Mehdi Yazdani-Jahromi

Hello, I’m Mehdi Yazdani-Jahromi, an AI Ph.D. Researcher at the University of Central Florida and a dedicated Graduate Research Assistant. My research primarily revolves around the dynamic fields of computer vision, drug discovery, and graph neural networks. My work has been recognized in prominent conferences such as AAAI and Neurips, where I have contributed my insights and findings to the broader AI community.

My journey in AI research is marked by significant achievements. Recently, I was honored with the $30,000 Amazon Research Credit Award for my project CoViT and received the prestigious Outstanding Graduate Fellowship at UCF. These awards are a testament to my commitment and the impact of my research in AI. I am particularly interested in leveraging AI to transform healthcare, with a focus on drug target interactions and the advancement of computer vision technologies. My goal is to continue contributing innovative solutions and insights in AI, driven by the potential to revolutionize healthcare and technology through intelligent systems.

News

Apr 20, 2024	I will be presenting our work at RECOMB 2024 in Cambridge Boston at MIT campus! Join me on the 30th of April from 14:00 - 14:55 as I present our paper titled “FragXsiteDTI: Revealing Responsible Segments in Drug-Target Interaction with Transformer-Driven Interpretation.”
Dec 22, 2023	Thrilled to announce that our paper (FragXsiteDTI) has been accepted at RECOMB 2024, following its acceptance at the NeurIPS 2023 AI for Drug Discovery and Development Workshop!
Dec 11, 2023	We are excited to unveil DeepDrugDomain, an advanced Python toolkit tailored for enhancing drug-target interaction and drug-target affinity prediction through deep learning. GitHub Link

Latest Posts

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Selected Publications

FragXsiteDTI: an interpretable transformer-based model for drug-target interaction prediction

Ali Khodabandeh Yalabadi , Mehdi Yazdani-Jahromi , Niloofar Yousefi , and 3 more authors

In NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development , 2023

Bib

@inproceedings{yalabadi2023fragxsitedti,
  title = {FragXsiteDTI: an interpretable transformer-based model for drug-target interaction prediction},
  author = {Yalabadi, Ali Khodabandeh and Yazdani-Jahromi, Mehdi and Yousefi, Niloofar and Tayebi, Aida and Abdidizaji, Sina and Garibay, Ozlem},
  booktitle = {NeurIPS 2023 Workshop on New Frontiers of AI for Drug Discovery and Development},
  url = {https://openreview.net/forum?id=AlWm9Cyelk},
  year = {2023},
}

AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification

Mehdi Yazdani-Jahromi , Niloofar Yousefi , Aida Tayebi , and 4 more authors

Briefings in Bioinformatics, 2022