trajectory-judge: What Outcome-Only LLM Judges Miss on Agent Trajectories
NeurIPS 2026 Workshop “Who Verifies the Agents?” · accepted
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.
Citations: Google Scholar · updated October 2026
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.
Each role and its results, applied ML projects, and open-source libraries for auditing LLM judges.
Explainability, moral alignment and LLM evaluation: the research line behind my PhD thesis.
A course and a demo that run in the browser, field notes on production LLM systems, and open guides for people studying AI.
AcademicTransfer, Utrecht
Utrecht University School of Economics, FIRMBACKBONE
Built the fbb-sustainability-analysis-cli tool: keyword extraction and sustainability scoring of company websites.
SnowaTec (Innovation Center), Entekhab Electronic, Tehran
ETL warehouse (+16% data accessibility), KPI & satisfaction index (+2%), ML customer segmentation (+7.5% marketing impact).
Bdood.bikes (shared bicycle system), Tehran
Dynamic pricing and usage prediction (+5% revenue), fleet intelligence (−8% maintenance costs), retention analyses (+4.5%).
Bdood.bikes, Tehran
Predictive maintenance and battery-health algorithms (−3.8% downtime); GIS models for high-risk riders (+3% safety, +5% UX).
Utrecht University · thesis Let Me Explain!
University of Tehran · thesis on dynamic pricing with reinforcement learning
Isfahan University of Technology, Golpayegan College
NLP models whose decisions domain experts can inspect and question, through post-hoc methods and token-level explanations.
How LLMs represent cultural variation in moral judgments and social norms, and how to evaluate their alignment across cultures.
Interpretable chain-of-thought and LLM-as-judge evaluation, to tell when a model’s predictions and explanations can be trusted.
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
NeurIPS 2026 Workshop “Who Verifies the Agents?” · accepted
INLG 2026, Utrecht · long paper, accepted
*SEM 2026 (ACL), pp. 497–515
Computational Linguistics in the Netherlands Journal, Vol. 15 (2026), pp. 59–77
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
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
Nine MSc students co-supervised at Utrecht University (2024–2026), with Dr. Robert A. Bagheri and Dr. Anastasia Giachanou.
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.
I’m based in Utrecht, The Netherlands, and email is the fastest way to reach me for research collaboration, supervision, speaking or industry opportunities.