Independent Study (BE 490/492; Fall or Spring)
Faculty encourage every bioengineering student to explore research opportunities during their undergraduate career at Penn. Students can enroll in up to two semesters of independent study to earn class credits while working within the labs of faculty members across Penn’s campus, including the medical school, the veterinary and dental schools, the School of Arts and Sciences, and Penn Engineering.
Independent study projects span diverse biomedical research areas. Students have tested high-density flexible electrodes for the treatment of epilepsy, investigated fat storage cell formation, and attempted to synthesize artificial red blood cells to treat disorders like sickle-cell anemia. Many undergraduates have even published their independent-study research findings in peer-reviewed journals.
Senior Design Project (BE 495; year-long)
Students in BE 495 are organized into teams of 3-4 persons to design a device, system, material, process, or method, subject to real-world constraints including time, money, and resources. Day-to-day work is carried out in Penn Engineering research spaces and a modest budget is provided for each group’s project. Groups complete and document major planning aspects of the design process, demonstrate feasibility and need, and develop a plan for implementation and testing. The student groups also give several oral presentations about their projects, including to their classmates and in the annual SEAS Senior Design competition.
Instructor: Michael Rizk
Brain-Computer Interfaces (BE 521; Spring)
Brian Litt, M.D., and guest lecturers who have “real-world” experience in designing and developing implantable medical devices in research and industry, cover topics from the basics of neurosignals to deep-brain stimulation and antiepileptic devices. Students learn about software, brain-computer interface (BCI) hardware, the regulatory and approval process for devices, and start-up companies and entrepreneurship in BCI from one of the field’s pioneers in implantable brain devices. By the end of the course students will be able to design and implement a scaled-down computer interface device in computer software simulations, and understand basic concepts involved in its implementation and approval.
Instructor: Brian Litt
Biomicrofluidics (BE 551; Fall)
The focus of BE 551 is on microfluidics for biomedical applications, including microscale transport phenomena, small-scale fabrication techniques, and sensing technologies that are often leveraged in the development of microfluidic systems for the study of biomolecules, cells, tissues, and organs in living biological systems. The course also places a strong emphasis on the application of microfluidics in cell biology, bioanalytical chemistry, molecular biology, tissue engineering, and drug discovery.
Instructor: Dan Huh
Tissue Engineering (BE 553; Spring)
Tissue engineering demonstrates enormous potential for improving human health. BE 553 explores principles of tissue engineering, drawing upon diverse fields such as developmental biology, cell biology, physiology, transport phenomena, material science, and polymer chemistry. Current and developing methods of tissue engineering, as well as specific applications are discussed in the context of these principles. A significant component of the course involves review of current literature within this developing field.
Instructor: Jason Burdick
Network Neuroscience (BE 566 ; Fall)
The human brain produces complex functions using a range of system components over varying temporal and spatial scales. These components are coupled together by heterogeneous interactions, forming an intricate information-processing network. In BE 566, students learn about the use of network science in understanding such large-scale and neuronal-level brain circuitry. The course begins with a brief introduction to network science and associated tools for data analysis, mathematical modeling, and statistical inference, and progresses to an examination of the use of structural and functional brain networks extracted from non-invasive neuroimaging data (fMRI, MEG, MRI, DTI, DSI) in determining fundamental organizational principles of neuronal processes. Students review evidence for alterations in these network structures in psychiatric disease, neurological disorders, and brain injury. The course concludes with a section focused on the use of dynamic networks in understanding cognitive functions including learning and lexical processing.
Instructor: Danielle Bassett
Modeling Biological Systems (BE 567 ; Fall)
In BE 567, students learn about topics in systems biology at the molecular/cellular scale. The emphasis is on quantitative aspects of molecular biology, with possible subjects including probabilistic aspects of DNA replication, transcription, translation, as well as gene regulatory networks and signaling. Students will be actively analyzing and simulating models of biological behavior using MATLAB. The course also covers the development of new experimental methods (including imaging and sequencing) and how researchers are using them to generate a more quantitative picture of molecular biology.
Instructor: Arjun Raj