About Me

I am a PhD Candidate in the Brain Tool Lab under the mentorship of Patrick Codd and Boyuan Chen, where I develop cutting-edge technologies aimed at advancing automated surgery. My research encompasses Robotic Perception, Surgical Robotics Platforms, and Machine Learning. I hold an MS in Mechanical Engineering from Duke University, where I worked with Xiaoyue Ni on flexible epidermal sensors for physiological sensing.

My passion lies in creating transformative healthcare interventions by enhancing the capabilities of autonomous systems through innovative sensors and algorithms. I aim to empower healthcare professionals with advanced surgical robotic systems and sensors, improving clinical outcomes and accessibility. My work is committed to addressing the challenges faced by under-resourced communities, striving for a more equitable healthcare future.

News

2024

• December: Our workshop “The Evolving Landscape of Surgical Robotics: Towards AI-Powered Unconventional Instruments and Technologies in the Operating Theatre” got accepted for “ICRA 2025”. Excited for the speaker lineup. Additional details coming soon!
• December: Won Rhodes Graduate Fellowship for Interdisciplinary Research in recognition of my contributions towards the Bass Connections project Reimagining Surgery for Rural Needs: Robotics Teleoperation. This fellowship will allow me to understand surgical needs in rural North Carloina clinics and develop a suitable surgical platform.
• September: Our paper “Extracting Critical Information from Unstructured Clinicians’ Notes Data to Identify Dementia Severity Using a Rule-Based Approach: Feasibility Study” was published in JMIR Aging. It highlights the potential of unstructured EHR data in assessing ADRD severity while reducing clinician workload.
• September: Our work “Sampling-Based Model Predictive Control for Volumetric Ablation in Robotic Laser Surgery”, is now available online. We propose a surgical planning algorithm for volumetric tumor resection.
• September: Our work “Design and Evaluation of a Compliant Quasi Direct Drive End-effector for Safe Robotic Ultrasound Imaging”, is now available online. We demonstrate a compliant and patient-focused end-effector for autonomous ultrasound imaging.
• February: Congratulations to Zach Chen & Alexa Cahilig for winning the Duke CoLab research award for developing a low-cost test bench for tissue transition boundary evaluation.
• February: Awarded the Bass Connection Student Research Award by Duke University to develop affordable multimodal sensors for laser-tissue interaction studies.
• February: Delivered a talk at IIT Patna on “Innovating Surgical Robotics: Enhancing Precision and Automation in Minimally Invasive Procedures”.
• January: Our work “A Blinded Study Using Laser-Induced Endogenous Fluorescence Spectroscopy to Differentiate Ex Vivo Spine Tumor, Healthy Muscle, and Healthy Bone” has been published in Scientific Reports.

2023

• June: Our work “3D Laser-and-Tissue Agnostic Data-driven Method for Robotic Laser Surgical Planning” has been accepted at IROS 2023.
• March: Received the Maclin Community Connections Grant for supporting underrepresented undergraduate students.
• March: Awarded Duke India Initiative’s Research Travel Grant for testing portable diagnostic devices in under-resourced facilities in India.
• February: Presented “Developing Brain Tissue Mimicking Phantoms for Photoablation Studies” at ISMR 2023 with support from the Duke Graduate School’s Conference Travel Award.
• December: Received a DEI micro-award for mentorship efforts from Duke Graduate and Professional Student Government.

2021

• May: Honored with the Woo Center for Big Data and Precision Health Fellowship to work on unstructured EHR reports with Dr. Hanzhang Xu.

2020

• October: Received the Dean’s Research Award for my work on flexible sensors.

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