About Me
I study how language technologies can be made more useful, fair, and human-centred, with a particular focus on education and young users.
My research sits at the intersection of Natural Language Processing and Human-Computer Interaction, with a strong emphasis on educational applications. I am particularly interested in evaluating large language models in educational settings, especially for young users, and in understanding how culture, difficulty, fairness, and human factors shape AI systems in practice.
I am also interested in NLP for social good, including biases and social norms for low-resource languages such as Farsi.
I received my Ph.D. in Information Technology Engineering from Politecnico di Milano, and I worked with Prof. Dirk Hovy at the MilaNLP Group (MilaNLP Lab), where I contribute to INTERGRATOR, a project studying demographic factors in language technologies and their implications for the future of conversational AI.y
Recent News
- Oct 2026: We present three papers at EMNLP 2026 in Budapest:
- The Role of Implicit and Explicit Demographic Signals in Large Language Model-based Student Assessment
- Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation
- SEAL: SocioEconomic Alignment in LLMs (NLP4PI Workshop)
- [October 2026]: I joined ETH Zurich as a Postdoctoral Researcher.
- Sep 2026: Our paper GeoDial: A Multimodal Conversational Tutoring Dataset for Geometry Problem-Solving with Visual Tutor Turns was accepted at NeurIPS 2026.
- July 2026: We present Incentives Of EdTech: A Systematic Review Of EduNLP Research at the BEA Workshop at ACL 2026 in San Diego.
- June 2026: Invited talk at Cambridge University for NLP Seminars.
- March 2026: Attending EACL 2026 in Rabat and presenting three papers.
- February 2026: Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models at WASSA, EACL 2026.
- January 2026: PATS: Personality-Aware Teaching Strategies with Large Language Model Tutors at EACL 2026.
- January 2026: Can Reasoning Help Large Language Models Capture Human Annotator Disagreement? at EACL 2026.
- November 2025: Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction at BabyLM, EMNLP 2025.
- November 2025: Biased Tales: Cultural and Topic Bias in Generating Children's Stories at EMNLP 2025.
- November 2025: Co-detect: Collaborative Discovery of Edge Cases in Text Classification at EMNLP 2025.
- September 2025: Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models on arXiv.
- July 2025: Measuring Gender Bias in Language Models in Farsi at GeBNLP, ACL 2025.
- July 2025: Large Language Models for Education: Understanding the Needs of Stakeholders, Current Capabilities and the Path Forward at BEA, ACL 2025.
- July 2025: Educators' Perceptions of Large Language Models as Tutors: Comparing Human and AI Tutors in a Blind Text-only Setting at BEA, ACL 2025.
- July 2025: Are Large Language Models for Education Reliable for All Languages? at BEA, ACL 2025.
- April 2025: Can I Introduce My Boyfriend to My Grandmother? Evaluating Large Language Models' Capabilities on Iranian Social Norm Classification at NAACL 2025.
- April 2025: Invited talk at Universita della Svizzera italiana (USI) on Child-Centred AI in Education.
- November 2024 to February 2025: Visiting researcher at ETH Zurich, Language, Reasoning and Education Lab.
Selected Projects
KidAlign AI
Survey-based research on how children use AI across learning, creativity, social interaction, and emotional support, bringing together the perspectives of children, parents, and educators to identify safety gaps and design needs.
View ProjectPATS
Personality-Aware Teaching Strategies with Large Language Model Tutors, grounded in learning science and LLM-based evaluation of tutoring strategies.
View Project
Biased Tales
A dataset for analyzing how biases influence protagonists' attributes and story elements in LLM-generated stories for children.
View Project
LegalBot
A collaboration between Politecnico di Milano and Tribunale di Milano aimed at improving access to legal information through a conversational interface.
View Project
TalkyTutor
An adaptive educational chatbot built with the aCHAT framework so teachers and other non-technical users can customize content and conversational learning flows.
Publications
Please find all publications on my Google Scholar.
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Datasets
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PATS — Personality-aware teaching dialogues at three difficulty levels (stories & images).
Dataset
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Biased Tales — Cultural and topic bias in LLM-generated children's stories.
Dataset
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Farsi Subjective Tasks — Survey of 110 papers on sentiment, emotion, and toxicity detection in Farsi.
Dataset
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GBFA — Farsi translations of ISEAR, BBQ, and HONEST for gender bias evaluation in Farsi LMs.
Dataset
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ISN — Iranian Social Norms: 1,699 bilingual (Farsi/English) samples labelled with social norms.
Dataset