Mehdi Foroozandeh
Ph.D. Candidate · Simon Fraser University
Graduate Scientist · Roche
Ph.D. Candidate · Simon Fraser University
Graduate Scientist · Roche
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I am a Ph.D. candidate in the Computing Science department at Simon Fraser University, focusing on computational biology and machine learning.
Currently, I also work as a Graduate Scientist at Roche Diagnostics.
Simon Fraser University
2023 – Present
Simon Fraser University
2020 – 2022
University of Tehran
2015 – 2019
Roche
2025 – Present
Simon Fraser University
2020 – Present
University of Tehran
2019 – 2020
Open-source research tools and computational frameworks.
An agentic research companion that organizes a research program as a tree of questions and falsifiable hypotheses in a markdown vault your LLM agent drives.
Agent skills for Claude Code and skills.sh-compatible agents — response-mode and collaboration modes that change how the agent thinks and replies.
A self-supervised deep learning framework for denoising and imputing epigenomic data with confidence-aware prediction for robust genomic analysis.
Evaluation of chromatin state annotation confidence and reproducibility.
Generalized machine-learning framework for automated enzyme discovery from metagenomic data.
Machine-learning framework for targeted cellulase discovery from metagenomic data.
Predicts thermal activity of xylanase enzymes from sequence features to support targeted enzyme discovery and screening.
Selected peer-reviewed work.
2025
Integrative chromatin state annotation of 234 human ENCODE4 cell types using Segway
M Farahbod, A Diab, P Sud, MS Kagda, I Whaling, M Foroozandeh, I Goel, …
Genome Research
CANDI: self-supervised, confidence-aware denoising imputation of genomic data
M Foroozandeh, AR Diab, M Libbrecht
bioRxiv, 2025.01
2024
Robust chromatin state annotation
MF Shahraki, M Farahbod, MW Libbrecht
Genome Research
Precision enzyme discovery through targeted mining of metagenomic data
S Ariaeenejad, J Gharechahi, M Foroozandeh Shahraki, F Fallah Atanaki, …
Natural Products and Bioprospecting
2022
A computational learning paradigm to targeted discovery of biocatalysts from metagenomic data: a case study of lipase identification
MF Shahraki, FF Atanaki, S Ariaeenejad, MR Ghaffari, …
Biotechnology and Bioengineering
Evaluating the reproducibility of segmentation and genome annotation (SAGA) algorithms
M Foroozandeh Shahraki
Simon Fraser University
دیاسپورا — این روزها زیاد به این واژه فکر میکنم. تداعیگر اندوه شده؛ تداعیگر کوچ و دوری و آوارگی. دیاسپورا از ریشهٔ واژهٔ یونانی speirein به معنای «پراکندن» است — همان ریشهای که واژهٔ spore (هاگ) نیز از آن مشتق شده است.
Read article →Unsupervised machine learning grapples with evaluating models in the absence of ground truth. To circumvent this, researchers often rely on downstream tasks that provide some ground truth, allowing an indirect assessment of model efficacy.
Read article →Interested in collaboration or have questions about my research?