November 2025
Building Lightweight & Explainable ML
Lessons from AChorDS-LVQ: interpretable text classification that runs without GPUs.
Read Article →Mohammad Mohammadi
Data Scientist / ML Engineer
PhD Data Scientist with 3+ years of experience developing AI solutions across legal, medical, and
cultural heritage domains.
Currently working on the HAICO project at Tilburg University, applying AI to national library data.
Discover how we can peek inside the "black box" of deep learning models to build trust in medical
diagnosis.Featured Insight
Latest Article
Explainable AI in Healthcare
Work Experience
Data Scientist
Tilburg University
09/2025 - Present
Working on the HAICO project to analyze cultural heritage data from the National Library (KB).
- Developing AI models to enrich and explore large-scale historical datasets.
- Collaborating with domain experts to unlock insights from digital heritage collections.
Data Scientist
University of Groningen
10/2022 - 08/2025
Collaborating with legal experts and biomedical engineers to develop and apply AI solutions in NLP and computer vision.
- Lead interdisciplinary teams collaborating with legal experts and biomedical engineers.
- Developed and deployed scalable ML pipelines for image and text classification using PyTorch, Docker, DVC, and Flask.
- Published high-quality research in TPAMI, Neurocomputing, and others.
- Built data pipelines using Airflow and BigQuery to automate ETL processes.
Lecturer
University of Groningen
10/2021 - 09/2022
Taught undergraduate and graduate courses on data science and machine learning.
PhD Researcher
University of Groningen
07/2017 - 09/2021
Developed novel algorithms for the detection and characterization of astronomical structures as part of the SUNDIAL project.
Data Scientist Intern
Webfleet Solutions
06/2019 - 07/2021
Developed predictive models leveraging telematics data in a cross-functional agile team.
Highlighted Projects
Brain Tumor Classification
A Flask-based web application for diagnosing brain tumors using MRI scans with 99.7% accuracy and explainability features.
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Legal Case Classification
Predicting legal case categories (housing vs. eviction) using NLP, featuring model interpretability for legal professionals.
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Astronomical Analysis
Novel algorithms for detection and characterization of astronomical structures in large datasets.
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Latest Articles
November 10, 2023
Mining the Universe
Swarm-intelligence-based extraction and manifold crawling along the Large-Scale Structure.
Read Article →November 2025
Explainable AI in MRI Diagnosis
A practical story from building an interpretable MRI classification model.
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