POSITION
Ph.D., Massachusetts Institute of Technology, 2007
M.S.M.E., Massachusetts Institute of Technology, 2003
B.S.M.E., Georgia Institute of Technology, 2001
PROFILE
Dr. Craig Forest joined the Woodruff School of Mechanical Engineering as an Assistant Professor in August 2008. Since then he has established a research program focused on the creation and application of miniaturized, high-throughput robotic instrumentation to advance biomolecular science, along with the fundamental engineering that makes such instrumentation possible. Dr. Forest’s laboratory works at the intersection of bioMEMS, machine design, signal processing, optics, and manufacturing at the frontiers of the emerging bio-nano field. The development of instruments that can load, manipulate, and measure many biological samples at the resolution of single cells simultaneously with better accuracy and reliability than current approaches opens the door to essential, comprehensive biological system studies.
RESEARCH INTERESTS
Neuroengineering tools and robotics, ultra-high throughput genomics and molecular measurement instrumentation; 3-D microfabrication and bioMEMS technologies for neuroscience and genomics applications; and micro-lenslet arrays
In the course of the past 4.5 years, the instruments developed in the Forest laboratory have led to the genesis of a new field of intracellular in vivo robotics for neuroscience, a new virus detector that is a 10-100x improvement over pre-existing technologies, a device for personalizing drug dosage to prevent heart attacks, and a parallellized genome-engineering technique. Fundamental engineering advancements have been made in microfabrication, modeling flow of photons and fluids, and neuron identification within the milieu of the living brain. These instruments, and the discoveries they enable, are unlocking new frontiers in neuroscience and genetic science.
- Neuroengineering tools and robotics
- Ultra-high throughput genomics and molecular measurement instrumentation
- 3-D microfabrication and bioMEMS technologies for neuroscience and genomics applications
- Micro-lenslet arrays
