Artificial Intelligence (AI) is reshaping our world at an unprecedented pace, influencing everything from daily conveniences to global economies. As AI technologies continue to advance and integrate into every facet of society, understanding their implications has never been more crucial. The following experts are available to the media to provide context and insight into the multitude of issues relating to artificial intelligence:
Qing Hu, Dean, School of Business
Qing Hu has devoted over three decades to research on the transformative impact of information technology on competitive strategies, business processes, and human behavior. His journey in this field began during his doctoral studies in the early 1990s, where he explored the potential of artificial intelligence, particularly artificial neural networks — the foundation of generative AI today, to revolutionize business decision-making. In recent years, leveraging his position as a business school dean, he has emerged as a passionate advocate for the integration of AI into education curricula. He is committed to preparing an AI-empowered workforce capable of not only meeting but embracing the challenges and opportunities presented by the AI-driven Fourth Industrial Revolution, and ensuring that the next generation of organizational leaders is well-equipped to navigate and shape the AI-transformed world.
Contact: qhu@pdx.edu
Christof Teuscher, Professor, Engineering & Computer Science
Christof Teuscher is an expert in building hardware for artificial intelligence and machine learning algorithms. The main goal of Teuscher's research is to design and build computers that are more intelligent, secure, and energy-efficient. He and his team in the teuscher.: Lab are developing disruptive new computing paradigms and machines that will allow for lasting breakthroughs and open new application domains in the next 5-20 years.
Contact: teuscher@pdx.edu
Ameeta Agrawal, Assistant Professor, Electrical & Computer Engineering
Ameeta Agrawal is at the forefront of Artificial Intelligence (AI) and Natural Language Processing (NLP) research. Her team is focused on developing efficient and ethical large language models (LLMs), with a particular emphasis on their practical applications across diverse linguistic landscapes. Through innovative projects, Agrawal is committed to creating AI solutions that are more robust, inclusive, and applicable in real-world, diverse environments. Agrawal was recently appointed to the Oregon State Legislature's Joint Task Force on Artificial Intelligence, where her expertise will help develop AI-related definitions, potentially informing future ethical guidelines and strategic initiatives for responsible AI implementation in Oregon.
Contact: ameeta@pdx.edu
Bart Massey, Associate Professor, Computer Science
Bart Massey's research places an emphasis on open source technology development and software engineering. With a Ph.D. in artificial intelligence, Massey explores classic AI pre-machine learning, AI in gaming and open source software. He is also an expert in State Space Search, which is used in applications including route planning, airline scheduling and playing games against a computer. He is a member of the Association for Computing Machinery, a long-time open source developer with software industry experience, and regularly implements AI ideas as code to see how they work in practice.
Contact: masseyb@pdx.edu
Sambit Tripathi, Assistant Professor, Business Technology Analytics
Sambit Tripathi's research aims to tackle business problems related to the use of data analytics. With the rapid growth of digital platforms, the volume and complexity of big data will tremendously increase. Tripathi applies ML/AI methods to data to generate value for organizations. For example, they use text mining methods to uncover user behavior on the platform. Also, not every business stakeholder is well acquainted with complex AI methods. For example, customers may not understand how Amazon or Netflix recommend products and movies to them. Tripathi's research aims to develop interpretable data analytics methods that can help organizations and their customers trust and use AI methods effectively.
Contact: sambit@pdx.edu