CV

Academic and professional CV of Mohammad Aghajani Asl, an AI and NLP researcher working on trustworthy AI, agentic RAG, question answering, Persian NLP, and large-scale data infrastructure.

My curriculum vitae presents my research background, publications, engineering experience, education, technical expertise, and selected AI and NLP projects.

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Research Profile

I am an AI and NLP researcher with a background in complex-systems physics and experience in designing evidence-grounded language-model systems, agentic retrieval-augmented generation, Persian question answering, and large-scale social-data infrastructure.

My work connects fundamental research with end-to-end engineering. I have contributed to research datasets, retrieval systems, multi-agent workflows, production NLP services, distributed data pipelines, and analytical applications.

Current Research Directions

My primary research interests include:

  • trustworthy and faithful artificial intelligence,
  • agentic retrieval-augmented generation,
  • automated fact-checking and evidence verification,
  • multi-hop reasoning and question answering,
  • Persian and multilingual NLP,
  • human-in-the-loop AI systems,
  • and AI for scientific discovery.

Selected Research and Engineering Strengths

Trustworthy Language-Model Systems

Designing systems that explicitly evaluate evidence sufficiency, identify missing information, preserve source traceability, and reduce unsupported generation.

Retrieval-Augmented Generation

Developing hybrid retrieval, iterative refinement, evidence filtering, query decomposition, and citation-grounded generation pipelines.

Persian NLP

Constructing Persian datasets and training models for question answering, sentiment analysis, topic classification, geographic inference, and social-media analytics.

Data and ML Infrastructure

Building asynchronous collection systems, Elasticsearch-backed analytical platforms, model-serving APIs, data-processing pipelines, and production monitoring workflows.

Human-in-the-loop AI

Designing systems in which users review, revise, approve, or reject intermediate outputs before the workflow advances.

Education

M.Sc. in Physics — Complex Systems

Sharif University of Technology
2021–2023

  • GPA: 18.71/20
  • Thesis grade: 19/20
  • Research focused on mathematical consistency and conceptual foundations in a quantum theory of consciousness.

B.Sc. in Physics

Sharif University of Technology
2016–2021

  • GPA: 17.30/20
  • GPA during the final two years: 18.44/20
  • Final project focused on foundational principles of modern physics and the Principle of Least Action.

Current Objective

I am seeking PhD opportunities in:

  • Natural Language Processing,
  • Trustworthy AI,
  • Agentic AI,
  • Retrieval-Augmented Generation,
  • Automated Fact-Checking,
  • Question Answering,
  • and AI for Science.

I am particularly interested in research environments that combine rigorous methodological work with the development and evaluation of practical AI systems.

Contact

The fastest way to reach me is by email:

aghajani76m@gmail.com

I welcome inquiries concerning PhD opportunities, research collaborations, and applied AI research.