Session Abstract:
Have Questions about Explainable & Trustworthy AI? Join us, for our panel discussion, as we are sure to answer your questions! Artificial intelligence plays a critical role in driving innovation and enhancing automation across diverse industries. With widespread adoption of Artificial Intelligence in IoT systems, comes the need to increase our focus around transparency, accountability, and trustworthiness. To address these areas, the AI IOT community must come together to explore the realm of Explainable AI in order to foster a deeper understanding of trustworthy AI systems. This panel discussion aims to highlight the intricate relationship between AI and IoT, emphasizing the urgent need for explainability and trust in AI-powered IOT applications. Experts from industry will converge to share their perspectives, and practical experiences in predictive maintenance, finance, regulated industries, energy, and intelligent manufacturing.
Key discussion topics will include:
- Use cases for Explainable and Trustworthy AI
- Addressing Explainable and Trustworthy AI requirements
- Describing Explainable and Trustworthy AI best practices
Speakers:
Dr. Gül Ege is the Senior Global Director for SAS IoT Research & Development (R&D), leading advanced analytical components innovation for SAS’ global customer and partner stakeholders. Dr. Ege leads a team of world-class scientists, helping SAS customers and stakeholders solve complex, real-world problems. Dr. Ege has held positions of incremental responsibility within SAS R&D for over 34 years. She has significant expertise in high-value vertical markets; having led projects in Finance, Risk, Retail, Energy and Manufacturing over the course of her career. Dr. Ege holds a B.S., M.S. and Ph.D. in Industrial and Systems Engineering. She received her Ph.D. from NC State University and is a registered professional engineer in the State of North Carolina. A celebrated career engineer and scientist, she has been awarded the SAS CEO Award of Excellence and the NCSU Industrial and System Engineering Distinguished Alumni Award. As an IoT and AI industry leader, Dr. Ege holds leadership positions at several industry organizations and associations, including as Chairperson of the NCSU-ASSIST Advisory Board and as an Advisory Board Member of both NCSU-CARTA and the IoT Community–where she holds the position of Chairperson on the Artificial Intelligence of Things Center of Excellence (COE). She is also a proud member the INFORMS-Edelman Committee and SIGKDD. Dr. Ege is passionate about mentoring, with a particular focus on supporting young women in STEM and empowering junior team members. She lives in Cary, North Carolina and enjoys spending time with her family, especially her two young grandchildren and devotes her free time to causes benefitting the well-being of women and children.
Audrey Reznik is a Sr. Principal Software Engineer in the Red Hat Cloud Services – OpenShift Data Science team focusing on managed services, AI/ML workloads and next-generation platforms. She has been working in the IT Industry for over 20 years in full stack development to data science roles. As a former technical advisor and data scientist Audrey has been instrumental in educating data scientists and developers about what the OpenShift platform is and how to use OpenShift containers (images) to organize, develop, train and deploy intelligent applications using MLOps. She is passionate about Data Science and in particular the current opportunities with ML and Open Source technologies.
Justin is responsible for managing solution integration initiatives within the product strategy organization across all AI/ML products and Line of Business Solutions at SAS. As a Product Manager he helps to guide the direction of AI/ML development with a focus on scalability, performance, and trustworthy AI. Justin holds a bachelor’s degree in Industrial Engineering from North Carolina State University as well as a master’s degree in Business Analytics from Wake Forest University. Prior to joining SAS, he held various roles across a wide range of industries including, Energy Management, Retail, Manufacturing, and Tech.
Andrii Ryzhkov is an AI Consultancy Leader at SoftServe. He has extensive experience in Data Science, Machine Learning, and Natural Language Processing and has worked with international clients in Banking, Financial Services, and Insurance. He excels in developing prototypes and industrializing ML pipelines to ensure Data Science initiatives achieve their full potential. Andrii also has experience building and managing Data Science teams to help organizations build strong, sustainable AI/ML capabilities.
Mei Zhang is Director of Data Science at Otis Elevator Company responsible for delivering AI/ML solutions for Condition Based Maintenance program and for supporting regional service operations. Before joining Otis in 2020, Mei spent 18 years in aviation industry providing analytical solutions for aircraft maintenance operations. Mei obtained her PhD in Industrial and System Engineering from Georgia Institute of Technology. She currently serves on INFORMS Practice Session board and is a member of Women in Technology International.
