Gregg Eschelmuller

PhD Candidate in Neuromechanics | Researcher & Engineer

Tech Resume

My experience structured for a tech, neurotech, or R&D role. Download PDF Version

Technical Toolkit

Languages

Python, MATLAB

Data Science & ML

Pandas, NumPy, SciPy, Scikit-learn, PyTorch, Statsmodels

Hardware & Neuro

NI-DAQmx, PsychoPy, Biomechanical/EMG Signal Processing, Spike2

Tools

Git, GitHub, Jupyter

Pillar Projects

My core portfolio pieces, translating my PhD research into industry-ready applications.

Pillar 1: Real-Time Hardware Platform

A "human-in-the-loop" experimental platform built in Python. This application integrates NI-DAQ hardware (for data acquisition), PsychoPy (for visual stimulus), and real-time signal processing (for online feedback) into a robust, event-driven system.

View on GitHub

Pillar 2: Bayesian Model of Proprioception

A computational model (built with PyMC/Statsmodels) that translates my core PhD research. It models sensory illusions as a rational Bayesian cue combination problem, successfully predicting human motor errors under noisy sensory feedback.

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Pillar 3: State-Space & Cue Combination Model

My final project for an advanced Bayesian modeling course. This project uses a state-space model to explain proprioceptive drift through optimal cue combination and sensorimotor learning, demonstrating a grasp of core ML theory.

View on GitHub

Education & Specialized Training

Teaching & Leadership Experience

Selected Publications

For a full list, please see my Academic CV.