I want language technologies to be
for the people who use them, in every language they speak.

(Go ahead, unmask it. My thesis was about what models put in that blank.)

I am a Lecturer in Computer Science and Engineering at BRAC University, where I also completed my B.Sc. with university's Highest Distinction (GPA: 4.0/4.0). My research sits at the intersection of natural language processing (NLP) and fairness: I study how language models absorb, express, and transfer bias, and how we can measure and mitigate it.

My undergraduate thesis, supervised by Dr. Farig Sadeque, introduced MALoR, a masked-token metric for quantifying gender bias in encoder models, and showed that counterfactual data augmentation can reduce measured bias by up to 95%.

I am looking for PhD opportunities for Spring 2027 / Fall 2027 in trustworthy and fair NLP, human centered NLP, privacy and security in LLMs, and multilingual, low-resource language technology. If our interests overlap, I would be glad to hear from you.

News

  • Two papers submitted to ARR (targeting EMNLP 2026): one on gender bias transfer in LLM-assisted student writing, one on benchmarking Bengali dialectal bias.
  • Our paper on RAG techniques for Bengali standard-to-dialect translation was published at the BLP Workshop, IJCNLP–AACL 2025.
  • My undergraduate thesis work on gender bias in encoder models is now on arXiv (2511.00519).

Publications & Preprints

Contaminated Collaboration: Measuring Gender Bias Transfer in LLM-Assisted Student Writing2026

Ariyan Hossain, K. K. Rabbi, Farig Sadeque, S. M. Taiabul Haque

under review · ARR targeting EMNLP 2026

Conducted the first controlled study (N=153) on gender stereotype propagation in LLM-assisted career essay writing. Demonstrated bias transfer using a fine-tuned agency classifier and a novel Stereotype Congruence Rate (SCR) metric.

Benchmarking Bengali Dialectal Bias: A Multi-Stage Framework Integrating RAG-Based Translation and Human-Augmented RLAIF2026

K. M. J. Sami, D. Sumit, Ariyan Hossain, Farig Sadeque

under review · ARR targeting EMNLP 2026

Created a benchmark evaluating 19 LLMs on 4,000 gold-labeled questions across nine Bengali dialects using RAG-based translation. Proposed an RLAIF bias evaluation framework with Chain-of-Thought rubrics and introduced the Cultural Bias Score (CBS) metric for safety-critical assessment.

A Comparative Analysis of RAG Techniques for Bengali Standard-to-Dialect Machine Translation Using LLMs2025

K. M. J. Sami, D. Sumit, Ariyan Hossain, Farig Sadeque

published BLP Workshop @ IJCNLP–AACL 2025, ACL Anthology

Designed two RAG pipelines for standard-to-dialectal Bengali translation across six dialects using in-context learning. Improved translation accuracy by over 25% with sentence-pair RAG, enabling Llama-3.1-8B to outperform GPT-OSS-120B..

Exploring and Mitigating Gender Bias in Encoder-Based Transformer Models2025

Ariyan Hossain, K. M. A. Hannan, R. Haque, N. T. Rafa, H. Musarrat, S. A. Dipu, Farig Sadeque

preprint Undergraduate Thesis, BRAC University

Proposed MALoR, a metric for quantifying gender bias in encoder-based models. Built a gender-balanced pretraining dataset with over 19,000 counterfactual sentence pairs using CDA, reducing gender bias by up to 95%.

Identifying Framing Bias in Online Climate Change News Articles2024 – 2025

Ariyan Hossain, with Dr. Muhammad Nur Yanhaona

Research Project, BRAC University

Built a climate change news dataset using expert annotation and GPT-4 synthetic augmentation for multi-class framing classification. Fine-tuned Longformer, BigBird, BERT, and LLaMA 3.1, applying QLoRA for memory-efficient PEFT.

Work Experience

2024 – present

Lecturer, Dept. of CSE, BRAC University

Dhaka, Bangladesh

I teach CSE220 (Data Structures), CSE221 (Algorithms), and CSE440 (Natural Language Processing) to 300+ undergraduate students each semester.

Other services

  • Thesis Supervisor: Co-supervised and supervised 50+ students working on NLP undergraduate theses
  • Pre-Thesis I Panel Judge: Reviewed and provided feedback on initial thesis drafts of undergraduate teams
  • Final Thesis Defense Panel Judge: Reviewed and evaluated completed undergraduate research works
  • Course Advisor: Advised students on and approved undergraduate courses, and created course routines
2023 – 2024

Research Assistant, Dept. of CSE, BRAC University

Dhaka, Bangladesh

Full-time RA under Dr. Muhammad Nur Yanhaona on news framing classification with ML and NLP.

2022 – 2023

Student Tutor (ST), Dept. of CSE, BRAC University

Dhaka, Bangladesh

Graded, lectured occasionally, and held up to 15 hours/week of student consultations.

Education

2020 – 2023

B.Sc. in Computer Science and Engineering, BRAC University

Dhaka, Bangladesh

Grade: GPA 4.0/4.0 (Highest Distinction)
Thesis: Exploring and Mitigating Gender Bias in Transformer-based Language Models
Relevant Coursework: NLP, Neural Networks, Artificial Intelligence, Linear Algebra, Calculus

2017 – 2019

Cambridge O & A Levels, Sunnydale

Dhaka, Bangladesh

Award: Outstanding Cambridge Learner Award for World's Highest Mark (100%) in AS Level Mathematics

Selected Projects

More on GitHub →

Talks

May 2025

Talking to Machines: The Power of Natural Language Processing

IEEE Robotics and Automation Society, BRAC University

Introduced NLP from how machines understand language to recent technologies including LLMs to 140+ undergraduate students [slides]

Awards & Achievements

  • BRAC University Highest Distinction: Awarded Highest Distinction for achieving a CGPA of 3.80 or higher. Graduated with perfect 4.0/4.0 GPA.2023
  • BRAC University 100% Performance-Based Scholarship: Received 100% scholarship for maintaining CGPA of 4.0/4.0 throughout undergraduate studies.2020 – 2023
  • BRAC University Vice Chancellor’s List: Recognized on Vice Chancellor's List 10 times during Bachelor's for achieving a GPA of 3.90-4.00 in multiple semesters.2020 – 2023
  • Outstanding Cambridge Learner Award: Awarded World Highest Marks (100%) in AS Level Mathematics.2019
  • The Daily Star Award for A Level Outstanding Results: Recognized for achieving a minimum of 3 A's in A Level examinations.2019