Robotics Seminar: Dr. Farshid Alambeigi, "Surgineering Using Intelligent and Flexible Robotic Systems."

Event Type

Seminar/Symposium

Sponsor

Robotics Seminar Team

Virtual

Join online

Date

Oct 10, 2025   1:00 pm  

Speaker

Farshid Alambeigi

Contact

Allison Mette

E-Mail

agk@illinois.edu

Views

21

Originating Calendar

Siebel School Speakers Calendar

Abstract: Recent advances in surgical robotics have enabled innovative techniques that reduce patient trauma, shorten hospital stays, and improve both diagnostic accuracy and therapeutic outcomes. However, despite the many benefits of robot-assisted minimally invasive and endoscopic procedures, significant limitations remain, particularly in the dexterity, intelligence, and autonomy of current robotic systems, as well as in the biomechanical design of medical devices and implants.

One of the most pressing challenges is inadequate dexterity, driven by limited access to target anatomy and insufficient control over rigid instruments and implants. These constraints highlight the need for specialized instrumentation, intelligent sensing, and adaptive control paradigms capable of navigating complex anatomical environments. Advancing autonomy in surgical systems also requires more than robotic intelligence alone, it demands synergistic human–robot interaction, where the system can both assist and adapt to the surgeon's decision-making process in real time.

This talk will introduce our lab’s efforts in advancing the engineering of surgery (or surgineering) to address these challenges. I will present translational research across several clinical applications, including:

•             Spinal fixation using steerable drills and flexible pedicle screws

•             Colorectal cancer screening with vision-based tactile sensors and complementary AI algorithms

•             In vivo bioprinting for treating volumetric muscle loss via robotic delivery systems

By integrating continuum manipulators, stretchable soft sensors, intelligent implants, and semi/autonomous control strategies, our work aims to fundamentally transform the paradigm of minimally invasive and endoscopic interventions, bringing true dexterity and autonomy to surgical robotics.

Bio: Dr. Farshid Alambeigi is the Leland Barclay Fellowship in Engineering Associate Professor in the Walker Department of Mechanical Engineering at The University of Texas at Austin, where he has served since August 2025. He is also a core faculty member of Texas Robotics. Dr. Alambeigi earned his Ph.D. in Mechanical Engineering (2019) and M.Sc. in Robotics (2017) from Johns Hopkins University. In 2018, he was awarded the 2019 Siebel Scholarship in recognition of his academic excellence and leadership. He is the recipient of the NIH NIBIB Trailblazer Award (2020) for his work on flexible implants and robotic systems for minimally invasive spinal fixation surgery and the NIH Director’s New Innovator Award (2022) for pioneering in vivo bioprinting surgical robotics for the treatment of volumetric muscle loss. His contributions have also been recognized with the UT Austin Faculty Innovation Award, the Outstanding Research Award by an Assistant Professor, the Walker Scholar Award, and several best paper awards and recognitions. He serves as an Associate Editor for the IEEE Transactions on Robotics (TRO), IEEE Robotics and Automation Letters (RAL), and the IEEE Robotics and Automation Magazine (RAM).
At UT Austin, Dr. Alambeigi directs the Advanced Robotic Technologies for Surgery (ARTS) Lab. In collaboration with the UT Dell Medical School, the ARTS Lab advances the concept of Surgineering, engineering the surgery, by developing dexterous, intelligent robotic systems designed to partner with surgeons. The ultimate goal of this work is to enhance surgical precision, improve clinician performance, and advance patient safety and outcomes.

Location: We will meet only virtually. Please use the following zoom meeting information to join us:

https://illinois.zoom.us/j/83068322043?pwd=McN371foR4WvsLrEIafIVDurVN5kgT.1

Meeting ID: 830 6832 2043

Password: 746892