Benjamin D. Killeen
Ph.D. Benjamin Killeen
Informatics 16 - Chair of Computer Aided Medical Procedures (Prof. Navab)
Postal address
Boltzmannstr. 3
85748 Garching b. München
- Phone: -
- Homepage
- E-mail: bd.killeen@tum.de
I am a postdoc working on surgical data science within the chair for Computer Aided Medical Procedures.
Summary
As a postdoctoral researcher in the CAMP Chair at the Technical University of Munich, I research the future of AI- and robot-assisted healthcare, leveraging enormous data generated by health systems together with sophisticated simulation environments to improve patient outcomes. Every day, I aim to build community in the classroom, in my network, and through professional societies to foster an inclusive environment.
Please find more information on my personal webpage or full CV.
If you are a student interested in working with me, please email me with a brief message, your CV, and a recent transcript if applicable.
Research Interests
- Surgical Data Science
- Computer assisted surgery
- Artificial intelligence in healthcare
- Simulation
Curriculum Vitae
- 09/2015 - 06/2019: Bachelor in Computer Science with Honors at the University of Chicago
- 08/2019 - 08/2022: Master in Computer Science at Johns Hopkins University
- 08/2019 - 03/2025: Ph.D. in Computer Science with the ARCADE Lab at Johns Hopkins University
- 09/2025 - Present: Postdoc in the Chair for Computer Aided Medical Procedures (CAMP) at the Technical University of Munich
- 01/2026 - Present: AI Consultant at Semaphor Surgical
Awards
Personal Awards:
Siebel Scholar (2024)
Finalist, WSE Excellence in Teaching, Advising, and Mentoring Award (2024)
DAAD AI-Net Fellow, Postdoc-NeT-AI Networking Week on Human-centered AI (2023)
Recipient, Link Foundation Fellowship in Modeling, Simulation, and Training (2023)
LCSR Fellowship for Outstanding Incoming Ph.D. Students (2019)
Publication Awards:
Best Paper Award, IPCAI 2025 (2025)
Bench-to-Bedside Award, IPCAI 2024 (2024)
Finalist, Best Paper Award, IPCAI 2024 (2024)
Honorable Mention, Bench-to-Bedside Award, IPCAI 2023 (2023)
Runner Up, Best Paper Award, Physics of Medical Imaging (2022)
Best Paper Award in Bioengineering, IEEE BIBE (2021)
Kaggle COVID-19 Dataset Award (2020)
Reviewer Awards:
IEEE TMI Distinguished Reviewer, Bronze Level (2024)
IPCAI Outstanding Reviewer Award (2024)
Honorable Mention, MICCAI Outstanding Reviewer Award (2023)