Application of engineering principles towards mechanistic insights into biological systems and engineering robust solutions inspired by bio-design (self assembly and coordinated events).
I develop rigorous quantitative analytical approaches for interpreting the results from both computational and wet experiments. The primary goal is not only to extract mechanistic information out of data, but also to be able to predict biological features in spite of "complexity" of the systems.
The real challenge in my scientific world lies in development and/or discovery of functional assays (both theoretical and experimental) for biological questions of my interest, data from which is then analyzed using self-developed robust analytical systems or theoretical (mechanistic) frameworks. Therefore, the computational component in my research is often more labor intensive than the experimental component.
While today's definition of "successful" biological research falls under the category of "hypothesis driven science", I still prefer to enjoy the non-materialistic rewards in the world of "observation driven science". A substantial effort in my work goes into extracting quantitative signatures from biological data for (a) understanding origins of life, and, (b) developing functional applications, of the discovered signatures, relevant to biological research.