The application of machine learning and precision robotics in medicine is rapidly changing the landscape of technologies available to the surgeon in the operating room. This rise in advanced surgical technologies has created an environment that demands collaboration between engineering researchers and medical practitioners; it also requires a convergent approach to integrate the legal, ethical, societal, and economic considerations into future developments of beneficial surgical technologies. Current models of graduate education and training do not provide the necessary framework for students to excel at this interface of medicine and engineering. Although engineering students receive thorough background training in technical and problem-solving skill-sets, relevant to development of technologies that could be applicable to the operating room, very few have access to the guidance or opportunity to discuss the medical needs and applications with medical practitioners, patients, or to visit an operating room to better understand surgical barriers, challenges, or constraints of the technologies they design. To address these limitations in graduate education at the intersection of engineering and medicine, we need to train engineers to understand and have direct experience with the emerging socio-technological-medical application landscape as well as the risks and benefits of new technologies. Training at this level of convergence requires increased interactions between students, the providers who will test these technologies, and the end-users (i.e., practitioners and patients) for whom these technologies are developed to better understand the impact of these technologies on patients’ well-being. At Duke University, the engineering and medical schools are separated by a single road - Research Drive. The vision for this certificate is to provide a new training framework for engineering and computer science graduate students, to “cross the road,” both literally and figuratively, into the other disciplines to design advanced surgical technologies that considers provider, societal, end-user, and patient needs in their development and testing. This transdisciplinary training will provide a pathway for engineering and Computer Science graduate students to design innovations in fundamentally new technologies to advance surgical practice, an engineering training pathway which otherwise does not formally exist at Duke. Furthermore, by partnering engineering students with medical students to gain perspectives into each other’s fields as well the challenges, benefits and tradeoffs between design potentials and real-world medical needs, innovation in surgical technology can be achieved with greater patient and societal benefits. MEMS will serve as the host departments, but primary faculty and interested students also come from ECE and CEE.
Eligible Students All MS, MEng, and Ph.D. can apply for the Surgical Technology Development Certificate including students from the following disciplines:

 • Mechanical Engineering and Materials Science
 • Electrical and Computer Science
 • Civil and Environmental Engineering
 • Computer Sciences
 • Statistics
 • Science & Society
 • Math
 • Data Science
 
Admissions: Students may be admitted before or after completing the academic requirements.

Medical Robotics and Surgical Technologies Certificate Requirements:

This certificate will be concurrent with the student’s degree program and thus will be awarded upon degree completion.

4 courses (3 credits each) = 12 credits required for certificate completion.

The following two courses are required:

ME 555 Introduction to Medical Robotics and Surgical Technologies in Fall term only ME 555 Medical Robotics and Surgical Technologies Team Project in Spring term only


One course in Machine Learning and one Elective Course listed below. 
Students admitted to a graduate certificate program are subject to the general policies and procedures of the Mechanical Engineering & Materials Science Department. Your signature below indicates your understanding and acceptance of this. Please note that if you must complete your PhD or Masters in order to be awarded this certificate. 
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Mandatory Classes: 

ME 555 Introduction to Medical Robotics and Surgical Technology (taught in the Fall)
ME 555 Project in Medical Robotics and Surgical Technology (taught in the Spring)
1 Machine Learning class from the list below:

• COMPSCI 590-07 Applied Natural Language Processing
• COMPSCI 571D/ECE 682D/STA561 D Probabilistic Machine Learning
• ECE 590-03 Machine Learning in Adversarial Settings
• ECE 590-06 Case Studies in Machine Learning Applications
• COMPSCI 671 D/ECE 590D Machine Learning
• COMPSCI 570/ECE 590D Artificial Intelligence
• ECE 590-002 Introduction to Deep Learning
• BME 590 -006 Machine Learning in Imaging
• EGRMGMT 599 Machine Learning Principles and Applications
• ME555 Data Drive Dynamics and Control

1 Elective from the list below: 

• ECE 590-26/ ME 555-28 Robotic Systems Design
• ECE 590-25/ME 555-27 Autonomous Systems Engineering
• ME555-28 Robotic Systems Design
• ME 555-06 Introduction to Robotics
• ME-555-04: Engineering Technology in Urology Applications
• CS 527 Computer Vision
• BME 590-001 Design Medical/Assistive Devices
• BME 590-05 Biotech Design
• BME 547 Medical Software Design
• ECE 590-07 Human Centered Computing
• I&E 721-01 Design in Healthcare
• Surg Star Duke Surgical Technique and Review (STAR)
• ME555-0? Lasers in Medicine
• BIOETHIC 602S Law, Research & Bioethics
• BIOETHIC 605S Contemporary Issues in Bioethics & Science Policy
• BIOETHIC 704/LAW 333 Science, Law, & Policy
• BIOETHIC603S Clinical Bioethics & Health Policy
• BIOETHIC 605S Contemporary Issues in Bioethics & Science Policy
• BIOETHICS680S Ethical Foundations of Innovative Technology Policy
• BIOETHIC 704 Frontier Robotics
• I&E Intellectual Property Law: Law, Policy and Practice
• BME 590 Biomedical Device Innovation
• I&E 590 01 Special Topics I&E Global Health Practicum
• EGRMGMT 520 Intellectual Property Business Law and Entrepreneurship
• EGRMGMT 590 Intellectual Asset Management