I work in the area of computational biophysics. In short, I look at the jiggling and wiggling of proteins using molecular dynamics simulations and try to find how the protein works or how to target that protein. In my PhD, I pursued coarse-grained (CG) forcefield development for all things sugars, including glycans, glycosaminoglycans. We used these sugar models to study their interactions with viral as well as receptors proteins.
I have been trained in using computational tools for understanding biophysical problems. Apart from research, I am huge photography and drone geek. Love to make digital arts using new tips and techniques.
Aishwary Shivgan
aishwaryshivgan55@gmail.com
Portfolio
Protein design
Advanced algorithms to predict, optimize, and generate protein structures with desired functions. By analyzing vast biological datasets, these models accelerate the discovery of novel proteins for therapeutic, industrial, and research applications, offering unprecedented speed and precision compared to traditional methods.
Molecular dynamics simulations
Computer-based methods that model the physical movements of atoms and molecules over time. By using physics-based force fields, MD allows scientists to visualize how biomolecules like proteins and DNA behave in realistic environments — helping to reveal their structure, flexibility, and interactions at various resolution.
Drug Discovery
Development of novel drugs by applying computational techniques to identify potential drug targets and design small molecules with high binding affinity. Conducted virtual screening and molecular docking studies.
Deep Learning
Subset of machine learning that uses neural networks with multiple layers to analyze complex patterns in data. Inspired by the human brain, it powers advanced technologies like image recognition, natural language processing, and autonomous systems — enabling machines to learn from large datasets and make intelligent decisions
Created visually appealing and informative data visualizations to present complex biological data in a clear and intuitive manner. Utilized tools like D3.js and matplotlib to generate interactive and publication-quality plots.
Multiscale modelling
Using the Martini coarse-grained force field, complex biomolecular systems can be simulated efficiently over longer timescales — capturing essential dynamics like membrane organization, protein folding, and large-scale conformational changes with reduced computational cost.