Hadi Mohammadi

I build production LLM and ranking systems, and research explainable NLP and LLM evaluation.

Senior AI & Data Science Expert - R&D Specialist at AcademicTransfer and PhD in Explainable NLP from Utrecht University.

Hadi Mohammadi presenting research on moral alignment in LLMs at the IOPS Winter Conference 2025
Best Oral Presentation, IOPS Winter Conference 2025 →
167
Citations
21
Publications
6+
Years in ML
€40K+
Research grants

Citations: Google Scholar · updated October 2026

01About

At a glance

At AcademicTransfer I build the LLM matching and ranking behind the recruitment platform of 22 Dutch research universities and university medical centres. It reads 10,000+ applications a month. It has cut time-to-hire by 20% and improved candidate–job matching by 17%.

My PhD at Utrecht University asked why a model gives the answer it does and whether that explanation can be trusted. Its papers appeared at *SEM 2026, in the CLIN Journal and Applied Sciences, and at an ACL 2025 workshop. This autumn adds a long paper at INLG 2026 and my first solo paper at a NeurIPS 2026 workshop.

Hiring

Industry ML & LLM systems

Each role and its results, applied ML projects, and open-source libraries for auditing LLM judges.

Research

Explainable & culturally fair NLP

Explainability, moral alignment and LLM evaluation: the research line behind my PhD thesis.

Learning

Explainable AI, hands-on

A course and a demo that run in the browser, field notes on production LLM systems, and open guides for people studying AI.

02Experience

Experience & education

Professional experience
  • Dec 2025 – now

    Senior AI & Data Science Expert - R&D Specialist

    AcademicTransfer, Utrecht

    • Leads the company’s 2026 WBSO R&D programme as R&D Specialist since Mar 2026: an MCP-based academic query engine and an explainable CV matching engine with recruiters in the loop.
    • Technical lead of the AI layer and applicant-tracking system.
  • Jan 2024 – Dec 2025

    AI & Data Science Expert

    AcademicTransfer, Utrecht CV Priority Sorter (active learning + LLMs): manual effort halved
    • Deployed transformer models on Azure ML (MLflow, Docker, CI/CD); evaluated ranking with A/B tests, uplift analysis, and bandit simulations.
  • Feb 2024 – Mar 2025

    Researcher & NLP Developer

    Utrecht University School of Economics, FIRMBACKBONE

    Built the fbb-sustainability-analysis-cli tool: keyword extraction and sustainability scoring of company websites.

  • Dec 2021 – Jan 2023

    Senior Data Scientist, Customer Behavior

    SnowaTec (Innovation Center), Entekhab Electronic, Tehran

    ETL warehouse (+16% data accessibility), KPI & satisfaction index (+2%), ML customer segmentation (+7.5% marketing impact).

  • Apr – Oct 2020

    Head of Data Science & BI Team

    Bdood.bikes (shared bicycle system), Tehran

    Dynamic pricing and usage prediction (+5% revenue), fleet intelligence (−8% maintenance costs), retention analyses (+4.5%).

  • Jul 2019 – Apr 2020

    Data Scientist

    Bdood.bikes, Tehran

    Predictive maintenance and battery-health algorithms (−3.8% downtime); GIS models for high-risk riders (+3% safety, +5% UX).

Education
  • Feb 2023 – Oct 2025
    defended Sep 2026

    PhD, Explainable NLP

    Utrecht University · thesis Let Me Explain!

  • Sep 2018 – Apr 2021

    MSc Industrial Engineering: Macro Systems

    University of Tehran · thesis on dynamic pricing with reinforcement learning

  • Sep 2011 – Jul 2016

    BSc Mechanical Engineering

    Isfahan University of Technology, Golpayegan College

Training
  • Jun 2024Generative Modeling Summer School, TU Eindhoven
  • 2023Oxford Machine Learning Summer School (OxML 2023), ML x Finance & NLP
  • Aug 2022Explainable AI Summer School (XAISS), TU Delft, scholarship recipient
Core stack
  • Python · PyTorch
  • Hugging Face Transformers
  • LLM fine-tuning (LoRA, PEFT)
  • Preference optimization (DPO, GRPO)
  • LLM-as-judge evaluation
  • RAG · agents · MCP
  • Ranking & matching models
  • Azure ML · MLflow · Docker
  • A/B testing · uplift · bandits
  • SQL / PostgreSQL

Full experience, skills & training

03Research

What I work on

Explainable NLP

NLP models whose decisions domain experts can inspect and question, through post-hoc methods and token-level explanations.

Cultural fairness in LLMs

How LLMs represent cultural variation in moral judgments and social norms, and how to evaluate their alignment across cultures.

LLM evaluation

Interpretable chain-of-thought and LLM-as-judge evaluation, to tell when a model’s predictions and explanations can be trusted.

Human-AI annotation reliability

Whether LLM annotations can stand in for human ones: model outputs against human rationalizations, and demographic bias in annotation.

PhD thesis: Let Me Explain! Explainable NLP for Understanding Large Language Models

Themes, grants & talks

04Selected publications

Recent research

All 21 publications

05News

Recent news & updates

  • Oct 2026Invited talk at the HAI SIG Day of Utrecht University’s Human-centered AI focus area, in the NLP@U session: “From Explainable NLP to Human-Centered AI: Connecting research with practice”.
  • Sep 2026First solo-author paper accepted at the NeurIPS 2026 workshop “Who Verifies the Agents?”: “trajectory-judge: What Outcome-Only LLM Judges Miss on Agent Trajectories”. Paper
  • Sep 2026PhD defended at Utrecht University on 9 September 2026. About the thesis
  • Aug 2026Long paper accepted at INLG 2026 in Utrecht (19–21 October): “Chain-of-Thought Faithfulness Under GRPO and DPO Fine-Tuning”, with Dr. Anastasia Giachanou. INLG 2026
  • Dec 2025Best Oral Presentation Award at the IOPS Winter Conference 2025 for research on cultural moral alignment in LLMs. Event details
Earlier news, 2023–2025 (10)
  • Dec 2025€5,000 Applied Data Science grant for “Optimizing the CV Priority Sorter for Fair and Efficient Prioritization of Academic CVs”, with Dr. Robert A. Bagheri, Dr. Georg Krempl, and Jeroen Sparla.
  • Jul 2025€9,000 CUCo Spark Grant for “ReDOSE: Towards a more Circular Pharmaceutical Industry using AI”, an interdisciplinary collaboration across WUR, TU/e, and UMC Utrecht.
  • Jul 2025Paper accepted at ECAI 2025 (LUHME Workshop) on cross-cultural morality understanding with large language models.
  • Jun 2025€5,000 Applied Data Science grant for “Rule Extraction from Human Evaluation Using LLMs and Reinforcement Learning”, with Dr. Anastasia Giachanou and Dr. Shihan Wang.
  • Apr 2025Paper accepted at ACL 2025 (GeBNLP Workshop) on LLM reliability assessment and annotation reliability.
  • Jan 2025Selected for the LERU Doctoral Summer School on AI in Copenhagen, representing the Faculty of Social and Behavioural Sciences, Utrecht University.
  • Dec 2024€14,400 Enfield grant (European Lighthouse to Manifest Trustworthy and Green AI) for research on “User Perspectives on Explainable AI”.
  • Nov 2024Co-founded the NLP@U Young Scholar Network: a community for PhD students, postdocs, and early-career NLP researchers at Utrecht University and UMC Utrecht. YSN website
  • Nov 2024Communications Chair at BNAIC/BeNeLearn 2024, the Joint International Scientific Conferences on AI and Machine Learning at Utrecht University.
  • Dec 2023€7,500 Applied Data Science grant for “Assessing Reliability of Annotations in the Context of Model Predictions and Explanations”, with Dr. Pablo Mosteiro Romero, Dr. Anastasia Giachanou, and Prof. Dr. Massimo Poesio.

All news & updates

06Newsletters

In English and Persian

English · every other Saturday

Weekend Learning

One finding every two weeks on how LLM evaluation breaks: judges, benchmarks, calibration. Every number is recomputed from the data, and each issue ends with an exercise you can run in about an hour.

Issue 8 · 10 Oct 2026:
A ranker 0.036 better on labels loses on production’s clicks

Persian · every other Friday

یادگیری آخر هفته

Its Persian sister, for beginners: one basic idea from machine learning and language models, with lessons you can read, play with, run in plain Python or download for offline use.

Issue 1 · 2 Oct 2026:
مدل زبانی فقط کلمه‌ی بعدی را حدس می‌زند

07Teaching

Teaching & supervision

Master’s thesis co-supervision

Nine MSc students co-supervised at Utrecht University (2024–2026), with Dr. Robert A. Bagheri and Dr. Anastasia Giachanou.

Students by cohort
  • 2024 Mijntje Meijer, Evi Papadopoulou, Lourenço Santos Moitinho de Almeida (graduated)
  • 2025 Hein Brouwer, Tamás Kozák, Mohamad Jouhar
  • 2026 Aliyah Vos, Geanina Verestiuc, Thomas Rietman

I also built Opening the Black Box, a free, self-paced course on explainable AI with thirteen hands-on labs. The instructor-led five-day version runs as a summer school for universities and companies.

Teaching experience
  • Dec 2023Practical Assistant, Transformers Workshop: UMC Utrecht.
  • Sep–Oct 2023Computer Lab Assistant: MSc Applied Data Science, Utrecht University.
  • Aug–Sep 2021Lead Teaching Assistant, Deep Learning: Neuromatch Academy.

Full teaching record

10Contact

Get in touch

I’m based in Utrecht, The Netherlands, and email is the fastest way to reach me for research collaboration, supervision, speaking or industry opportunities.

Download CV (PDF)

Portrait of Hadi Mohammadi

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