SADF

Saadat Rafid Ahmed

Lecturer

saadat.ahmed@bracu.ac.bd

Websites

https://saadat-r-ahmed.notion.site/Saadat-Rafid-Ahmed-131658b6e40b80ac9384e3757e9d5828

Address

CSE Department
4th floor, Room No # 4J51,
Brac University,
Kha 224 Bir Uttam Rafiqul Islam Avenue,
Merul Badda, Dhaka, Bangladesh

Saadat Rafid Ahmed is a Lecturer in the Department of Computer Science and Engineering at BRAC University, Dhaka. He is actively engaged in multiple research projects spanning Computational Biology and Computational Linguistics. Previously, he has worked as a Data Scientist on the ACE team at Robi Axiata Limited, where he focused on implementing AI pipelines and designing Hierarchical models on Robi's 47M User's transnational data and Generative AI tasks maintaining standard industrial norms data governance, security and sustainability. His research is dedicated towards addressing the low-resource nature of the Bangla language in Computational Linguistics paradigm and elevating its standards on an international scale.

  • Lecturer, Department of CSE
    Brac University, Bangladesh

 

  • Data Scientist, ACE, Corporate Strategies
    Robi Axiata Limited, Bangladesh

 

  • Undergraduate Teaching Assistant, Department of CSE & MNS
    Brac University, Bangladesh


 

  • Graduated with “Highest Distinction”
  • Appeared in Vice Chancellor’s Honor List in BSc

Class: SRD

Advising Discord: SRA

USIS: SRDF

  • Computational Biology
  • Computational Linguistics 
  • Natural Language Processing (NLP)
  • Large Language Model (LLM)
  • Low-resource Language (Bangla)
  • Machine Learning
  • Artificial Intelligence
  • Computational Social Science
  • Retrieval-augmented generation (RAG)

 


 

Thesis

Accepting


As:

  • Supervisor
  • Co-supervisor

Level:

Undergraduate

Type:

  • Thesis
  • Project
  • Internship

Research Interest

  • Computational Linguistics 
  • Natural Language Processing (NLP)
  • Large Language Model (LLM)
  • Low-resource Language (Bangla)
  • Machine Learning
  • Artificial Intelligence
  • Computational Social Science
  • Retrieval-augmented generation (RAG)

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