Bioengineering, Current Students

Spring 2008 UCB Courses:

BioE 290A Numerical Methods in Cardiovascular Engineering Research
Day/Time: TT, 3:30-5, 179 Stanley
Instructor: Liang Ge
Units: 3
Prerequisities: BioE 102; programming experience; graduate standing or permission of instructor

Course Description:
This course covers the two main numerical simulation tools used in cardiovascular engineering research: computational fluid dynamics (CFD) and computational solid mechanics (CSM). A brief overview of the cardiovascular system, cardiovascular diseases and the application of mechanical engineering principles to study these diseases will be provided. Detail explanation of the state-of-the-art development in both CFD and CSM will be presented. Toward the end of the course students will be also exposed to the applications of these advanced tools to real-life cardiovascular engineering research.

Goals:
This course is aimed at providing students with background necessary to conduct original research in cardiovascular engineering. The students will be introduced to the basic engineering principles
applicable to the cardiovascular system, challenges in solving the mathematical system describing the cardiovascular system and the state-of-the-art tool developed to address these issues.

Syllabus (lecture number):
1. Introduction(1)
2. Blood flow and governing equations (2-3)
3. Classification of partial differential equations (PDE)(4)
4. Taylor series and finite difference(5)
5. Consistency, stability and convergence(6)
6. Numerical methods for parabolic PDE(7)
7. Elliptic PDE(8)
8. Hyperbolic PDE(9)
9. Iterative methods(10-11)
10. Numerical methods for unsteady problems(12-13)
11. Solution of Navier-Stokes equations (14-17)
12. Cardiac anatomy and histology (18)
13. Cardiac physiology and ventricular function (19)
14. Continuum mechanics: constitutive laws (20)
15. Continuum mechanics: differential equations of equilibrium (21)
16. Continuum mechanics: principle of virtual work (22)
17. Finite element (FE) models for passive ventricular mechanics (23)
18. FE models for systolic ventricular mechanics (24)
19. FE models for ventricular mechanics with ischemia/infarction (25-26)
20. Fluid/structure interaction (27-28)
21. Applications (29-30)

For any questions, please contact This e-mail address is being protected from spam bots, you need JavaScript enabled to view it . Thanks

MSE 151
Course Description:
This 3-unit course is designed for upper division undergraduate students and graduate students to gain a fundamental understanding of the science of polymeric materials. It introduces fundamental principles governing polymer synthesis, phase behaviors and various techniques to characterize polymeric materials. The course also introduces the fabrication and applications of polymeric materials, particularly in the thin films, in the nanosciences, nanotechnology, and biotechnology.

Course Prerequisites:
Chem 1A or E 5 required, MSE 103 recommended

MSE 151 Course outline:
Introduction to polymer; Polymer synthesis; Single polymer chain; Polymer blends and solutions; Networks and Biopolymers; Polymer structural characterization; Polymer thin films and applications in nanotechnology; Polymer applications in biotechnology; Field tours and laboratory hands-on experiences….

According to Dr. John Kelly, IBM's senior vice president of research and development, "To our knowledge, this is the first time anyone has used nanoscale self-assembled materials to build things that machines aren't capable of doing."

Developing the Research Agenda for Biotech Operations (IEOR 290C).
In spring 2008, we will be offering a new course designed to develop a research agenda for operations in the biotech industry. This course builds on the highly successful Bioproduction Forum held in Fall 2007, and is designed for graduate students in IEOR (as well as other departments) who are new to Biotechnology, or who are looking to do research in this exciting new field.

In this project-based course, interdisciplinary teams of four students will collaborate to outline the issues in one specific area of the Biotech industry. Working closely with advisors both in industry and academia, teams will formulate questions which will be discussed in an industry-academic workshop to be held at Berkeley in May 2008.

The ultimate objective both of this course and of the workshop will be to establish a set of biotech operations research questions interesting to both academia and industry. There is a $1000 prize offered to the team with the best research ideas.

Research Proposal Competition:
As part of the course, students will compete to produce a comprehensive research proposal. Like a business plan, the research proposals / plans developed in this class will outline the current state of research in a particular area and suggests practical problems which are novel and fundamentally different from existing research in the field. They can also outline some potential approaches to addressing these problems.

The proposal will include a literature review of a particular research area, the outcomes of detailed interviews with leading Biotechnology companies, a detailed summary of the current state of the art in the area in which the team is working, a general overview of potential research directions in the teams area, and a set of more specific research project proposals. The best proposals will be presented at the Bioproduction Group’s industry conference in May 2008, and will be judged by a joint industry-academic panel.

Enrollment in IEOR 290C (CCN: 41125)
Spaces for the inaugural Bioproduction Course are currently available, but severely limited due to a class size limit of 20.

The course will be held on Wednesdays 12-1:30pm, in Etcheverry's Shephard Room (3117).

The Course Control Number (CCN) is 41125. This is a three-credit letter grade class with no pre-requisites.

Note: the course is listed as 'Statistical Aspects of Discrete Event Simulation' in the online catalog and in telebears. The actual course name is 'Developing the Biopharmaceutical Operations Research Agenda'.

Computational Nanoscience
Spring 2008

Course (cross-listed): Physics C203 (CCN 69735) / NSE C242 (CCN 61011)
Day, Time & Location: TuTh 9:30-11:00 AM, 325 LeConte Hall

Instructors: Dr. Jeffrey C. Grossman and Dr. Elif Ertekin
Office: 319 Birge Hall
Phone: 642-8358
e-mail: This e-mail address is being protected from spam bots, you need JavaScript enabled to view it

Format: This course will consist of two 1.5-hour lectures per week and hands-on, interactive simulation using research and commercial codes as well as web-based simulation codes such as those found at nanohub.org.

Homework: Homework will consist of derivations related to the lectures, numerical experiments with existing codes, and a class project. We will stress the different computational approaches that are available for solving realistic problems in nanoscience.

Grading: The breakdown of a final grade for this course is as follows: class participation: 25%, homework: 25%, class project: 50%. There are no exams.

Prerequisites: Graduate standing or instructor approval.

Course Description: This course will provide students with the fundamentals of computational problem-solving techniques that are used to understand and predict properties of nanoscale systems. Emphasis will be placed on how to use simulations effectively, intelligently, and cohesively to predict properties that occur at the nanoscale for real systems. The course is designed to present a broad overview of computational nanoscience and is therefore suitable for both experimental and theoretical researchers. Specific examples of topics the course will cover are:
1) The central ideas behind a wide range of nanomaterials simulations methods
2) How to break down a nanoscale problem into its “simulatable” constituents, and then piece it back together
3) How to simulate the same thing in two different ways
4) How to know what you’re doing and why thinking is still important
5) The importance of connecting simulation directly with experiment
6) What to do with all of that data, and how to judge its accuracy and validity
7) Why the “multi-scale” modeling picture is critically important and also nonsense

While some aspects of the simulation methods such as numerical algorithms will be presented, there will be little if any programming required. Rather, we will emphasize the intelligent application (as opposed to “black box” use) of codes and methods, and the connection between the computer results and the physical properties of the problem.

Required Textbooks: Due to the wide-ranging nature of material covered in this class, there will be no specific required textbooks. A combination of published review articles and relevant books will be encouraged as reading material. In addition, Powerpoint and Breeze presentations will be posted on the course web site.

Synchrotron Radiation for Materials Science Applications
Professor David Attwood
EE290F, cc# 25757 (likely to be approved as co-list AST290S)
Spring 2007, Tu-Th, 2-3:30 PM, 203 McLaughlin