Describe what your organization does, and how it relates to data science.
Data science is a core component of industrial and systems engineering. Industrial and systems engineers work to design and improve processes and systems in every field imaginable. To do so, they must access data, analyze and interpret data, and make decisions based on that data.
Why is sponsoring the Research Bazaar important to you?
The relatively recent explosion of access to data is thrilling, but also daunting. It’s important for us to be both a leader and a supporter in this important field.
In what ways are AI and ML tools transforming the methodologies and potential outcomes of research within your specific field?
The emerging AI and ML tools can handle extremely large and complex datasets, which enables more accurate prediction of system performance and optimal decision-making for large scale systems. These tools create new opportunities and capabilities for operations research and system quality and reliability improvement.
Can you share an example of a research project where AI or ML significantly accelerated discovery or provided novel insight?
Our faculty has developed novel industry AI techniques that can fuse the complex temporal in-process sensing data from a semiconductor manufacturing process, and then use the knowledge learned to monitor the process and identify the root cause of the abnormal conditions. The accuracy and granularity of the AI-enabled process monitoring schedule is unprecedented.
Can you share a success story where your organization’s data science efforts had a positive impact on a broader community?
The Internet of Things (IoT) Systems Research Center, an university-industry partnership within our department, regularly organize tutorials on emerging AI and ML technologies used in IoT systems. Those tutorials have attracted significant interests from industries.
Are there any notable collaborations or partnerships your organization has formed to advance data science research or applications?
Our faculty has been working with many companies on AI and ML based projects for system control and improvement, including Oshkosh, Toyota, 3M, and Jewelers Mutual, just to name a few.
How does your organization approach ethical considerations and responsible use of data in your data science endeavors?
Dr. Yonatan Mintz’s research focuses on the application of machine learning and automated decision making to human-sensitive contexts. He is specifically attracted to the issue of ethics and privacy implications in the rise of AI. His conclusions take into account the need to address things like the historical context of data, where data is collected, and the inherent bias that is unavoidable with the human beings behind the models.