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Sina Majidian

Sina Majidian's image 

Sina Majidian, Ph.D.
Assistant Professor,
Data Science and AI Division,
Department of Computer Science and Engineering,
University of Gothenburg.
Chalmers University of Technology.
DDLS Fellow, Group Leader,
SciLifeLab, Sweden.

[sina.majidian a.&t. gmail]

(Rome, Italy. Apr, 2022)

* We are hiring PhD students and PostDocs. Interested candidates are welcome to send their CV and a letter of interest to us. Check out the Computational Genomics Research Lab website CGRLab.github.io,

Research Interests

  • Pangenomics & Comparative genomics

  • Genetic variations

  • Genomic language models

About me

I am an Assistant Professor and lead the Computational Genomics Research (CGR) Lab in the Data Science and AI division of the Department of Computer Science and Engineering. The department is joint between the University of Gothenburg and Chalmers University of Technology in Gothenburg, Sweden. Previously, I was a Postdoctoral Fellow in the Department of Computational Biology at the University of Lausanne, Switzerland (2021–2024 and 2026) in the Comparative Genomics Lab, led by Christophe Dessimoz and Natasha Glover. I also held a postdoctoral position in the Department of Computer Science at Johns Hopkins University, USA, from 2024–2025, working with Ben Langmead. I was a research intern at the Human Genome Sequencing Center, Baylor College of Medicine, with Fritz Sedlazeck. I completed my PhD in Signal Processing at Iran University of Science & Technology in 2020 supervised by Prof. Kahaei, accompanied by a research visit to the Bioinformatics Group in the Department of Plant Sciences, Wageningen University & Research, The Netherlands, with Dick de Ridder (2018-2019). My research focuses on characterizing genome variation and evolution by developing interpretable and efficient methods in comparative pan-genomics.
We strive to understand genome variation and evolution across different genomic regions by developing interpretable and efficient methods in comparative pan-genomics. Our lab have developed methods and written software in the field of comparative genomics, aiming to enable evolutionary analysis at the scale of the Tree of Life, specially for orthology and phylogeny inference. We contributed to the development of Read2Tree, a fast and accurate method for inferring phylogenies from sequencing reads. We developed FastOMA, a tool for accurately identifying orthologous genes by distinguishing them from paralogs. This tool makes a significant impact in orthology prediction and addresses the challenges of growing large-scale genomic data. During my PhD, I have developed methods for estimating haplotype blocks from single nucleotide variants (SNVs) called from DNA sequencing reads.

Experiences

Education