Data Computer Science
Resume:
Galina Malovichko, PhD ******.*****@*****.***
Profile
• 2 years of data analysis and machine learning experience in a scientific environment
• Selected ML algorithms: linear / logistic regression, random forest, gradient boosted trees, SVM, kNN, PCA, k- means
• Technologies: Python, numpy, pandas, scipy, scikit-learn, matplotlib, git, SQL Education
2017 Ph.D., Condensed Matter Physics • University of California, Davis 2009 M.S., Physics • Moscow Institute of Physics and Technology, Russia 2007 B.S., Physics • Moscow Institute of Physics and Technology, Russia Work Experience
2012-2017 UC Davis • Graduate Student Researcher
• I implemented early steps of drug development pipeline, conducting multiple high-throughput experiments with 50k+ of chemical reactions in each experiment and tracking the reactions with polarized light. I derived geometrical features from microarray images for heuristic reaction detection and fitted various chemical mod- els to the binding curves. I also numerically modeled the optical signal as a function of microarray physical properties and explored limitations of approximate analytical solution.
• Performed dose-response analysis of chemical binding in the presence of an inhibitor. I aggregated experi- mental data from over 380 images of 25 features of interest in each image, modeled, fitted and plotted binding strength dependence on inhibitor concentration.
• Screened sets of 3.5k+ peptides of similar composition against protein ligand to investigate the effect of small changes in peptide composition on binding strength and synthesis efficiency. I filtered and aggregated microar- ray images and binding curves data to visualize and quantify these effects.
• Applied ellipsometry to measure thin film magnetization in the presence of the external field. I de-spiked, de-trended and averaged multiple hysteresis loop curves to increase signal-to-noise ratio. Technologies: Python, numpy, pandas, scipy, matplotlib. 2011-2017 UC Davis • Teaching Assistant
• Taught and graded multiple lower- and upper-division physics courses. 2011-2017 NT-MDT •QualityControlEngineer
• Ran series of tests on atomic force microscopes and scanning tunneling microscopes. Acquired test images, I-V curves and approach curves to evaluate device performance.
www.linkedin.com/in/malovichko k www.kaggle.com/galinamalovichko
******.*****@*****.***
Independent Coursework
Self-motivated learner with demonstrated success from a variety of online data science courses. Coursera 10 verified certificates
Machine Learning • Introduction to Recommender Systems • Getting and Cleaning Data • Regression Models
• Practical Machine Learning • Basic Statistics • R Programming • The Data Scientist’s Toolbox • Exploratory Data Analysis • Programming for Everybody (Python) edX Introduction to Computer Science and Programming Using Python Publications
• Malovichko, G., Zhu, X.D. (2017) ”Single Amino Acid Substitution in the Vicinity of a Receptor-Binding Domain Changes Protein–Peptide Binding Affinity.” ACS Omega 2, 5445-5452
• Zhu, X.D., Malovichko, G. (2017) ”Zero Loop-Area Sagnac Interferometer at Oblique-Incidence for Detecting in-Plane Magneto-Optic Kerr Effect.” AIP Adv. 7, 055008
• Wang, X., Malovichko, G., Mendonça, M., Rochedo Conceição, F., Aleixo, J.A., Zhu, X.D. (2016). ”Label-Free Real-Time Monitoring of Reactions Between Internalin A and Its Antibody by an Oblique-Incidence Reflectivity-Difference Method.” J Opt Soc Korea. 20, 165-168
• Landry, J.P., Malovichko, G., Zhu, X.D. (2015) ”High-Throughput Dose–ResponseMeasurementUsingaLabel-FreeMicroarray- in-Microplate Assay Platform.” Anal. Chem. 87 (11), 5640-5648
• Landry, J.P., Proudian, A.P., Malovichko, G., Zhu, X.D. (2013) ”Kinetic identification of protein ligands in a 51,200 small- molecule library using microarrays and a label-free ellipsometric scanner,” Proc. SPIE 8587, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XI, 85871V.
www.linkedin.com/in/malovichko k www.kaggle.com/galinamalovichko
Contact this candidate