tasks, improve forecasting accuracy, optimize resource allocation, and uncover valuable insights from vast amounts of data.
When implementing AI / ML, companies across different industries often have specific questions and considerations tailored to their unique needs and challenges. During this event, we intend to explore the potential applications of AI / ML in various business functions by addressing the critical challenges that might unlock new opportunities.
Our two-day program will feature expert insights from the front lines of industry’s AI / ML transformation. Get involved in the discussion – take advantage of ample Q&A and networking opportunities.
Conference Schedule
Activity schedule for Operations Conference
| Activity (Location) | Time |
|---|---|
| Thursday, 11/9 | |
| Conference Check-In (AT&T Center Ballroom DE) | 5:15-5:45 PM |
| Networking Reception (Grand Salon DE) | 5:30-6:30 PM |
| Welcome Remarks (Grand Salon DE) | 6:30-6:45 PM |
| Networking Dinner (Grand Salon DE) | 6:45-8:00 PM |
| Friday, 11/10 | |
| Breakfast (Tejas Room) | 7:00-8:45 AM |
| Welcome Remarks (Classroom 203) | 8:50-9:00 AM |
| Keynote Speaker #1 (Classroom 203) | 9:00-10:00 AM |
| Networking Break | 10:00-10:30 AM |
| Keynote Speaker #2 (Classroom 203) | 10:30-11:30 AM |
| Conference Industry Panel (Classroom 203) Student moderated discussion |
11:30-12:15 PM |
| Conference Networking and Lunch (Classroom 103) | 12:30-1:30 PM |
Meet the Speakers
Keynote Speaker: Inranil (Indy) Bardhan
Indranil Bardhan is Foster Parker Centennial Professor of Management in the McCombs School of Business at the University of Texas at Austin. He is a Distinguished Fellow of the INFORMS Information Systems Society. His research focuses on healthcare analytics, digital health innovation, and the economic impact of information technology, and involves close collaboration with the University of Texas Southwestern Medical Center and the UT Dell Medical School. His research has been funded by the National Science Foundation and the UT Health system. His research has won seven best paper or runner-up awards and he currently serves as Senior Editor at Information Systems Research, and Associate Editor at Management Science. He previously served as Senior Editor at MIS Quarterly and co-editor of a special issue on “The Role of Information Systems and Analytics in Chronic Disease Management.” Dr. Bardhan teaches in the MBA and MS programs at the McCombs School of Business and the UT Health Dell Medical School.
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Keynote Speaker: Padampreet Singh
Padampreet is a Managing Director and Chief Data & Analytics Officer for High Tech Industry in
Accenture’s Data & AI practice based out of San Francisco. He has deep expertise in customer & supply chain functions with strong experience in Generative AI, Data & AI strategy, Modern Data Platform, Data Governance and Data Management. His broader experience includes leading large engagements in areas like Digital Transformation, Customer 360, Sales & Control Towers, Data Science & AI COEs, Manufacturing Quality Analytics, Master Data Management etc. He has advised executive teams at organizations across US, Europe and Asia supporting development of overall Data & AI strategies.
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Panelist: David Schaub
Working within an internal AI consultancy, David spearheads the end to end design and implementation of software incorporating AI. David channels his engineering roots to meet with experts from the business and turn their needs into programmable inputs and outputs, going from PoC to MVP to deployment with a handoff plan for IT. David is accomplished in the predictive maintenance, subsurface, and retail fuels pricing domains complete with global deployments of applications, platforms, and entire predictive systems. For fun, David delves into IoT devices, lifting weights, arcade cabinet repair, and PCB design.
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Panelist: Jeffrey Vah
Jeffrey Vah is an experienced Distinguished Member of Technical Staff and trusted strategic advisor in Dell’s Supply Chain Global Operations team with over 30 years’ experience in computer engineering technology driving transformation for the Services ecosystem. He serves as a technology strategist and Innovation Champion in Reverse logistics, Sustainability, and AI/ML technology domains. Jeff also serves as a key member of our Partner Innovation council, and has co-invented over 10 patent pending solutions in AI/ML, predictive analytics, cloud solutions, and machine vision to enable global Supply Chain and Partner transformation.
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Panelist: Hernan Chavez
Hernan Chavez is a Senior Data Scientist at HEB DSCOE (Data Science, Clickstream, Optimization, and Experimentation) team. For over 5 years he has led efforts that provide innovative solutions to important challenges. Some of these include building optimal last-mile fleet routes, recommending dispatching schedules for mid-mile routes, optimally assigning forecast task hours to partners at multiple stores, and providing systems that support decisions related to immediacy orders picking and orders retrieving for last-mile. He has also actively contributed to other projects such as Polygons Design, Speed Wall Assortment, Markdown Pricing, and Substitute Products Recommendations. He holds a Master’s degree from Lancaster University (U.K.) and Ph.D. from The University of Texas at San Antonio. Experience previous to joining HEB includes collaborating in a research team at Oak Ridge National Laboratory for developing models that optimize the logistic processes related to the supply of feedstock for the production of biofuel.
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Supporting Companies
