BioPACIFIC MIP Research: SET 4 - Degradation-Optimized Materials
What is your research focus?
My advisor Dr. Mengyang Gu and I are currently working on the next stage of previous Differential Dynamic Microscopy (DDM) project that aims at reducing the computational cost and improving the robustness of estimation to extend the algorithm to a broader range of system. DDM is a relatively new technique of microscopic analysis, as it can be fully automated and it can apply to experimental data where the traditional particle tracking algorithm fails. Our new statistical framework DDM-UQ and its corresponding MATLAB software package have enabled fully automated, fast analysis for extracting mean squared displacement (MSD) using this technique. This project will improve our current framework in various dimensions, which includes: 1) developing a new method that relates MSD to pixel intensity, which can allow robust estimation in large lag time; 2) reducing the computational costs without image reconstruction techniques 3) adding more features for current analysis module in our MATLAB software package, such as estimating bulk moduli from MSD; 4) deriving more efficient estimates for model parameters (specifically, A(q): the Fourier transformed probe intensity profile & B(q): transformed background noise variance), 5) extracting information from microscopic videos for anisotropic and nonergodic systems, such as cell migration and alignment processes.
What excites you about NSF BioPACIFIC MIP?
As a selected Fellow in the previous year, I think what excites me the most about BioPACIFIC MIP is it gives massive opportunities for interdisciplinary collaborations, and for students to talk to excellent faculties, researchers, and people from industry. It’s a great opportunity to build up network, learn requirement for different companies, and prepare myself in an early stage. Additional to that, I found research presentations and literature reviews held by graduate students are intriguing as well. This platform enables learning of new things, spark of new ideas from a different point of view, and realization of potential new technique, which not only help my current research, but also help come up with new research topic. And I think it will be a great opportunity for me to practice translating scientific problems to statistical algorithms.