Education
Harvard University (August 2018 - Present)
- Ph.D. in Systems, Synthetic, and Quantitative Biology
- Thesis advisor: Benjamin de Bivort
University of Chicago (August 2014 - June 2018)
- B.S. in Statistics, B.S. in Biological Chemistry
- Senior honors thesis: Mathematical Modeling of the Cyanobacterial Circadian Clock
- Advisors: Aaron Dinner, Mike Rust
Research Experience
Graduate Student Researcher, de Bivort Lab (Harvard University)
- Developed a Python-based biophysical model of the fruit fly olfactory circuit, based on the wiring diagram from a real fly, capable of simulating dynamics of $\sim$3,000 neurons in response to odor stimuli (preprint on bioRxiv)
- Performing a Bayesian analysis of the olfactory circuit model to infer posterior distributions over biophysical parameters and compare capacities of different models to predict data (in prep)
- Building a novel fly-on-a-ball device that measures fly walking behavior while recording brain activity to study temporal variation in odor decision-making (in prep)
- Developed a random forest classifier that identifies fruit flies actively exhibiting signs of infection by the parasitic fungus E. muscae (contributed to article in eLife)
Undergraduate Student Researcher, Dinner & Rust Labs (University of Chicago)
- Developed a Python-based kinetic model of phosphorylation in the Kai proteins (the core circadian clock in cyanobacteria) and implemented Markov chain Monte Carlo-based Bayesian inference procedure to infer parameter values (published in Molecular Systems Biology)
Publications
- Churgin, M.*, Lavrentovich, D.*, Smith, M., Gao, R., Boyden, E., & de Bivort, B. (2023). Neural correlates of individual odor preference in Drosophila. bioRxiv. DOI: 10.1101/2021.12.24.474127
- Elya, C., Lavrentovich, D., Lee, E., Pasadyn, C., Duval, J., Basak, M., Saykina, V., & de Bivort, B. (2023). Neural mechanisms of parasite-induced summiting behavior in ‘zombie’ drosophila. eLife, 12. DOI: 10.7554/elife.85410
- Cammann, J., Schwarzendahl, F., Ostapenko, T., Lavrentovich, D., Bäumchen, O., & Mazza, M. (2021). Emergent probability fluxes in confined microbial navigation. Proceedings of the National Academy of Sciences, 118 (39). DOI: 10.1073/pnas.2024752118
- Hong, L., Lavrentovich, D., Chavan, A., Leypunskiy, E., Li, E., Matthews, C., LiWang, A., Rust, M., & Dinner, A. (2020). Bayesian modeling reveals metabolite-dependent ultrasensitivity in the cyanobacterial circadian clock. Molecular Systems Biology, 16 (6). DOI: 10.15252/msb.20199355
*: equal contributions
Skills
- Programming languages:
- 8+ years of experience with Python
- data handling / visualization: numpy, pandas, matplotlib, seaborn
- statistical inference: cmdstanpy, PyMC, emcee, PyVBMC
- machine learning: scikit-learn
- neuron modeling: BRIAN
- Proficient in STAN, R, git, Bash, LaTeX, parallel computing
- 8+ years of experience with Python
- Languages:
- English (native), Ukrainian (near fluent), Russian (native)