Dariya Bakshinska, Ph.D.
Senior Computer Vision Engineer @ Farsight Vision
About
I’m a computer vision engineer with a Ph.D. in Neuroscience from UC Berkeley, where I developed advanced imaging pipelines to study neural circuits. Now I design large-scale vision systems at Farsight Vision, creating tools that can make sense of messy, real-world data from drones. From synapses to geospatial scenes, my work focuses on turning complex visual data into something clear and actionable. Continuing along the imaging thread, I also translate footage for award-winning documentaries about Ukraine, ensuring cultural nuance and accuracy. I’m most at home working on hard problems, especially when the data are noisy and the path isn’t obvious.
United States
Oakland
Research
Experimental Design, Computer Vision, Deep Learning, OpenCV, 3D Reconstruction, SLAM, Project Management, Image Processing, Image Analysis, Scientific Writing, Python, Signal Processing, Machine Learning, Written Communication, Statistical Data Analysis, Conferences, Technical Writing, Scientific Presentation, Animal Studies, Data Analysis
Experience

Computer Vision Engineer
At Farsight Vision, I design large-scale computer vision pipelines that make sense of messy, real-world drone imagery. My work spans the entire lifecycle: curating and preprocessing multi-terabyte geospatial datasets, fine-tuning state-of-the-art models (SuperPoint, DINOv2, YOLO) to handle low-texture and harsh-lighting conditions, and packaging them into reproducible tools for the team. I focus on translating cutting-edge research into production-ready systems: building robust, scalable workflows that bring complex visual data into real-world use.

Ph.D. in Neuroscience
Completed a Ph.D. in Neuroscience in Dr. Ehud Isacoff’s lab, where I led a cross-disciplinary research program focused on the molecular determinants of synaptic heterogeneity. Built and optimized advanced imaging pipelines for calcium imaging and super-resolution confocal microscopy, addressing challenges in noise reduction, signal extraction, and resolution enhancement from high-dimensional datasets. Applied machine learning models to classify genotypes from imaging-derived protein expression, uncovering genotype-specific molecular patterns, and published findings in PNAS and Nature Communications.

Methods in Computational Neuroscience Graduate Student Fellow
Woods Hole, Massachusetts, United States
▪ One of the fellows selected to carry out a computational neuroscience project using open-source data ▪ Applied an array of computational methods/models to hippocampal place cell data including Generalized Linear Models ▪ Designed and executed an independent computational neuroscience project investigating differential coding between phases of theta and hippocampal place cell activity in 2D environments.

Research Specialist I/II
Princeton, New Jersey, United States
Research Specialist in Sam Wang's lab where I was involved in a few different projects which included the following: ▪ Analyzed and quantified behavioral data obtained from mice undergoing a virtual reality evidence accumulation task. ▪ Performed UV/Vis spectroscopy and fluorimetry measurements to partially characterize GCaMP6f variants (Kd and nH). Furthermore, employed stopped-flow photometry to characterize the on- and off-kinetics of GCaMP6f variants in vitro ▪ Designed subcellular localization plasmid constructs expressing GCaMP6f and localization proteins for further characterization in primary hippocampal culture ▪ Performed surgeries in mice to trace anatomical projections from the cerebellum to the neocortex using HSV-H129 followed by tissue clearing using iDISCO
Dariya Bakshinska, Ph.D.'s Contact Information
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