Mohammadali Mohammadkhani
- +98 901 451 81 71
- moali.mohammadkhani@gmail.com
- Google Scholar
- Saarland University, Saarbrücken
My name is Mohammadali Mohammadkhani. In July 2024, I graduated from Sharif University of Technology in the field of Computer Engineering. My fields of interest mainly lie in the intersection of Human-centered Computing, Machine Learning, and Natural Language Processing. I started my Master's degree in Computer Science at Saarland University in October 2025.
Education
Master of Science in Computer Science
Saarland University, Saarbrücken, Germany
Bachelor in Computer Engineering
Sharif University of Technology, Tehran, Iran
Diploma of Mathematics
Ehsan High School, Tehran, Iran
Awards
University Entrance Exam
Ranked 47th among more than 150,000 participant in Iran National University Entrance Exam (Konkour) in Mathematics Branch in 2019
Publications
Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation
Toward Inclusive Low-Code Development: Detecting Accessibility Issues in User Reviews
MultiMind at SemEval-2025 Task 7: Crosslingual Fact-Checked Claim Retrieval via Multi-Source Alignment
Emotion Alignment: Discovering the Gap Between Social Media and Real-World Sentiments in Persian Tweets and Images
Empowering Teaching Assistants: A Platform for Streamlined Assignment Creation and Collaboration
Research Interests
Human-Centered Computing
Machine Learning and Natural Language Processing
Software Engineering
Research Experience
Detecting Accessibility in Low-code Applications using Artificial Intelligence
Working on Low-code applications' reviews and analyzing them to detect accessibility-related issues. Gathering a novel dataset for application reviews and labeling them. Using a Transformers-based module to classify reviews into two distinct groups.
Personality Detection on Twitter and Comparing It to the Real-world Personality (B.Sc. Project)
Working on personality detection on X (former Twitter). Using two Transformers-based modules to perform sentiment analysis on both tweets and images. Extracting users' real-world personalities via a novel pipeline consisting of questionnaires' distribution to participants' friends. Comparing all these results to deduce a conclusion about the user's personality.
Designing an Educational Helper Website for Teaching Assistants
In this project, we aim to create a supplementary website for teaching assistants to facilitate the process of idea or question generation and management. They can store their ideas or questions on the website and even enhance them with tailored and customized suggestions.