Instructor(s): Reza Abbasi-Asl

This course will establish the foundations of deep learning through lectures, weekly seminars, and a hands-on approach in Python. We will cover the basics of regression and classification, model optimization, and neural network architectures, including autoencoders, convolutional networks, and transformers, with the use cases of these models in biological and clinical research. This is the same class as BIO MD INF 212. Students should ensure they are registering for the right course number.

Instructor(s): Staff

Laboratory research rotations are to allow students to become familiar with different areas of research, learn new experimental techniques, obtain experiences in unique research laboratories, and ultimately to identify a lab in which to conduct dissertation research. Rotation projects should involve hands-on research and be a piece of work that the student can present at the end of the rotation.

Instructor(s): Jeffrey Lotz, Tamara Alliston, Valerie Weaver

A central role for many tissues is to support physical forces (tension, compression, shear, pressure). This course will introduce the mechanisms by which cells respond to load; how these mechanisms are relevant to normal function & disease etiology; progression; prevention & treatment; an overview of tissue mechanics (relationships between force, stress/strain), mechanisms of cell/matrix interactions, examples of tissue modeling & remodeling in response to physical stimuli.

Instructor(s): Peder Larson

This introductory course aims to teach the basic principles behind magnetic resonance imaging (MRI). It will cover the physical principles of magnetic resonance, image formation, and image reconstruction, MRI hardware, contrast generation, and common artifacts. Cross-listed with BIOMED IMG 201.

Instructor(s): John Kurhanewicz

This course is designed to follow BIOENGR 240 or BIOMED IMG 201, Magnetic Resonance Imaging. It will build on the fundamental aspects of magnetic resonance physics presented in the first course, but will focus on MR spectroscopy which provides metabolic and biochemical information. The course will cover basic theory, underlying biochemistry and physiology, techniques for acquiring and processing MR spectroscopic data, and biomedical applications for this emerging medical modality.

Instructor(s): Srikantan Nagarajan, Yang Yang, Ashish Raj

The goal of this course is for students to understand various machine learning algorithms that are used in brain imaging, and to gain hands-on experience using them in student projects, homework, and student-driven class-presentations. Common machine learning algorithms used for MRI, fMRI, EEG, MEG, and ECOG, will be the focus of the course.

Instructor(s): Staff

Advanced study in various subjects through seminars on topics to be selected each year, informal group studies of special problems, group participation in comprehensive design problems, or group research on complete problems for analysis and experimentation.

Instructor(s): Staff

In this course, students will work together with a primary research advisor to select a research question and design a project plan that will be carried out by the student. Through this experience, the student will gain experience in research strategy and execution, as well as experimental techniques and analysis and interpretation of results. At the conclusion of this course, the student will present on their progress.

Instructor(s): Marc Shuman

This course focuses on solutions to challenges in the diagnosis and treatment of diseases of the eye, hereditary disorders and cancer. Lecturers with diverse skills discuss their experience in navigating this process. They have successfully solved challenges in their fields that led to commercialization. They will cover technical and scientific limitations and opportunities for advances with inventions in biomarker development and technology for delivery of new types of treatment.

Instructor(s): Shuvo Roy

This course covers a broad range of topics in the development and operation of medical diagnostics, devices, and therapeutics and combines lectures, readings, case studies, and class discussion. It will feature regular UCSF faculty as well as industry professionals.

Instructor(s): Hanmin Lee

The goal of this course is to give students interested in medical device innovation an introduction to the workings of the health system. Learners will explore the structure of hospital systems and distinguish stakeholders and their roles. By learning how different players put medical technology to use, students will learn to identify gaps and unresolved needs.

Instructor(s): Adam Abate

The objective of this course is to introduce students to the broad range of bioengineering research that is associated with biological applications. Students will be exposed to problems in cellular and molecular engineering, tissue engineering and modeling neural and complex systems. Each session will involve presentations from invited faculty members of specific areas of research.

Instructor(s): Shuvo Roy

Introduces students to the strategies applied to clinical study design for a variety of medical technologies. Main elements of a clinical protocol such as objectives, study design, patient population, sample size and endpoints will be taught in context of company value creation and risk reduction. Students will receive an overview on the regulatory requirements associated with conducting clinical trials for medical technologies. Course will be taught by industry experts.

Instructor(s): Joanne Spetz

This course focuses on how current health care financing systems and emerging trends affect strategic technology development and market decisions. This course is designed so students understand the underlying drivers of rising health spending, the policies that might slow it, and the impact of possible policies on future product markets. The course covers the fundamental components of health economics, financial analysis, and strategies to increase health care value.

Instructor(s): Shuvo Roy

The objective of the MTM program is to develop leaders who can synthesize the technical, economic, and social issues involved in the design and operation of complex medical devices, systems, and organizations. Students will develop and demonstrate these skills through the capstone project and course activities. This course combines classroom instruction with outside project work. In addition to lecture, teams meet with outside mentors and develop project.

Instructor(s): Staff

Reading and conferences for properly qualified students under the direction of a member of the staff.

Instructor(s): Staff

For graduate students engaged in writing the thesis for the master's degree.

Instructor(s): Staff

This course is for students who have finished research and data collection, and are writing their dissertation. It is customized by the instructor for each student(s), depending upon their exact dissertation topic.