University of Pittsburgh

Pitt HexAI Research Laboratory

AI for Musculoskeletal Care

Making Musculoskeletal Care Smarter, Safer, and More Transparent using AI

Advancing Musculoskeletal Care with Explainable AI

Reimagining Musculoskeletal Care with Transparent and Trustworthy AI

Exploring the Impact of Trustworthy AI in Orthopedics

Examining Bias in AI-Powered Musculoskeletal Care

Sharing Best Practices in Trustworthy AI and Interpretable Models in MSK

Evaluating and Generalizing Interpretable AI Models in MSK

Ahmad P. Tafti, PhD


Ahmad P. Tafti, PhD, FAMIA

Director, Pitt HexAI Research Laboratory

Director, Division of Scientific Affairs, CPACE

Chair, Pitt AI Summer School

Vice Chair, IEEE Computer Society (Pittsburgh)

Fellow, AMIA

Federal Grant Review Panelist (NIH & NSF)

Oracle Eureka Award

SiiM Imaging Informatics Innovator Award

The Pitt Health + Explainable AI (Pitt HexAI) Research Laboratory at the University of Pittsburgh, led by Ahmad P. Tafti, has a simple goal: to make healthcare better through the power of trustworthy and explainable artificial intelligence (AI). From a computational perspective, our research focuses on engineering, implementing, validating, and deploying cutting-edge fundamental and applied explainable AI algorithms, and promoting their applications in healthcare problems. We attempt to answer three main questions: 1) how advanced explainable AI strategies are developing in healthcare, 2) how they shape healthcare systems, and 3) how they impact the healthcare community. From a clinical perspective, our research agenda spans musculoskeletal (MSK) care, with a focus on our aging populations and sports-related injuries and conditions (e.g., ligament injuries, joint degeneration, and total joint arthroplasty) and computational orthopedics.

The Pitt HexAI Research Laboratory is functioning in the Department of Health Information Management at the School of Health and Rehabilitation Sciences. Our group at Pitt HexAI is a multidisciplinary team, and it benefits from several extramural collaborations with other academic institutions, nationwide and worldwide. Moreover, our group aims to provide the highest quality education and research experience in AI-powered health informatics at all levels, from K-12 to undergraduate, graduate, MD, and postdoctoral training.

Research Interests

Technical

Trustworthy and Explainable AI

Responsible and Accountable AI

Medical Imaging Informatics

Clinical

Musculoskeletal (MSK) Care

Computational Orthopedics

Sports-Related MSK Injuries

Supports | Partners | Collaborators

Pittsburgh Cure Sarcoma
Oracle for Research
Computational Pathology & AI Center of Excellence (CPACE)
Clinical and Translational Science Institute

Recent News

News: 2026

  • April 2026: Pitt HexAI Podcast Episode #39 featuring Dr. George Demiris, PhD, FACMI is now available on all major podcast platforms. HexAI Podcast .
  • April 2026: Our team will present three research contributions at the IEEE International Symposium on Biomedical Imaging (ISBI 2026) in London, UK (April 8–11, 2026).
  • March 2026: Dr. Jacob Mathew will serve as a keynote presenter and panelist at the 62nd Annual Medical Conference and International Health Exhibition in Addis Ababa, Ethiopia (March 27–28, 2026). His talk, "Learning to Lead", will be featured in the panel "AI in Academic Medicine: Leveraging Artificial Intelligence to Accelerate Scientific Discovery and Transform Medical Education".
  • March 2026: Pitt HexAI Podcast Episode #38 featuring Martin Raison, MSc is now available on all major podcast platforms. HexAI Podcast .
  • March 2026: Hiring: Research Assistant position available in the HexAI Lab at the University of Pittsburgh for AI-driven medical imaging research. Apply here.
  • March 2026: The AI Summer School – Medical Imaging Informatics will be held at the University of Pittsburgh (June 8–12, 2026). This free one-week program introduces high school students to the exciting world of AI in medical imaging, including Python programming, CNNs and U-Net, and hands-on medical image analysis, with guest lectures from leading researchers in academia and industry. Learn more & register.
  • Feb. 2026: The paper "KneeXNet-2.5D: a clinically-oriented and explainable deep learning framework for MRI-based knee cartilage and meniscus segmentation" by Maimouna S. and colleagues has been published in npj Health Systems .
  • Feb. 2026: The abstract "An Explainable Age- and Sex-Aware Contrastive Artificial Intelligence Framework for Knee Osteoarthritis Classification" by Fengyi Gao and colleagues has been accepted at the IEEE International Symposium on Biomedical Imaging (ISBI 2026) , London, UK.
  • Feb. 2026: The abstract "Prompt-Constrained Vision–Language Models for Zero-Shot Orthopedic Pathology Recognition" by Farnaz Rezvani and colleagues has been accepted at the IEEE International Symposium on Biomedical Imaging (ISBI 2026) , London, UK.
  • Feb. 2026: Pitt HexAI Podcast Episode #37 featuring Ekaterine Kldiashvili, PhD is now available on all major podcast platforms. HexAI Podcast .
  • Jan. 2026: Recent contributions on 2.5D knee MRI segmentation using explainable and uncertainty-aware AI were presented at the Pittsburgh ACL Research Retreat, in collaboration with the Department of Orthopaedics, University of Pittsburgh–UPMC , within the field of sports medicine, including Dr. Tring Cong, Dr. James Irrgang, Dr. Will Pitt, and Dr. Volker Musahl. Pitt HexAI .
News: 2025 and Earlier