Past projects have specifically included:
- Designing, constructing, characterizing and optimizing a fluorescence-based microrheometer to quantitatively assess cellular mechanics with nanometer and microsecond resolutions;
- Developing molecular and cell biology assays and computer algorithms to study the role of environmental cues in regulating intracellular signaling and trafficking;
- Building non-linear optics-based microscopes, ranging from two-photon multi-foci and fluorescence resonance energy transfer (FRET) imaging apparatus, to fluorescence correlation spectroscopy (FCS) and quantum dot monitoring devices;
- Conceiving, maturing and manufacturing automated robotics platforms interfaced with mass spectrometers, for industrial applications in the fields of biopharmaceutical drug discovery, clinical research, metabolomics and quantitative proteomics.
Developing hands-on lab environments, pertinent and comprehensive, to quantitatively examine and understand biological systems is the central goal of my work.
My focus is on exploring and teaching what makes the design of an instrument good: what purpose and techniques make it relevant to answer a biological question, what hardware components make it robust and outstanding, what models and signal processing algorithms make its data informative.
The laboratory is often where knowledge becomes meaningful and fulfilling from being applied, tangible, and constructive. To students, the lab is where the bridge can be made between fascinating but sometimes vague concepts and the concrete appreciation of how these ideas relate to real-world problems and interesting forays in biology. Through the learning of solid design principles, and of hardware and software attributes, then through iterative, continuous improvement to a device and rigorous troubleshooting, comes the conclusion of which features and parameters effectively influence practical outcomes.
The discipline of Biological Engineering also offers researchers the great challenge and reward of intrinsically pushing the boundaries of traditional engineering approaches, in order to infer accurate rules from manipulating and monitoring dynamic, complex, and variable biological systems. Identifying and illustrating limits of detection and of deduction constitute a core goal of the 20.309 and 20.S947 classes I instruct.