James Mcfarland Email and Phone Number

- Leading the Cancer Data Science team of ~20 computational biologists and software engineers using machine learning, statistics, and bioinformatics tools to identify and understand cancer vulnerabilities- Responsible for data science and computational strategy for the Cancer Dependency Map project

- Analytics lead on multiple target discovery and drug development projects.- Developed computational methods for analyzing large-scale functional genomics data (CRISPR and RNAi screens).- Built interpretable machine learning models for identifying predictive biomarkers of genetic dependencies and drug sensitivities in cancer- Co-developed method for using multiplexed single-cell RNA-Seq to characterize perturbation responses across diverse cancer cell contexts.- Created machine learning tool for integrative analysis of tumor and cell line genomics data.

Selected from top ~2% of applicants to participate in a rigorous 2-month data science training program. Weekly course modules cover topics including: web-scraping, SQL, natural language processing, machine learning, and distributed computing.

My research focused on understanding neural computation in the visual cortex. Specifically, I developed and applied statistical modeling tools to study how visual information is represented and processed by cortical neurons, and how such neural representations are in turn shaped by factors such as ongoing network dynamics and eye movements.

As a graduate student in the lab of Dr. Mayank Mehta, my research focused on interactions between single neurons and the cortical network during 'slow oscillations' characteristic of sleep. I also studied the representation of spatial position among populations of hippocampal neurons.

Worked with Dr. John Soechting studying haptic perception using a programmable robotic arm.

Research in the lab of Dr. David Tanenbaum, studying carbon nanotube growth using experiments and fluid dynamics simulations.

Summer research project calibrating a solid state beta particle detector as part of an experiment measuring the rest mass of the neutrino.

Summer research project using electron and atomic force microscopy to study carbon nanotube growth.