The Rutgers Center for Biomedical Informatics & Health Artificial Intelligence (BMIHAI) is proud to announce the recipients of funding for multidisciplinary projects to support Postdoctoral Health AI Research (PAIR) Fellows. Four research teams have been selected to receive support for innovative projects and provide leading-edge interdisciplinary mentorship in Biomedical Informatics and Health AI for postdoctoral researchers.

The postdoctoral fellowship program was established to provide support for new interdisciplinary projects and teams through funding for postdoctoral fellows who will be mentored by experts in health AI-related fields.

Awardees will receive funding to support postdoctoral fellows for one year.

“Investing in the next generation of biomedical informatics researchers is essential to advancing health innovation,” said Leslie Lenert, the director of BMIHAI and a professor in the Department of Medicine at Robert Wood Johnson Medical School (RWJMS). “These awards are intended to empower researchers to mentor emerging scholars who will shape the future of biomedical informatics and health AI.”

“Through the Postdoctoral Health AI Research (PAIR) Fellowships, we’re not only strengthening research capacity but also cultivating a collaborative environment where fresh perspectives and cutting-edge methodologies can thrive,” said Antonina Mitrofanova, the deputy director of the center and an associate professor with the Rutgers School of Health Professions.

The research teams receiving PAIR Fellow funding are:

“Project AiCCESS (Artificial Intelligence for Comprehensive Care, Equity, and Sustainability in Surgery)”

The researchers said, “Project AiCCESS is redefining surgical care by harnessing multimodal AI to predict, detect, and manage surgical site infections.”

Lead Mentor:

• Mayur Narayan, the chief of the Division of Acute Care Surgery, a professor of surgery, the trauma medical director and the program director of the Acute Care Surgery Fellowship at RWJMS

Co-Mentors:

• Divya Kewalramani, an assistant professor in the Division of Acute Care Surgery at RWJMS
• Les Barta, the director of the Simulation Technology Program at Ernest Mario School of Pharmacy and the co-chair of the Rutgers Health Simulation Workgroup
• Rachel Choron, an associate professor of surgery, the medical director of the Shock Trauma ICU and the program director of the Surgical Critical Care Fellowship at RWJMS
• Dimitris Metaxas, a distinguished professor in the Department of Computer Science at Rutgers School of Arts and Sciences

“Combined motor and brain function analysis using AI for screening cognitive impairment”

When asked about goals from this project, the research team said, “The proposed approach uses a novel dual-task test to accentuate subtle brain function alterations due to Alzheimer’s disease that are measured using fNIRS, providing the opportunity to reduce the cost and duration of cognitive screening.”

Lead Mentor:

• Nima Toosizadeh, an associate professor in the Department of Rehabilitation and Movement Sciences at Rutgers School of Health Professions

Co-Mentors:

• Michal Schnaider Beeri, the director of the Herbert and Jacqueline Krieger Klein Alzheimer’s Research Center at Rutgers and a professor of neurology at RWJMS
• Laleh Najafizadeh, a professor of electrical and computer engineering at Rutgers School of Engineering

“Advancing ICU Care with Real-Time, AI/ML-Driven, Patient-Specific Digital Twins (AID-TWIN)”

The research team said they are aiming to create “a modular, AI/ML ICU digital twin framework to accelerate proactive, individualized care and build workforce capacity through immersive, cross-disciplinary training.”

Lead Mentor:

• Jag Sunderram, a professor of medicine, the division chief of Pulmonary and Critical Care Medicine, the medical director of Respiratory Care Service and service chief of Pulmonary Services at RWJMS

Co-Mentors:

• Ioannis Androulakis, a professor in the Biomedical Engineering Department and Chemical and Biochemical Engineering Department at Rutgers University, the vice-chair and Undergraduate Program director, and an adjunct in the Department of Surgery at RJWMS
• Julie Goswami, an assistant professor of surgery in the Division of Acute Care Surgery at RWJMS and the associate director of the Rutgers Acute Care Surgery Research Lab
• Sabiha Hussain, a professor of medicine, the director of the Pulmonary and Critical Care Medicine Fellowship, the director of the Adult Cystic Fibrosis Program, the director of the Long-COVID program and the director of YourHealthKiosk at RWJMS
• Aesha Jobanputra, an associate professor of medicine in the Division of Pulmonary and Critical Care Medicine at RWJMS
• Shantenu Jha, a professor of computer engineering at Rutgers, the co-director of Cyberinfrastructure and AI for Science and Society, and the chair of the Center for Data Driven Discovery at Brookhaven National Laboratory
• Kaushik Kumar, a fellow in the Division of Pulmonary and Critical Care Medicine at RWJMS
• Thomas Nahass, a clinical assistant professor in the Division of Pulmonary and Critical Care Medicine at RWJMS and the regional vice president of health informatics at RWJBarnabas Health

“Transfer Learning for Brain-Based Prediction in Psychotic Illness”

The team provided the following statement when asked about what their project will provide: “We will develop transfer-learning models leveraging large datasets to improve brain-based predictions of symptoms and treatment response in bipolar depression and schizophrenia across clinical cohorts.”

Lead Mentor:

• Avram Holmes, an associate professor of psychiatry at RWJMS

Co-Mentor:

• Waheed Bajwa, a professor of electrical and computer engineering at Rutgers School of Engineering

BMIHAI, based within IFH, serves as a catalyst for transformative research by harnessing the power of AI to transform the way research is conducted and by uniting health-related educational, training and research efforts involving data science under one umbrella.

For more information about BMIHAI, visit https://ifh.rutgers.edu/center-for-biomedical-informatics-and-health-artificial-intelligence/