# Isabel Vanegas

> Software Engineer & Applied Scientist | Computational Neuroscience, Neural Engineering, Machine Learning, Algorithms

Location: San Francisco, California, United States
Profile: https://flows.cv/isabelvanegas

Software engineer & applied scientist with extensive research experience in computational neuroscience and neural engineering.

Experienced in computational modeling of neural systems, neural population dynamics, and electrophysiological recordings, including single- and multi-unit activity. My doctoral work applied statistical and machine learning methods to study neural mechanisms of Parkinson’s disease and neurodegeneration.

I now focus on developing algorithms and scalable AI systems, translating rigorous scientific methodology into reliable, production-quality software.

## Work Experience
### Software Engineer @ Alembic Technologies
Jan 2026 – Present | San Francisco, California, United States
- Develop algorithms and computational methods for scalable applications
- Build scalable software and computational workflows for production environments
- Collaborate across research and engineering to translate models into reliable systems

### Postdoctoral Researcher @ University of Utah School of Medicine
Jan 2018 – Jan 2025 | Greater Salt Lake City Area
- Conducted computational research on neural systems and neural population dynamics
- Developed modeling and analysis frameworks for cortico-cortical communication during visuomotor behavior.
- Developed scripts for real-time neural signal processing and workflows to visualize multimodal electrophysiological data.

### Clinical Research Coordinator - Dysautonomia Center, Department of Neurology @ NYU Langone Health
Jan 2017 – Jan 2018 | New York, New York, United States
- Led longitudinal studies on retinal and cortical biomarkers in Parkinson’s and autonomic disorders, involving 273 participants.
- Developed data processing scripts and a central database (Filemaker Pro, REDCap) to streamline data collection, analysis, and visualization.
- Managed participant retention, protocol adherence, and successfully supported regulatory audits.
- Collaborated with neurologists, ophthalmologists, and engineers to optimize clinical research execution.
- Conducted electrophysiological and retinal physiology measurements, including data analysis to predict retinal degeneration progression using mathematical modeling.

### Graduate Research Assistant - Neural Engineering Lab, Department of Biomedical Engineering @ The City College of New York
Jan 2011 – Jan 2017
- Collaborated with NYU Langone Health Neurology to study visuomotor processing in Parkinson’s using high-density EEG and eye-tracking.
- Managed IRB protocols, participant recruitment, and ensured regulatory compliance and data quality.
- Programmed visual experiments in MATLAB with Psychotoolbox and analyzed EEG data to study disease-related abnormalities.
- Applied machine learning methods (logistic regression, decision tree, SVM) to classify and predict Parkinson’s disease using neurophysiological data.
- Authored peer-reviewed publications and presented research at national conferences.


## Education
### Doctor of Philosophy - PhD in Bioengineering and Biomedical Engineering
The City University of New York

### Master of Science (MSc) in Biomedical/Medical Engineering
The City University of New York

### Bachelor of Engineering (BEng) in Bioengineering and Biomedical Engineering
Universidad de Antioquia


## Contact & Social
- LinkedIn: https://linkedin.com/in/m-isabel-vanegas-phd

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Source: https://flows.cv/isabelvanegas
JSON Resume: https://flows.cv/isabelvanegas/resume.json
Last updated: 2026-04-10