Assisted in research under Dr. Isaac Macwaan on the modeling and simulation of bacteriorhodopsin, a membrane-embedded protein, and its interaction with synthetic polymers used in electrospinning. The study also compared bacteriorhodopsin's interactions with carbon nanotubes and graphene oxide nanoparticles. Responsibilities included utilizing Visual Molecular Dynamics (VMD) to visualize and analyze biopolymers, and employing NAMD2 and CHARMM to design and run high-performance simulations of biomolecular systems. Conducted detailed analyses on simulations, including NAMD energy, salt bridges, root mean square deviation (RMSD), interaction energy, optimal distances, solvent-accessible surface area, and Ramachandran plots.

Assisted in research under Dr. Danushka Bandara focused on applying machine learning to brain activity data, specifically using functional near-infrared spectroscopy (fNIRS) and convolutional neural networks (CNNs) to identify brain regions associated with cognitive strain during demanding tasks. Responsibilities included setting up and conducting fNIRS experiments, analyzing visual imagery data using CNNs, and organizing tabular data recorded throughout the spectroscopy learning process.

Assisted in research under Dr. Anita Fernandez, using C. elegans to model the relationship between dhc-1; mel-28 double mutants and reduced brood size. Contributed to investigating how disruptions in dynein and mel-28 impact oocyte maturity. Responsibilities included conducting RNA interference-based genetic interaction screening using mel-28 and wild-type larvae, as well as developing Python scripts to analyze RNAi screening data and assess correlation patterns.

Perform multi-step organic syntheses to develop compounds with precise properties and structures. Ensure the accuracy and calibration of laboratory instruments, including pH meters, balances, and chromatography systems, by adjusting them to established standards. Maintain detailed and accurate records of experimental procedures, observations, and results to ensure reproducibility and compliance with regulatory standards.

Assisted in Dr. Carsten Marr's lab, contributing to research focused on improving the diagnosis and treatment of severe blood disorders through the development of machine learning algorithms for classifying individual cells and patients. The lab utilized single-cell big data analysis to identify drug targets and applied mechanistic mathematical models to time-resolved haematopoiesis data. Responsibilities included testing the accuracy of image-based software for classifying leukemia, reviewing patient data from LMU and comparing machine-generated results to clinical outcomes, as well as analyzing scripts and proposing edits to improve efficiency.