Connecting researchers with the power of AI


Published July 24, 2023

Jinjun Xiong.

Jinjun Xiong’s years of experience with artificial intelligence (AI) are making a dramatic impact at UB.

SUNY Empire Innovation Professor of Computer Science and Engineering, Xiong is scientific director and co-director of the AI Institute for Exceptional Education, a national institute developing artificial intelligence systems that identify and assist young children with speech and/or language processing challenges. It was established earlier this year with a five-year, $20 million grant from the National Science Foundation.

Xiong also serves as co-director of UB’s Institute for Artificial Intelligence and Data Science (IAD), where he connects investigators — including clinical and translational researchers — with the power of AI.

These efforts include:

  • Weekly open office hours: UB researchers can sign up to chat with Xiong about their research challenges, and he will connect them with UB AI and data science experts and help translate the domain problems in a language that can be easily understood by computer scientists.
  • Monthly proposal brainstorming sessions: An extension of the open office hour sessions, these more focused discussions bring in relevant experts to brainstorm possible AI-driven solutions and develop proposals and teams as a follow-up action.
  • Quarterly request-for-information proposals: Investigators are invited to describe a research challenge that arises from their domain and explain how AI, big data and computational science can be a potential gamechanger in addressing that challenge.

“I am also always looking for new ideas for how we can make the IAD platform more useful and accessible for all UB investigators,” Xiong says.

He believes it is important for researchers and the public to understand artificial intelligence, and the ways in which it is changing our world. In a Q&A with UBNow, Xiong discusses the impact of AI on research now and in the future, and analyzes how it will affect health care.

How is AI impacting clinical and translational research now, and how will it be in the future?

AI is already impacting clinical research in multiple ways, such as medical imagining analyses for skin cancer detection, MRI imaging segmentation, clinical trials data understanding, wearable sensors to improve patient monitoring — the list just goes on and on. The future of clinical practices will incorporate more and more intelligent solutions enabled by more efficient and intelligent algorithms, all aiming to improve the patient quality of care. One such example is the growing capabilities of AI, especially the recent amazing results from generative AI like ChatGPT, where it is conceivable that AI-augmented agents — such as chatbots — can help with providing more accessible and higher-quality health literacy for patients.

What do investigators need to know to incorporate AI into their work?

To some degree, every future professional needs to understand a bit about AI and computing, by either talking to AI experts/researchers or learning online to gain a general understanding of how AI works, and what AI can do and cannot do right now and even in the near future. With that basic understanding, people working in a particular domain — like medicine — can revisit their daily practices and think out of the box about where AI can help in their current practice flows, and then engage with an AI expert to co-imagine and then co-design a possible AI-driven solution.

What should the public know about how AI will impact their health care?

The public should realize that the impact of AI to health care is real and inevitable. There is always an ethical and moral issue around AI in health care, as it may potentially remove autonomy from humans. But that is exactly why the public should be aware of the technology — so they can be part of the conversation to find meaningful solutions. I believe the voices of the public should be heard in charting a new direction for humankind with AI.

The power of AI can only become real when it is applied to solve a particular domain problem.

For more information on IAD research initiatives, write to Xiong at jinjun@buffalo.edu.