Thomas J. Stoll, Ph.D.
Postdoctoral Research Fellow · Maddox Lab, University of Michigan
Bridging computational auditory neuroscience, human EEG, and machine learning to predict and understand how the brain responds to sound. Focused on translating predictive neural models into clinical diagnostics, neural interfaces, and next-generation hearables.
Core Research & Engineering Projects
Selected Publications
Full Scholar ProfileCore Technical Competencies
Machine Learning & DSP
PyTorch, Python (NumPy, SciPy), Digital Signal Processing (DSP), Deconvolution & Temporal Response Functions (TRF), Neural Regression, Digital Filtering, High-Performance Computing (Linux / Slurm).
Neurotech & Biosignals
Electroencephalography (EEG), Electrocochleography (ECochG), Auditory Brainstem Response (ABR / pABR), Auditory Evoked Potentials, Psychophysics, Continuous Speech Tracking & Decoding.
Hardware & Prototyping
Electrode Fabrication, Rapid Prototyping (CAD & 3D Printing), Custom Sensor Design, Custom Sensor & Tool Fabrication, Soldering & Bench Electronics, Audio Equipment Calibration.