I am a third year PhD candidate in computational biology at School of Life Sciences in Technical University of Munich (TUM) under supervision of Fabian Theis. My PhD is focused on developing machine learning tools to analyze single-cell genomic data.

My main focus is leveraging single-cell technology and machine learning for Biomedicine and drug discovery. In the first year of my PhD, I developed scGen a tool to analyze and predict the effect of a perturbation (i.e drug, disease) at single-cell resolution. To learn more about the the model, you can check our paper in Nature Methods and media coverage in TUM website. I am also a huge advocate of using ML to facilitate single-cell analysis for every one, regardless of their stat or ML knowledge. I developed a frame work called scArches leveraging transfer learning to create, share and integrate new datasets in to existing references.

Apart from academic research, I performed consulting for drug discovery companies such as Cellarity. I am also collaborating with Facebook AI centered around machine learning for health and recently admitted to FACEBOOK AI research intern program.

Before starting my PhD, As a part of my master thesis thesis, I developed Deep packet, the first end-to-end model to replace classical rule based approaches for traffic classification. The model was favoured by The research community and has been cited 150 times since 2019!

Interests

  • Machine learning
  • Computational biology
  • computational drug discovery

Education

  • PhD in Computational Biology, 2021

    Technical University of Munich

  • MSc in Artificial Intelligence, 2017

    Computer Engineering Department, Sharif university of Technology

  • BSc in computer engineering, 2015

    Faculty of Electrical and Computer Engineering, Tabriz University

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