Sandeep Bodduluri, Ph.D., is working to use artificial intelligence (AI) to improve health care processes and the patient experience. Through courses offered by the Marnix E. Heersink Institute for Biomedical Innovation, he is sharing his knowledge with clinicians at UAB and abroad, emphasizing the importance of interaction between clinicians and engineers in AI research and development.

Bodduluri is an assistant professor in the Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine, and is the director of AI research for the Center for Lung Analytics and Imaging Research (CLAIR). He also serves as Director of AI Programming for the Marnix E. Heersink Institute for Biomedical Innovation (Innovation Institute) overseeing the AI in Medicine Graduate Certificate, MS AI in Medicine, and MS in Healthcare Innovation programs. He also holds teaching appointments in the Department of Electrical and Computer Engineering in the UAB School of Engineering.

We met with Dr. Bodduluri, who explained his journey to UAB and the research and education initiatives he is involved with now.

Journey to Biomedical Engineering

Bodduluri has been fascinated with computers from childhood, particularly now the ease of automation with AI in the medical field. He highlighted how AI enables quicker and more efficient processes.

“When I was earning my Ph.D., I used to hand code and do programs that had to run for days and just stayed at the computer until it finished,” said Bodduluri. “Now with AI, you can do all of these things very quickly. I just told my student that she could do my thesis, which took me six years in one year with existing open-source AI algorithms and can now look into researching complex topics.”

Bodduluri came from India to the U.S. in 2009 to earn his master's in Biomedical Engineering at the University of Iowa with the goal of merging software development with health care. After earning his master's degree, he worked in a startup focused on lung disease diagnostics, particularly Chronic Obstructive Pulmonary Disease (COPD). Motivated to further his research in the detection of COPD, he returned to the University of Iowa to earn his Ph.D. at Professor Joe Reinhardt’s biomedical imaging group at Iowa and met Surya P. Bhatt, M.D., MSPH, a professor of Medicine and Endowed Professor of Airways Disease in the Division of Pulmonary, Allergy and Critical Care Medicine, who invited him to join his imaging lab as a post-doctoral fellow at UAB in 2016.

At UAB, he has contributed to the growth of the lung imaging lab, now the Center for Lung Analytics and Imaging Research (CLAIR), which is leading the introduction of several new methods for quantitative lung imaging and AI applications. He discussed the importance of early diagnosis of COPD, a lung disease caused by smoking, which often goes unnoticed until significant damage occurs.

“Often by the time you end up at the clinic due to COPD, your lungs are already moderately damaged,” said Bodduluri. “Our goal is that when you come to a hospital for any other type of scan, to have the ability to take the results and use AI to tell you if you have any type of lung damage prior to the onset of advanced lung disease.”

Bodduluri is continuing this research to show how AI can identify early patterns in lung damage and offers the potential of providing timely care and reducing misdiagnosis.

Teaching and Mentoring

In 2023, Rubin Pillay, M.D., Ph.D., executive director of the Innovation Institute, asked Bodduluri to join their team as the director of AI Academic Programs. In this role, he focuses on developing AI academic programs and teaching clinicians to use AI for diagnostics, combining his expertise in software development, AI, and lung disease research.

“I always had students in my lab in collaboration with Dr. Bhatt, who has always supported having some students in there,” said Bodduluri. “I always enjoyed mentoring."

When asked to develop a curriculum for clinicians, he ended up teaching the courses himself, which provided an opportunity to learn from experienced clinicians.

“My engineering perspective initially led me to focus on technical details, but I soon realized the importance of clinician interaction and patient learning,” said Bodduluri.

This realization enriched the courses and made them more practical for clinicians. Bodduluri values the interactive Q&A sessions with clinicians, which provide motivation and new problems to solve as an engineer. He emphasizes the value of interaction with clinicians for problem-solving and motivation.

"We might learn some things which they already doing, which we don't know about, or they also can learn from us,” said Bodduluri. “I think the Innovation Institute brings that aspect to everybody. Clinicians will have access to engineers. Engineers will have access to clinicians, which is rare to happen."

The AI in Medicine Graduate Certificate program has grown significantly, with 58 students enrolled in the Fall 2024 semester. Bodduluri highlighted the success of their partnerships with institutions like Maastricht University in the Netherlands and Thammasat University Hospital and Mahidol University in Thailand, which have led to the launch of a master's program in collaboration with Maastricht. This program aims to enhance the AI and medicine curriculum by enabling global knowledge sharing and mutual learning. He is expanding these collaborations and continuing to innovate in AI and medicine education and plans to share more about this work at the UAB AI and Technology in Global Health Symposium this fall.

Future Goals

Bodduluri now teaches year-round and was recently named a 2025 Pittman Scholar, recognized as a junior faculty member for his exceptional research achievements and potential for future contributions to his field.

He continues to emphasize the importance of clinician-engineer interaction, both in his own research and in his educational approach.

"If you don't interact with the clinician at early stages of any AI,” said Bodduluri, “there is no point of doing any clinical AI research development at all."

In his COPD research, Bodduluri continues to focus on early detection of COPD using AI and CT images, hoping to establish early screening protocols. He plans to develop and deploy algorithms for early COPD detection during routine chest CT scans.

As a teacher, he hopes to have more engineers working on medical applications, combining AI and health care to improve patient outcomes. He finds it rewarding that students have shared that upon completing his courses, they are now comfortable using AI and understand its potential.

“Despite not having any prior background in AI, I was able to learn a lot during the course,” said one student after completing the Foundations of Artificial Intelligence in Medicine course taught by Bodduluri. “By the end of the course, I had gained a solid foundation in AI, which gave me the confidence to continue advancing my knowledge in the field.”