University of Colorado Denver Behavioral Neuroscience Laboratories | 2015 – 2024
Cutting-Edge Optogenetic Implementation:
Launched an optogenetic protocol and experimental design,
expanding the lab’s research capabilities and fostering interdisciplinary approaches.
Chemogenetics Pioneering:
Initiated the use of chemogenetic techniques at the
University of Colorado Denver Downtown campus, contributing to advanced neural circuit analysis.
Self-Directed Technical Mastery:
Taught myself Med Associate operant behavior box functions
using MedState code, automating drug schedule control and managing extensive data output
collection and storage.
Professional Research Assistant
University of Colorado Boulder Institute for Behavioral Genetics | 2012 - 2015
Genotyping & Molecular Analysis:
Determined genotypes of multiple mouse strains using PCR,
gel electrophoresis, and molecular imaging, ensuring accurate genetic profiling and data integrity.
Database Management & Troubleshooting:
Managed, updated, and streamlined a multi-lab animal database
for a pathogen-specific facility. Conducted ongoing census and cross-referenced animal inventories
to resolve discrepancies and maintain reliable records.
Precision Equipment Operation:
Operated complex instruments including micro sampling systems and
long-term quantification protocols to ensure accurate, high-quality data collection.
Undergraduate Researcher
University of Colorado Institute for Behavioral Genetics | 2003 - 2012
Designed and executed complex experiments:
Applied advanced molecular biology techniques
to analyze genetic variations in mouse models, including nicotinic receptor differences in knockout strains.
Data-driven experimental planning:
Conducted systematic cross breeding and behavioral testing
to generate reliable datasets, ensuring precise phenotypic characterizations.
High-volume data management:
Managed data collection from a colony spanning 20 unique mouse strains
and hundreds of subjects, emphasizing rigorous record-keeping and analytical accuracy.
Management
Project Coordination:
Collaborated with multiple Principal Investigators to manage overlapping projects,
aligning diverse teams with experimental objectives and varied timelines.
Operational Oversight:
Coordinated inventory management and ensured regulatory compliance across experimental endeavors,
facilitating smooth and efficient project execution.
Communication
Research Presentations:
Delivered clear and engaging oral presentations of research findings to academic peers,
colleagues, and public audiences, including at major neuroscience conventions like the Society for Neuroscience.
Scholarly Publishing:
Co-authored peer-reviewed papers across various scientific domains,
effectively translating complex data insights into accessible language.
Leadership
Mentorship & Training:
Continuously mentored undergraduate students, researchers, and post-doctoral fellows,
enhancing team skills and fostering professional growth.
Guidance:
Provided leadership and guidance on professional conduct for newcomers.
Collaboration
Fostered Collaborative Environment:
Worked closely with a multidisciplinary team and contributed to experimental designs
that informed broader research objectives.
Spearheaded Multidisciplinary Initiatives:
coordinated cross-disciplinary projects to meet shared research goals.
SELECTED PROJECTS
Dynamic Group Matching Analysis with PySimpleGUI
Developed a PySimpleGUI desktop application to analyze and optimize group assignments
from Excel data, preserving cage mate pairing.
Evaluated all possible group combinations, calculating metrics such as means,
absolute differences, and the smallest mean difference between groups.
Automated data export to Excel and visualized results using Matplotlib,
producing line plots that highlight optimal group assignments and minimal variance.
Delivered actionable insights to improve decision-making in experimental setups
through comprehensive analysis and visualization.
Dynamic Group Matching Analysis with PySimpleGUI
Developed a dynamic web application using the Tomorrow.io API to provide real-time weather
insights tailored for golfers.
Enabled users to customize "golfable" parameters, including minimum temperature,
maximum wind speed, and precipitation limits.
Designed a dashboard to display metrics such as temperature differences, wind variance,
and precipitation likelihood, along with total golfable hours.
Created interactive visualizations using Matplotlib,
highlighting optimal golfing windows throughout the day and the next four days.
Delivered an intuitive, data-driven solution to inform ideal golfing conditions,
enhancing planning and decision-making for users.
Automated Wheel Running Data Analysis Tool
Developed a Python-based application with a user-friendly interface to
analyze millions of data points from running wheel experiments logged in Excel files.
Automated identification of valid running bouts (≥3 revolutions/min) and
categorized activity by light and dark phases, significantly reducing manual processing time.
Consolidated raw data into a summary sheet with detailed metrics,
ensuring efficient data organization and accuracy.
Enabled users to generate phase-specific bar graph visualizations,
providing actionable insights into exercise behavior and activity patterns.
Delivered a robust, scalable solution that streamlined workflow,
accomplishing tasks in seconds that previously required hours.