AM · Computational Neurotechnology

Turning signal, image & video into clinical insight.

I'm a computational researcher who analyzes sensor, imaging, and video data across clinical, animal, and computational studies — and, unusually, I also build the microcontroller-based instruments that capture it. I understand the full chain from sensor to signal to result. My aim is to move these methods toward clinical digital biomarkers and open-source neurotechnology.

Open to visiting research positions & research collaborations
1.0 About

An engineer's approach to neuroscience.

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"I think about a neuroscience experiment the way I think about any instrument: the quality of the science is bounded by the quality of the tools that record it. So I build the tools first — then use them to ask the questions I care about."

I came to neuroscience through biomedical engineering, and that order still shapes how I work. Before I ask what a dataset means, I ask how it was recorded, what noise it carries, and whether the instrument that produced it can be trusted. My doctoral work is the clearest expression of that: a driving-inspired paradigm in which I built the entire measurement stack — sensor to pose-estimation to statistics — to quantify a learned motor skill and its degradation under amyloid pathology.

2.0 Research

What I work on.

Full research statement

Signal, Image & Video Analysis

Turning raw data into measures: tactile/contact time series, markerless kinematics from video (DeepLabCut), and medical-image analysis — across clinical, animal, and computational studies.

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Reproducible Pipelines & Statistics

Python pipelines and mixed-effects modeling built so another researcher can rerun the analysis and reach the same result — with explicit quality control at every step.

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Instrumentation & Sensing / differentiator

The edge most analysts don't have: I also build the acquisition hardware — Arduino, tactile/contact sensing, embedded prototyping — so I control the data from the sensor up.

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Toward Clinical Digital Biomarkers

Where I'm heading: moving these computational methods toward human clinical application — digital biomarkers and open, shareable analysis tools.

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3.0 Selected Projects

Systems I've built, end to end.

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Rehabilitation Hardware

Wrist CPM Robot + Joystick Serious Game

An Arduino and stepper-motor continuous-passive-motion wrist device, linked to a Processing 3 joystick that drives a simple 2D game — an early, human-facing rehabilitation system.

ArduinoProcessing 3Rehab
4.0 Toolkit

The instruments I build with.

Python Mixed-Effects Modeling DeepLabCut Video & Image Processing Time-Series Analysis Reproducible Pipelines Arduino / Microcontrollers Tactile / Contact Sensors Processing 3 3D Slicer & Mimics Git & Open Source C++ (basic)
5.0 Publications

Selected publications.

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2026

Effectiveness of AI and rule-based conversational agents for depression, anxiety and stress: a meta-analysis

Mokhtari Masoumi Alamdarloo, S., Mirzakhani, A., Azhdarloo, M., Haghani-Samani, E., Nazari, A. — npj Digital Medicine.

2026

Effectiveness of group-based art interventions for late-life depression: a systematic review and meta-analysis of RCTs

Azhdarloo, M., Ataei, R., Mokhtari Masoumi Alamdarloo, S., Mirzakhani, A., Nazari, A. — BMC Medicine, 24:188.

Let's talk

Looking for a visiting research position for 2026.

I'm seeking a visiting research position, and open to collaborations with labs working on biosignal and movement-data analysis, digital biomarkers, computational neurotechnology, or open-source scientific tools.

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