Mercedes Gonzalez

Résumé

Education

Bachelor of Science in Mechanical Engineering

2015-2019
Missouri University of Science & Technology

Master of Science in Mechanical Engineering

2019-2023
Georgia Institute of Technology

PhD Candidate in Bioengineering

2019-present
Georgia Institute of Technology

Publications

⪼ Gonzalez, M. M., Lewallen, C. F., Yip, M. C., & Forest, C. R. (2021). Machine Learning-Based Pipette Positional Correction for Automatic Patch Clamp In Vitro. ENeuro, 8 (August), 1–8. doi: https://doi.org/10.1523/ENEURO.0051-21.2021 [PDF]

⪼ Yip, M.C., Gonzalez, M.M., Valenta, C.R., Rowan, M.J.M., Forest, C.R. Deep learning-based real-time detection of neurons in brain slices for in vitro physiology. Sci Rep 11, 6065 (2021). https://doi.org/10.1038/s41598-021-85695-4 [PDF]

⪼ Landry, C. R., Yip, M. C., Kolb, I., Stoy, W. M., Gonzalez, M. M. and Forest, C. R. (2021). Method for Rapid Enzymatic Cleaning for Reuse of Patch Clamp Pipettes: Increasing Throughput by Eliminating Manual Pipette Replacement between Patch Clamp Attempts. Bio-protocol 11(14): e4085. DOI: 10.21769/BioProtoc.4085. [PDF]

Experience

Graduate Research Assistant, Georgia Institute of Technology

Deep Learning for Automated Patch Clamp

• Innovated a deep-learning method to correct pipette positioning errors in automated in vitro patch clamp, resulting in a remarkable 50% improvement in success rates.
• Developed a cutting-edge deep-learning algorithm for real time automated cell detection in acute slice during in vitro patch clamp experiments, streamlining the process and enhancing efficiency.

PV Interneurons in Alzheimer’s Disease

• Conducted stereotaxic surgery and brain slice preparation for slice patch clamp experiments, demonstrating proficiency in precise and meticulous techniques essential for successful neurophysiological research.
• Quantified the intrinsic properties of Parvalbumin interneurons within an amyloid precursor protein mouse model of Alzheimer’s disease, contributing to a deeper understanding of the neurobiological mechanisms underlying the disease.

Automated Real Time Data Analysis

• Designed and implemented a Python-based graphical user interface (GUI) for real-time analysis of patch clamp data, providing researchers with a user-friendly tool for efficient data interpretation.

Graduate Teaching Assistant, Georgia Institute of Technology

Create-X Capstone Design – Mentor

• Mentored interdisciplinary capstone teams, guiding them through the process of problem discovery, solution design, and prototyping, fostering their critical thinking and problem-solving skills.
• Provided valuable feedback and constructive criticism on ideas, presentations, and design choices, helping students refine their work and enhance the quality of their projects.

Course Coordinator

• Efficiently managed the administrative aspects of the class, coordinating regular presentations and organizing weekly meetings with mentors from diverse departments, ensuring smooth communication and collaboration among all stakeholders.
• Streamlined the assignment collection process by implementing automation using AppScript, effectively reducing manual tasks and improving efficiency in organizing and managing student assignments.

Senior Engineering Consultant, Rouleau and Associates, LLC

Finite Element Analyses for Medical Devices

• Developed robust Finite Element Analysis (FEA) models to simulate the effects of varying loading conditions on medical device stress and displacement, enabling comprehensive analysis and optimization of design performance.
• Skillfully conveyed and summarized key insights from simulation results during weekly meetings with company executives, facilitating informed decision-making and ensuring alignment with project objectives.
• Authored FDA protocols and reports to document and validate simulation results, ensuring compliance with regulatory requirements and providing a comprehensive record of the analysis process.

Undergraduate Research Assistant, Missouri University of Science & Technology

Incremental Sheet Forming

• Generated complex 3D models and utilized Computer-Aided Manufacturing (CAM) software to generate tool paths, determining limits and accuracy of forming process.
• Developed a user-friendly graphical interface to convert tool paths into RAPID code, facilitating communication with an ABB robot and enabling post-processing of forming data.
• Analyzed digital image correlation data to assess thickness distribution and geometric error of intricate geometric forms, informing adjustments to tool paths and enhancing forming accuracy.

Engineering Intern, Pratt & Whitney

Human Machine Interface

• Orchestrated the design, programming, and integration of a cutting-edge Human Machine Interface (HMI) system, automating adhesive deposition on fan blade components.
• Conducted comprehensive testing and performed data analysis to quantify manufacturing process variations in fan blade priming methods.
• Collaborated closely with cross-functional teams to successfully implement an air-tight pass-through door, while meticulously documenting the enhanced procedures.

Engineering Co-op, Watlow

Computer Aided Design & Experimental Design

• Produced precise models and mechanical drawings for a Quartz vacuum chamber as a key member of the Advanced Thermal Systems Pedestal team.
• Devised and implemented an extensive experimental test plan, successfully evaluating and validating the performance of heating element designs for a full-scale wafer pedestal.
• Developed a web application for F4T controller communication and data visualization, facilitating the remote monitoring of heater testing and enhancing operational efficiency.