# Hi! I'm Arian, a PhD student in Artificial Intelligence and network biology at the University of Cambridge

I'm fascinated by how we can develop and better apply technologies to understand biological systems. So far this has taken me on a journey through classical biochemistry, scanning whole mouse brains to better understand processes of aging, the neurobiology of sleep & sexual behaviour in animals, deep into the the circuitry of the fruit fly brain to unpick the wiring of innate behaviours and learning & memory, and, finally, to the circus that is deep learning to improve drug discovery. Download my CV.

# Education


Deep learning for structural biology and drug discovery. Supervisors: Prof Sir Tom Blundell & Prof Pietro Lio

Computational Biology Group, Artificial Intelligence Group

Department of Computer Science & Technology

Structual Biology & Biocomputing Group

Department of Biochemistry

University of Cambridge


Department of Life Sciences

Imperial College London


BSc. Biochemistry

1st Class Honours

Dissertation: 3D Imaging of the Connectome. Supervisor: Prof Stephen Brickley. Tutor: Prof Anne Dell.

# Publications

A more up-to-date list may be found on my Google scholar page

Predicted Structural Mimicry of Spike Receptor-Binding Motifs From Highly Pathogenic Human Coronaviruses 2021. Christopher A Beaudoin, Arian Rokkum Jamasb, Ali Alsulami, Liviu Copoiu, Andries J van Tonder, Sharif Hala, Bridget P Bannerman, Sherine E Thomas, Sundeep Chaitanya Vedithi, Pedro H M Torres, Tom L Blundell. bioRxiv

Utilising Graph Machine Learning within Drug Discovery and Development 2020. Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King. Briefings in Bioinformatics

SARS-CoV-2 3D database: Understanding the Coronavirus Proteome and Evaluating Possible Drug Targets 2020. Ali Alsulami*, Sherine Thomas*, Arian R. Jamasb*, Christopher Beaudoin*, Ismail Moghul*, Bridget Bannerman, Liviu Copoiu, Sundeep Vedithi*, Pedro Torres*, Tom Blundell. Briefings in Bioinformatics

Message Passing Neural Processes 2020. Ben Day, Cătălina Cangea, Arian R. Jamasb, Pietro Liò. arXiv 2009.13895

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Protein Structures. 2020. Arian R. Jamasb, Pietro Liò, Tom L. Blundell. Workshop on Graph Representation Learning and Beyond at ICML 2020

The Photoswitch Dataset: A Molecular Machine Learning Benchmark for the Advancement of Synthetic Chemistry. 2020. Aditya Thawani*, Ryan-Rhys Griffiths*, Arian R. Jamasb, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander Aldrick, Alpha Lee. ChemRxiv

Complete Connectomic Reconstruction of Olfactory Projection Neurons in the Fly Brain. 2020. Alexander S. Bates*, Philipp Schlegel*, Ruairí J. V. Roberts, Nikolas Drummond, Imaan F. M. Tamimi, Robert G. Turnbull, Xincheng Zhao, Elizabeth C. Marin, Patricia D. Popovici, Serene Dhawan, Arian R. Jamasb, Alexandre Javier, Feng Li, Gerald M. Rubin, Scott Waddell, Davi D. Bock, Marta Costa, Gregory S. X. E. Jefferis. Current Biology

Functional and Anatomical Specificity in a Higher Olfactory Centre. 2019. Shahar Frechter, Alexander S. Bates, Sina Tootoonian, Michael-John Dolan, James D. Manton, Arian R. Jamasb, Johannes Kohl, Davi Bock, Gregory S.X.E. Jefferis. eLife

Ethoscopes: An open platform for high-throughput ethomics. 2017. Quentin Geissmann, Luis Garcia Rodriguez, Esteban J. Beckwith, Alice S. French, Arian R. Jamasb, Giorgio F. Gilestro. PLOS Biology

# Contact

Feel free to reach out at arian [a] or follow me on Twitter, Github or Linkedin.