About Me

I am a Ph.D. candidate in Mechanical Engineering at Boston University, advised by Prof. Sheila Russo. My research focuses on the design, fabrication, and control of soft robots for medical applications. Previously, I worked as a researcher at the medical device startup inTheSmart Co., Ltd. in South Korea for 3 years, where I contributed to the development of advanced medical imaging systems. I received both a Master's and Bachelor's degree in Mechanical Engineering from Purdue University, where I worked with Prof. Raymond Cipra.

Research Interests

Soft-Rigid Hybrid Robots

Unlike rigid robots, soft robots provide increased dexterity, flexibility, and resilience, making them well-suited for tasks requiring safe and adaptive interactions. However, soft robots face notable tradeoffs, particularly in actuation and sensing capabilities, including low output force, poor controllability, and limited sensing functionality. These challenges become even more pronounced as soft robots are scaled down to sizes smaller than a centimeter, where fabrication complexities further hinder their practicality. My research explores on bridging the gap between soft and rigid robotics, combining the safety and compliance of soft robots with the accuracy and precision in the movements of rigid systems. A key aspect of this work is developing an innovative layer-by-layer fabrication strategy. This method seamlessly integrates actuation, sensing, and control into a unified soft-rigid hybrid robotic system, paving the way for more versatile and functional robots at smaller scales.

Applied Skills : 3D Modeling (Solidworks), Programming (Python, MATLAB), Circuit Design (Altium), Fabrication (laser microprocessing, layer-by-layer fabrication, plasma etching)

Laser-assisted Surgery Robots

Lasers have become an essential tool in many surgical applications due to their ability to selectively ablate tissue based on light absorption which varies with laser wavelength. This selectivity can minimize damage to healthy tissue, shorten recovery time, and reduce the risk of postoperative complications. To further enhance laser surgery techniques, robotic technology can improve the precision of laser targeting by enabling automatic closed-loop control. Among the robotic technologies applicable to these medical procedures, soft robotics stands out for its inherent compliance, flexibility, and robustness, making it ideal for delicate surgical environments. However, while soft robots excel in adaptability, they often face limitations in controllability and precision. My research focuses on developing a laser-steering robot built upon a soft-rigid hybrid concept to address this. By merging the safety and adaptability of soft robotic technology with the structural stability and programmable precision of rigid components, this approach can enhance control, accuracy, and precision in laser-assisted surgeries.

Applied Skills : 3D Modeling (Solidworks), Programming (Python, MATLAB, ROS2), Machine Learning (PyTorch), Fabrication (laser microprocessing, layer-by-layer fabrication, plasma etching)

Surgical Vision

Imaging systems serve as the eyes of surgeons during minimally invasive surgeries, providing real-time visuals to guide precise interventions. However, these systems often fall short in delivering comprehensive information, leaving surgeons with critical unknowns. To address these limitations, my previous research focused on augmenting the information available during surgeries by leveraging NIR lasers and NIR imaging systems to provide insights beyond conventional imaging . A key outcome of this work was the development of two advanced imaging systems: a laser speckle contrast imaging system and a fluorescent laparoscopy system . The laser speckle contrast imaging system is a dye-free, real-time blood flow imager that uses laser speckles to visualize tissue perfusion and vascular structures. The fluorescent laparoscopy system combines white light and near-infrared (NIR) imaging cameras to highlight lymph nodes, vessels, and other critical anatomical features. Together, these systems aim to provide surgeons with context-rich visualization—acting as a form of visual guidance akin to the overlays in backup cameras for cars, allowing for greater precision and confidence during minimally invasive surgeries.

Applied Skills : 3D Modeling (Solidworks), Programming (Python, OpenCV), Machine Learning (PyTorch - YOLO v5), Fabrication (3D printing)

3D Printed Prostethic Hand

Body-powered prosthetic hands often have limited degrees of freedom and are typically constructed from rigid materials, making everyday object-grasping tasks challenging. Additionally, users often need to maintain awkward body positions to sustain a grasp. To address these limitations, my research focused on developing rigid-flexible fingers that provide the necessary compliance for grasping various objects and designing an innovative locking mechanism to secure finger positions without requiring uncomfortable postures. Furthermore, the project aimed to create an affordable prosthetic hand by leveraging cost-effective 3D printing technology.

Applied Skills : 3D Modeling (Solidworks), Programming (MATLAB), Fabrication (3D printing, Molding)

Selected Publications

A fabrication strategy for millimeter-scale, self-sensing soft-rigid hybrid robots

Hun Chan Lee, Nash Elder, Matthew Leal, Sarah Stantial, Elenis Vergara Martinez, Sneha Jos, Hyunje Cho, Sheila Russo

Nature Communications, 2024 | [Paper] | [Cover Art] | [Behind the Paper]

Capacitive Origami Sensing Modules for Measuring Force in a Neurosurgical, Soft Robotic Retractor

Daniel Van Lewen, Catherine Wang, Hun Chan Lee, Anand Devaiah, Urvashi Upadhyay, Sheila Russo

ICRA, 2024 | [Paper]

When the End Effector Is a Laser: A Review of Robotics in Laser Surgery

Hun Chan Lee, Nicholas Pacheco, Loris Fichera, Sheila Russo

Advanced Intelligent Systems, 2022 | [Paper]

A coaxial excitation, dual-red-green-blue/near-infrared paired imaging system toward computer-aided detection of parathyroid glands in situ and ex vivo

Yoseph Kim*, Hun Chan Lee*, Jongchan Kim*, Eugene Oh, Jennifer Yoo, Bo Ning, Seung Yup Lee, Khalid Mohamed Ali, Ralph Tufano, Jonathon Russell, Jaepyeong Cha (*equally contributed)

Journal of Biophotonics, 2022 | [Paper]

A pilot feasibility study to assess vascularity and perfusion of parathyroid glands using a portable hand‐held imager

Eugene Oh, Hun Chan Lee, Yoseph Kim, Bo Ning, Seung Yup Lee, Jaepyeong Cha, Wan Wook Kim

Lasers in Surgery and Medicine, 2021 | [Paper]

Design of a Novel Locking Ratcheting Mechanism for a Body-Powered Underactuated Hand

Hun Chan Lee, Raymond Cipra

Journal of Medical Devices, 2020 | [Paper]

Honors and Awards

• Distinguished Mechanical Engineering Fellowship (2021)

• Dean’s List & Semester Honor (2012-2016)

• EPICS AMD Design Award (2014)

• School of Mechanical Engineering Scholarship (2013)