
We recently spoke with François Modave, Ph.D., about his professional and personal pursuits. He is a professor of artificial intelligence (AI), associate chair of research for the University of Florida Department of Anesthesiology, and assistant dean of the Quality and Patient Safety Initiative (QPSi) Academy in the UF College of Medicine.
Q: Why did you choose computer science and artificial intelligence (AI) as your areas of professional focus?
A: Actually, my area was really mathematics; that was my area of focus when I was an undergrad. I really enjoyed working on the theoretical questions, and the curriculum design in France is a little bit less crisp than it is in the United States so I was able to take a bunch of classes that were in mathematics and theoretical computer science. Then when I started looking at AI classes, it was really doing a bunch of computer science, AI, and math questions. It was a fun way for me to mate the many aspects of mathematics and computer science that I was interested in, so I kind of fell into it a little bit by accident.
Q: Why did you then decide to join the UF Department of Anesthesiology?
A: I was always really interested in using the skill set that I have towards practical applications to clinical questions. Even when you’re addressing research questions, it takes a lot of time to have research actually lead to meaningful changes in clinical practice. For me, one of the interesting aspects of joining the Department of Anesthesiology was the ability to do work that impacts patients more directly than in a pure research department.
Additionally, I started collaborating with Patrick Tighe [professor of anesthesiology and executive director of the QPSi] and Chris Giordano [professor of anesthesiology] a couple of years before on building an AI curriculum for clinicians, and so that transition happened a little bit organically. A couple of years ago in the middle of COVID, Patrick reached out to me and said, “Hey, do you want to teach AI to my colleagues?” I thought, “Oh, that’s a cool idea,” and so I said, “Yes, sure,”, so we started doing online but synchronous lectures. What I never factored in was that those lectures needed to be before anesthesiologists were in the OR, around 6:00 a.m. This was about the same time that my daughter was born, so it made a couple of mornings a little bit complicated at home. I can laugh about it now, but at first I kind of thought, “Oh, oops—maybe not that great an idea.” That’s one of the fun memories of my foray into the Department of Anesthesiology.

Q: As the associate chair for research in the department and assistant dean of the QPSi Academy, you are involved in many aspects of research. What are some of the most compelling areas of research in the department? In what directions do you anticipate research developing?
A: I think all areas are really interesting, and there are really important questions because it’s such a broad field. I’ve been involved in a variety of projects that tend to be centered around using AI, using biomedical informatics for anesthesiology questions; for instance, patient blood management is a really interesting question. One project that is actually really important for the department is joining MPOG, the Multicenter Perioperative Outcomes Group, based out of the University of Michigan. Joining this group is going to be a big step for us to grow research across the entire department. We will be better equipped to address our research questions when we have quality data that is curated, harmonized, and centralized. It will be a good a good platform for us to have quality data that can be used by all our clinicians to move general knowledge in anesthesiology from a research standpoint.
Q: As an educator, you have helped develop courses in AI for the clinical community at UF. What is something that surprises students to learn? What advice would you give students to help them best maximize their learning experiences?
A: There are a lot of tools we currently have in our arsenal to do AI that do not require any programming, and so some of the learners who got involved in AI medicine have noticed that more and more we can do a lot of work without being a programmer or computer scientist. I’m hoping that we’ll see more and more people willing to give it a shot and realize, “Hey, I can build my own models. There is a lot of work that needs to be done in terms of cleaning the data, etc., but I don’t need to be an expert in programming or anything like that to do AI in medicine.”
"…one of the interesting aspects of joining the Department of Anesthesiology was the ability to do work that impacts patients more directly than in a pure research department."

Q: One of the most common conversations related to artificial intelligence involves the role of human versus machine decision-making. From your perspective, how do you see this dynamic playing out in the near and longer future?
A: I think there is a lot of fear around it, but it’s kind of interesting: I’m trained in the old school AI and there was fear around AI already in the 80s, 90s, 2000s, and it’s 2024 and we have new models and large language models and plenty of things like that, and we still have the same fear that there’s going to be some kind of all-purpose AI that surpasses humans. I’m not really worried about this.
What I know is that the purpose of AI in medicine is not to replace humans but to allow humans to be able to take into consideration larger datasets so that they can provide better care. In other words, the ideal kind of AI-enhanced physician, if you will allow me the term, would be a physician who has a couple of AI tools that they can use to look at all the data and evidence to make the best possible decision for a specific patient so that they can focus on the things that are inherently human rather than the things that can be automated like analyzing extremely large datasets and comparing how your patient does with other patients and things like that. I think AI is just one more tool that’s going to be available to providers and that’s going to help us deliver better care.
Q: How do you structure your time to enable all of your clinical, educational, scholarly, and other pursuits?
A: “Painfully” is the short answer [laughs]. You know, I have two young kids; young kids take a lot of time. Besides being a husband and a dad, I enjoy doing triathlons. So, I try to do a workout in the early morning and then later in the day I am available when the kids need me around to eat, to get ready for bed, etc. I make full use of the day from the moment I get up all the way to going to bed. Thankfully, I have a little bit more flexibility compared to clinicians who are going to be in the OR, so I can spread my activities across the entire 16 or 17 hours of being awake, which provides a little bit more flexibility.
Q: What aspects of competing in triathlons are most compelling to you?
A: It’s the challenge. It’s not unlike research: it’s about persevering. There is a pretty common saying when people race long distance events which goes along the lines of, “When you suddenly feel really good, don’t pick up the pace because it’s not going to last, and when you feel really bad, don’t give up because it’s not going to last either.” It’s just about persevering and toughing it out when it gets tough and being reasonable when it gets easy, so it’s not unlike research. Oftentimes you’ll get a grant funded and that’s kind of cool; it doesn’t mean that you are exceptional or anything, it just means somebody is interested in your question, so you’re continuing, you’re persevering, you’re trying to extend the body of knowledge. Sometimes your grant doesn’t get funded, so you go back to the drawing board, and you continue moving forward.
Usually once a year I try to do one race with my wife, and so we run together. Usually it’s a half marathon, so it’s not super long: a little bit under two hours, usually around an hour and 45 minutes. It’s probably one of the most fun races that I do as I get to spend time with her, encourage her, etc. That’s something I’ve really enjoyed.
The other thing, for full disclosure, is I really, really like to eat and I have a really big sweet tooth, so endurance sports are a good way to enable me to indulge.
Q: Any parting thoughts before we let you get back to work?
I would really like my clinical colleagues to absolutely email me, call me, and come and see me if you have research questions: I’m here to help. My role as associate chair of research is to help the department, not to build my own research. We’ve had some good interactions during my office hours, and I would really like for more clinical faculty to come see me with their questions about research and how I and the Office of Research can help. My door is open and I’m always willing to help the research move forward.