Hardware, Software, Wetware, Co-Design Research
High level application specifications are automatically converted to hardware to support the functional, structural, and performance requirements of the described application. In CIDAR, this hardware takes the form of custom microfluidic devices that can control, manipulate, and process data for engineered biological systems.
Software tools and algorithms provide mechanisms to map application functionality to biological elements (e.g. compile to DNA). In addition, software can be automatically generated to control microfluidics to meet specific function and performance requirements.
Engineered biological building blocks with well characterized performance parameters are the primitives on which CIDAR research designs systems. These elements are explicitly designed to be amendable to high throughput assembly protocols and are stored both virtually and physically using on-line "parts registries".
Software tools make synthetic biology more effective by integrating concepts from electronic design automation into the specification, design, and assembly of complex biological systems.
CIDAR is composed of a diverse team of undergraduates, graduate students, post-docs, and research staff from a range of programming, engineering and scientific backgrounds.
Mixed Purpose Workspaces
With both Computational and Wetlab facilities, CIDAR has workspaces for software development and biological engineering research across multiple departments at Boston University.
David publishes a review article in Lab on a Chip
Working with CIDAR Lab alum Ali Lashkaripour from the Fordyce lab at Stanford University, David co-authored a review paper surveying the applications of machine learning for microfluidic design and control. They also highlighted the challenges and outlook for machine learning-enabled microfluidics. Read the article here: https://pubs.rsc.org/en/content/articlehtml/2022/lc/d2lc00254j