My work explores machine perception in surgical environments at the intersection of computer vision and medical imaging. While perception is a broad problem, many interesting challenges arise from the specific constraints of clinical application domains.

I study these questions in the context of endoscopic sinus surgery, working closely with clinicians to understand nuances that shape these problems and develop systems that meaningfully support surgical practice.

A selection of my work is highlighted below:

Humanoid Robots as First Assistants in Endoscopic Surgery

J.E. Mangulabnan*, S.M. Cho*, H. Zhang*, Z. Mao, Y. He, P. Guo, D. Xu, G. Hager, M. Ishii, M. Unberath

* indicates shared first authorship

CT-Override: Endoscopic Updates to Preoperative Anatomical Models During Ablative Surgery (to appear)

J.E. Mangulabnan, J.M. Delgado-López, L. Seenivasan, R.D. Soberanis-Mukul, S.S. Vedula, R.H. Taylor, M. Ishii, G. Hager, M. Unberath

A Training-Free Approach for 3D Reconstruction from Monocular Sinus Endoscopy

J.E. Mangulabnan, R.D. Soberanis-Mukul, L. Seenivasan, S.S. Vedula, M. Ishii, G. Hager, R.H. Taylor, M. Unberath

An Endoscopic Chisel: Intraoperative Imaging Carves 3D Anatomical Models

J.E. Mangulabnan, R.D. Soberanis-Mukul, T. Teufel, M. Sahu, J.L. Porras, S.S. Vedula, M. Ishii, G. Hager, R.H. Taylor, M. Unberath