This course teaches how to `get things done' in a bioengineering laboratory where the interdisciplinary nature of the field creates barriers due to lack of awareness of what is possible. The project-based course empowers students to build custom experimental infrastructure, run fundamental `wet' bioengineering experiments, and analyze data. Key approaches covered in the course include: rapid prototyping; tissue culture and engineering; microscopy; functional image analysis; and core approaches in synthetic biology and genetic engineering.

This course provides a foundational exposure to contemporary research topics in Bioengineering, as well as lectures and panel discussions on strategies for success in the PhD program. The latter include strategies for time-management, selecting interesting research problems to focus on, as well as effective communications with the advisor, how to get the most out of rotations, how to write papers and give talks, and navigating collaborations.

This course offers an introduction to computational chemistry and molecular simulation, which are essential components to modern-day science and engineering, as they can provide both mechanistic insights underlying observed phenomena and predictions on thermodynamic/kinetic properties. Through pedagogical treatment of essential background, basic algorithmic implementation, and applications, students will develop knowledge necessary to follow, appreciate, and devise computational 'experiments'. Topics of emphasis include quantum chemical solution methods, Monte Carlo & molecular dynamics, and free energy/enhanced sampling.

For the past three decades have witnessed an explosion of new forms of optical microscopy that allows us to study living systems with unprecedented details. This course aims to cut through the confusion of the wide array of new imaging methods by offering both a unified theoretical framework and practical descriptions of the pros and cons of each. In addition, this course also explores advances in computational tools, especially recent advances in AI, for image visualization and quantification.

At a 10 nanometer scale, protein machines 'walk' on microtubule tracks. At a scale 10,000 times larger, networks of interacting genes pattern a developing embryo into different body regions. This course will examine these and other complex biological systems at the molecular, cellular, and multicellular scales. In parallel, we will cover emerging methods for quantitatively probing and analyzing biological systems. Specific topics will include structural biology from crystallography to cryo-electron microscopy, enzyme kinetics, gene regulatory networks, next-generation sequencing, data mining, simulating biological models and image analysis.