Mohammadali Esfahani

Master of Science in Computer Science - Soft Computing & Artificial Intelligence

from Amirkabir University of Technology

mohammadali.sefidi@gmail.com

About

Hello! This is Mohammadali Sefidi Esfahani. I obtained my master's degree in Computer Science from Amirkabir University of Technology (AUT), and collaborate with Dr. Mohammad Akbari on the problem of unspecified social event detection from Twitter. Recently, I've been working on the impact of code reviewer recommendation systems on the risk of developer turnover in software projects, and our recent research paper with Dr. Peter Rigby is accepted in ICSE'26. At this stage of my academic journey, I have successfully achieved my educational objectives in my country, and I desire to continue my academic journey in one of the top universities. After exploring various fields and implementing several projects, I believe that there is considerable potential in using AI and Natural Language Processing methodologies in software engineering tasks. In particular, below are some keywords of my recent interests:

Education

Master of Science in Computer ScienceSep. 2021 - Sep. 2023

Amirkabir University of Technology, Tehran, Iran

Cumulative GPA: 19.62 out of 20

Master’s Thesis: Identification of Unspecified Events from Twitter

Supervisor: Dr. Mohammad Akbari

Awards: 1st-ranked student

Bachelor of Science in Computer ScienceSep. 2017 - Jul. 2021

Kharazmi University, Tehran, Iran

Cumulative GPA: 18.26 out of 20

Bachelor’s Thesis: Comparative study on performance of ML models for fall detection in older people

Supervisor: Dr. Mohammad Soltanian

Awards: 1st-ranked student

Publications

The Cost vs the Benefit of Adding an Extra Code Reviewer to Mitigate Developer Turnover through Reviewer Recommenders

Mohammadali Sefidi Esfahani, Fahimeh Hajari, Peter C. Rigby

Accepted in ICSE'26

EnrichEvent: Enriching Social Data with Contextual Information for Emerging Event Extraction

Mohammadali Sefidi Esfahani, Mohammad Akbari

Published in Iran Journal of Computer Science, 2025

Comparative Study on Performance of ML Models for Fall Detection in Older People

Mohammadali Sefidi Esfahani, Mohammad Fattahian

Available on PrePrints.org

Feature Learning for Identification of Persian Events from Twitter

Mohammadali Sefidi Esfahani, Mohammad Akbari

Published in CSICC 2023

Research Experience

Graduate Research AssistantAUT, Tehran, Iran

Data Science Innovation CenterNov. 2021 - Sep. 2024

Supervisor: Dr. Mohammad Akbari

Teaching Assistant (Machine Learning)Tehran, Iran

Amirkabir University of Technology Sep. 2023 - Feb. 2024

Lecturer: Dr. Ali Mohades

Lead Teaching Assistant (Machine Learning)Tehran, Iran

Amirkabir University of TechnologySep. 2022 - Feb. 2023

Lecturer: Dr. Mohammad Akbari

Graduate Research AssistantAUT, Tehran, Iran

NLP Innovation CenterNov. 2021 - Aug. 2022

Supervisor: Dr. Ali Mohades and Dr. Mohammad Akbari

Executive Assistant Kharazmi University, Tehran, Iran

ACM Assocication Mar. 2021 - Aug. 2021

Supervisor: Dr. Bardia Panahbehagh

Vitæ

Full CV in PDF.

  • Data Science Innovation Center Nov. 2021 - Sep. 2024
    Graduate Research Assistant
    Amirkabir University of Technology
  • NLP Innovation Center Nov. 2021 - Aug. 2022
    Graduate Research Assistant
    Amirkabir University of Technology
  • Amirkabir University of Tech Sep. 2021 - Sep. 2023
    Master of Science in Computer Science
    Soft Computing & Artificial Intelligence
  • ACM Association Mar. 2021 - Aug. 2021
    Executive Assistant
    Kharazmi University
  • Kharazmi University Sept. 2017 - Jul. 2021
    Bachelor of Science in Computer Science