851 S. Morgan St.
Chicago, IL, 60607
Hey there! I’m Mohammad Arvan, a Ph.D. candidate in Computer Science at the University of Illinois at Chicago, under the supervision of Dr. Natalie Parde. My research is centered on improving the reliability of machine learning, with a particular focus on evaluation and reproducibility. I advocate for Open Science, emphasizing transparency, equity, and inclusivity in research practices. With a strong engineering background, I prioritize practical solutions to enhance the trustworthiness of machine learning technologies.
|Jun 12, 2022||‘Reproducibility of Exploring Neural Text Simplification Models: A Review’ was accepted at 15th International Natural Language Generation Conference|
|Jan 2, 2021||Ranked top 8% on Stackoverflow’s 2020 year rank|
|Dec 8, 2020||Proud recipient of PGRA award ($5000)|
|Nov 17, 2022||Reproducibility: on why and how|
- Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLPIn The Fourth Workshop on Insights from Negative Results in NLP, May 2023
- Reproducibility in Computational Linguistics: Is Source Code Enough?In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022, May 2022