Problem Solver
Milana Filatenkova
Areas Milana Filatenkova is Knowledgeable in:
Mathematical modelling, Machine learning, Data analysis, Statistics, Bioinformatics, Genomics
Techniques Milana Filatenkova Uses:
probability theory, stochastic differential equations, statistical inference, machine learning
Milana Filatenkova's Problem Solving Skills:
- Python
- R
- Statistics
- Python scipy
- Web-scraping with RSelenium & Python Scrapy
- Python numpy
- Python pandas
- SQL
Milana Filatenkova's Problem Solving Experience:
- - I solved stochastic differential equations for starch polymerization using branching
theory and Gillespie algorithm (implemented in rule-based modeling language - Kappa)
and fit the solution to chain length distribution data - - I carried out analysis of motion sensor data obtained from pro riders: I filtered noisy
accelerometer and gyroscope readings and combined them to extract motion highlights - - I derived a Hidden Markov Chain model to quantify the key parameters of a molecular
system from large noisy genomics data (100 Mb)