Adnan Munawar
Assistant Research Scientist, Johns Hopkins University
Professional Summary
I am an Assistant Research Scientist at Johns Hopkins University. I develop advanced computational and simulation technologies to enhance surgeons’ situational awareness, optimize clinical workflows, and improve patient outcomes. Central to this work is the Asynchronous Multi-Body Framework (AMBF), an open-source, real-time simulation platform I created and lead. AMBF supports high-fidelity physics, haptics, and robot control, and has been integrated with a wide range of imaging modalities (CT, MRI), tool registration methods, tracking systems (optical and electromagnetic), and robotic interfaces—including Galen, UR5, KUKA, da Vinci, Steady Hand Eye Robot (SHER), and Integrated Intraocular Snake (IRIS). In collaboration with clinicians and researchers, I apply this framework across diverse surgical domains—otolaryngology (lateral skull base, endonasal), spinal surgery (laminectomy), ophthalmology (epiretinal membrane peeling, deep vein cannulation), gynecology (hysterectomy), and orthopedics (drilling, implant placement).
Top Skills & Technologies
- Programming: C++, C, Python, ROS
- Simulation & Visualization: Blender, Unity
- Extended Reality: AR & VR
Featured Projects
Achievements & Awards
- Best Innovation Award: “Haptic-Assisted Collaborative Robot Framework for Improved Situational Awareness in Skull-base Surgery”, MRC Symposium, Hong Kong
- Best Paper Finalist: “Twin-S: a digital twin for skull base surgery”, International Journal of Computer Assisted Radiology and Surgery 2023, Munich, Germany
- Outstanding Interaction Paper Award: “Human-Robot Shared Control for Surgical Robot Based on Context-Aware Sim-To-Real Adaptation”, IEEE/RSJ ICRA 2022, PA, USA
- TechXplore Interview: Virtual reality simulator for skull-base procedures
- Best Paper Award Finalist: “AMBF-RL: A real-time simulation-based Reinforcement Learning toolkit for Medical Robotics”, Atlanta, GA, USA
- Outstanding Paper Award: “Virtual Reality for Synergistic Surgical Training and Data Generation”, MICCAI 2021 Workshop, Strasbourg, France
- Best Application Paper Finalist: “A real-time dynamic simulator and an associated front-end representation format for simulating complex robots and environments”, IEEE/RSJ IROS 2019, Macao, China
- Best for Research Community Award: Hamlyn Surgical Robotics Challenge, London, UK (2019)
- Fulbright Graduate Fellowship: M.S. in Robotics, Worcester Polytechnic Institute, MA (2012-2015)
- Best Planning Algorithms and Image Processing Award: National Instruments Mine Detection Robotics Competition, Lebanon (2011)
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