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CV


PhD Student in Computer Science @ Rutgers University β€” researching safe, fair, and explainable large language models.

πŸ“ New Brunswick, NJ Β· βœ‰οΈ a.khorramrouz@rutgers.edu Β· 🌐 akhorramrouz.com Β· πŸŽ“ Google Scholar


πŸŽ“ Education

PhD, Computer Science

Rutgers University Β· New Brunswick, NJ Β· 2024 – Present

M.Sc., Data Science

Rochester Institute of Technology Β· Rochester, NY Β· 2022 – 2024


πŸ”¬ Research Interests

  • NLP & Large Language Models
  • Responsible AI: Safety, Fairness & Bias Mitigation
  • Explainable AI
  • Computational Social Science for AI Evaluation
  • Agentic AI & Multi-Agent Systems

πŸ“„ Publications & Preprints

Under Review

  • Moral Combat: Exploiting Moral Foundations Theory to Jailbreak LLMs
    Adel Khorramrouz, Y. Wang, S. Levy
    NAACL 2027 Submitted

  • Where Guardrails Blur: Generating Domain-Specific Boundary Cases
    Adel Khorramrouz, K. Foley, S. Hamidian
    NAACL 2027 Submitted

2026

2024

2023

2021 – 2022


πŸ’Ό Work Experience

Machine Learning Engineer (Returning Intern) β€” Comcast

πŸ“… May 2026 – Sep 2026

Content Discovery Team Β· Synthetic data generation for LLM guardrails Β· Manager: Sardar Hamidian

Machine Learning Research Intern β€” Comcast

πŸ“… May 2025 – May 2026

Content Discovery Team Β· Guardrail development and recommendation-system safety Β· Mentor: Kevin Foley

Research Intern β€” BioInfo Lab

πŸ“… Summer 2024

Protein Language Models Β· Fine-tuning with PEFT Β· LoRA Β· QLoRA Β· Mixture of Experts

Research Intern β€” Social Insight Lab

πŸ“… Summer 2023

Multilingual LLMs Β· Instruction Tuning Β· Fairness Β· Safety & Guardrails

Data Scientist β€” Apply 4 Fund

πŸ“… Summer 2022

Social Media Web Scraping Β· Web Application Development Β· Data Analytics

Founder β€” PolyEkip

πŸ“… Jun 2019 – Mar 2020

Developed an AI-based friend-finding algorithm based on psychological personality assessment


πŸ§ͺ Research Experience


πŸ›οΈ Academic Service

  • Reviewer β€” ACL, COLM, COLING
  • Volunteer β€” ACL 2023
  • Judge β€” Genius Olympiad, with participants representing 45+ countries

πŸ“° Media Coverage

  • WIRED featured our research on bias auditing in large language models, emphasizing its socio-political implications.
  • Montreal AI Ethics Institute highlighted our work on bias auditing of LLMs.
  • RIT News featured our research findings on bias auditing in large language models.

πŸ† Honors & Awards

  • 2022 Fully funded scholarship β€” $120,000 USD (2022 – 2024)
  • 2017 Ranked 109th among 148K contenders (top 0.07%) in the national university entrance examination
  • 2010 – 2017 Admitted to the National Organization for Development of Exceptional Talents

πŸ‘¨β€πŸ« Teaching Experience

  • Fall 2025 Machine Learning Principles β€” Teaching Assistant Β· Prof. Sharon Levy
  • Spring 2025 Natural Language Processing β€” Teaching Assistant Β· Prof. Sharon Levy
  • Fall 2024 Introduction to Data Science β€” Teaching Assistant Β· Prof. Gunawardena
  • Spring 2022 Computer Vision Project β€” Leading Teaching Assistant Β· Prof. S. Seyedin
  • Spring 2022 Introduction to Artificial Intelligence β€” Leading Teaching Assistant Β· Prof. M. Ahmadi
  • Spring 2022 Introduction to Computational Social Science β€” Workshop Lecturer
  • Fall 2021 & Spring 2022 Machine Learning β€” Teaching Assistant Β· Prof. S. Seyedin
  • Fall 2021 Statistical Learning Theory β€” Teaching Assistant Β· Prof. V. Pourahmadi

▢️ Online Education (YouTube) β€” Machine Learning Concepts and Coding Series Β· Python and OOP Tutorial Series


πŸ› οΈ Skills

  • Programming β€” Python (Advanced) Β· Java Β· C++ Β· MATLAB
  • Machine Learning β€” PyTorch Β· TensorFlow Β· HuggingFace Transformers Β· Scikit-learn Β· Keras
  • Data Processing β€” Pandas Β· NumPy Β· SciPy Β· BeautifulSoup
  • NLP β€” Prompt Engineering Β· LLM Fine-tuning (LoRA, QLoRA, MoE) Β· Instruction Tuning Β· Multilingual NLP
  • Generative AI β€” Large Language Models Β· Vision-Language Models
  • LLM Guardrails & Safety β€” Content Moderation Β· Harmful Content Detection Β· Guardrail Implementation & Evaluation
  • AI Ethics & Fairness β€” Bias Auditing Β· Ethical AI Frameworks Β· Trustworthy AI Evaluation
  • Explainable AI β€” Model Interpretability Β· Feature Importance Analysis Β· Explanation Generation
  • Soft Skills β€” Research Leadership Β· Problem Solving Β· Academic Writing Β· Public Speaking Β· Workshop Facilitation

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