Developing electronic interfaces for sensing, stimulating, and understanding biological systems.

Bioelectronics
Sensors & biomedical systems
Embedded Hardware
PCB design & instrumentation
Computational Biology
Sequencing & epigenetics
Prototyping
CAD · fabrication · testing
Three projects spanning laboratory instrumentation, computational biology, and physiological sensing — from concept through working hardware.
A consistent process for moving from an open problem to working, tested hardware.
Understand the biological, technical, or clinical problem.
Develop system architecture, electronics, and mechanical components.
Prototype circuits, firmware, PCBs, and physical systems.
Characterize signals, hardware behavior, and system performance.
Refine the system using experimental results.
Understand the biological, technical, or clinical problem.
Develop system architecture, electronics, and mechanical components.
Prototype circuits, firmware, PCBs, and physical systems.
Characterize signals, hardware behavior, and system performance.
Refine the system using experimental results.
A structured process for turning scientific questions into measurable experiments, interpretable data, and engineering insight.
What do we need to understand?
Identify the biological phenomenon, engineering limitation, or unanswered question worth investigating.
What is already known?
Review existing methods, prior work, and open gaps to see where a better approach is possible.
What should happen?
Define measurable variables, expected behavior, and criteria for evaluating the idea.
How can we measure it?
Design the instrumentation, protocol, and data-acquisition approach needed to test the idea.
What does the evidence show?
Process signals and results, quantify performance, and determine whether the data supports the hypothesis.
What should we test next?
Use the results to improve the experiment and shape the next question.
What do we need to understand?
Identify the biological phenomenon, engineering limitation, or unanswered question worth investigating.
What is already known?
Review existing methods, prior work, and open gaps to see where a better approach is possible.
What should happen?
Define measurable variables, expected behavior, and criteria for evaluating the idea.
How can we measure it?
Design the instrumentation, protocol, and data-acquisition approach needed to test the idea.
What does the evidence show?
Process signals and results, quantify performance, and determine whether the data supports the hypothesis.
What should we test next?
Use the results to improve the experiment and shape the next question.
Tools and techniques I use across engineering, research, and software.
Python · MATLAB · C++ · JavaScript/TypeScript · SQL
Arduino · Microcontroller Programming · Sensor Integration · PCB Basics
Oscilloscope · Bench Power Supply · Multimeter · Function Generator · Logic Analyzer
Genomic Data Analysis · Statistical Modeling · R · Data Visualization
Microfluidics · PCR · Cell Culture · Assay Development
SolidWorks · AutoCAD · Git/GitHub · MS Office/Excel

I'm Regina Ruiz, a bioengineer focused on building technologies that connect electronics with biological systems. My work ranges from custom laboratory instrumentation and embedded hardware to sequencing workflows and computational biology.
I'm especially interested in bioelectronics, physiological sensing, biomedical devices, and engineering tools that transform biological signals into useful information.
More about meOpen to conversations about biomedical devices, embedded systems, research instrumentation, bioelectronics, and biological sensing.