About

Axel Krieger is an associate professor in the Department of Mechanical Engineering at Johns Hopkins University, with a secondary appointment in computer science. He is also a Carol Croft Linde Faculty Scholar and the director of the Intelligent Medical Robotic Systems and Equipment (IMERSE) Lab. His research focuses on the development of surgical robotic systems, robotic tools, and laparoscopic devices, including autonomous robotic surgery systems, 3D printed patient-specific implants, and magnetically controlled microsurgery. Krieger investigates methodologies that enhance the smartness and autonomy of medical robots, improve image guidance, and perform tasks previously impossible, aiming to improve efficiency and patient outcomes. His team gained international recognition in 2022 when their Smart Tissue Autonomous Robot (STAR) performed laparoscopic surgery on pig soft tissue without human guidance, marking a significant step toward fully automated surgery on humans. His projects also include the use of 3D printing for surgical planning, autonomous soft tissue surgery, image-guided interventions, autonomous trauma diagnosis, and cardiac planning. Krieger holds over 30 patents and patent applications, with licensees including medical device startups and industry leaders such as Siemens, Philips, and Intuitive Surgical. Before joining Johns Hopkins in 2020, he was an assistant professor at the University of Maryland and a research professor at Children’s National Hospital, where he led projects at the Sheikh Zayed Institute for Pediatric Surgical Innovation. He has also worked as a product leader at Sentinelle Medical Inc. and Hologic Inc., developing devices and software systems from concept to FDA approval and market. Krieger completed his undergraduate and master's degrees at the University of Karlsruhe in Germany and earned his doctorate at Johns Hopkins, where he pioneered an MRI-guided prostate biopsy robot used in over 50 patient procedures across three hospitals. His research has been recognized with awards such as the National Science Foundation’s Early CAREER Award in 2022 and the Best Innovation award at the 2021 Hamlyn Symposium.

Research topics

• Medicine
• Computer Science
• Artificial Intelligence
• Political Science
• Surgery
• Medical emergency
• Virology
• General surgery
• Risk analysis (engineering)

Selected publications

• Autonomous robotic laparoscopic surgery for intestinal anastomosis

  Science Robotics · 2022 · 339 citations

  Senior authorCorresponding
  • General surgery
  • Medicine
  • Surgery

  Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency independent of individual surgeon's skill and experience. Autonomous anastomosis is a challenging soft-tissue surgery task because it requires intricate imaging, tissue tracking, and surgical planning techniques, as well as a precise execution via highly adaptable control strategies often in unstructured and deformable environments. In the laparoscopic setting, such surgeries are even more challenging because of the need for high maneuverability and repeatability under motion and vision constraints. Here we describe an enhanced autonomous strategy for laparoscopic soft tissue surgery and demonstrate robotic laparoscopic small bowel anastomosis in phantom and in vivo intestinal tissues. This enhanced autonomous strategy allows the operator to select among autonomously generated surgical plans and the robot executes a wide range of tasks independently. We then use our enhanced autonomous strategy to perform in vivo autonomous robotic laparoscopic surgery for intestinal anastomosis on porcine models over a 1-week survival period. We compared the anastomosis quality criteria-including needle placement corrections, suture spacing, suture bite size, completion time, lumen patency, and leak pressure-of the developed autonomous system, manual laparoscopic surgery, and robot-assisted surgery (RAS). Data from a phantom model indicate that our system outperforms expert surgeons' manual technique and RAS technique in terms of consistency and accuracy. This was also replicated in the in vivo model. These results demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.

  DOI

• Medical Robots for Infectious Diseases: Lessons and Challenges from the COVID-19 Pandemic

  IEEE Robotics & Automation Magazine · 2021 · 76 citations

  • Computer Science
  • Risk analysis (engineering)
  • Artificial Intelligence

  Medical robots can play an important role in mitigating the spread of infectious diseases and delivering quality care to patients during the COVID-19 pandemic. Methods and procedures involving medical robots in the continuum of care, ranging from disease prevention, screening, diagnosis, treatment, and home care, have been extensively deployed and also present incredible opportunities for future development. This article provides an overview of the current state of the art, highlighting the enabling technologies and unmet needs for prospective technological advances within the next five to 10 years. We also identify key research and knowledge barriers that need to be addressed in developing effective and flexible solutions to ensure preparedness for rapid and scalable deployment to combat infectious diseases.

  DOI

Recent grants

• OpenIGTLink: a network communication interface for closed-loop image-guided interventions

  NIH · $4.1M · 2015–2026

• Patient Specific Tissue Engineered Vascular Graft Creation Using 3D Printing Technology

  NIH · $1.2M · 2017–2022

• Patient specific 3D printed tissue engineered vascular graft for aortic reconstruction designed by artificial intelligence algorithm.

  NIH · $2.7M · 2018–2023

• Next Generation of Surgical Imaging and Robotics for Supervised Autonomous Soft Tissue Surgery

  NIH · $1.5M · 2016–2020

• CAREER: Advancing Autonomy for Soft Tissue Robotic Surgery and Interventions

  NSF · $616k · 2022–2027

Frequent coauthors

• Justin D. Opfermann

  Johns Hopkins University

  79 shared

• Gábor Fichtinger

  Queen's University

  70 shared

• Louis L. Whitcomb

  Johns Hopkins University

  61 shared

• Ergin Atalar

  Bilkent University

  59 shared

• Robert C. Susil

  Johns Hopkins Hospital

  55 shared

• Peter L. Choyke

  50 shared

• Laura Olivieri

  49 shared

• Kevin Camphausen

  National Cancer Institute

  48 shared

Labs

• IMERSEPI

Awards & honors

• National Science Foundation’s Early CAREER Award (2022)
• Best Innovation award in the Medical Robotics for Contagious…
• Carol Croft Linde Faculty Scholar

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• Steven L. Salzbergh-191
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• Alan Yuilleh-134