# 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. My Erdős number is 4 and can be derived as follows: Arian Jamasb -> Gerald Rubin -> S. Shankar Sastry -> Béla Bollobás -> Paul Erdős 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

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Protein Structures. 2020. Arian R. Jamasb, Pietro Lio, 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 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

# Projects & Research

Computational Biology Group, Artificial Intelligence Group

Department of Computer Science & Technology

University of Cambridge

Winter 2018

Predicting transcriptional responses to combinations of drugs with a VAE

Drosophila Connectomics

Collaboration with Google, University of Oxford and HHMI Janelia Research Campus to reconstruct behaviourally relevant neural circuits from analysis of a whole-brain dataset of electron micrographs at synaptic resolution.

Drosophila Connectomics Group

Department of Zoology

University of Cambridge


Brickley Lab

Department of Life Sciences

Imperial College London

Spring 2017

Automated Quantification of Cells Across Whole-Brain Image Volumes

Developed a computer vision algorithm to automatically quantify the distribution of fluorescently-tagged cells across 2-photon image volumes of whole mouse brains.


The Ethoscope Platform is a collection of interconnected tools allowing biologists to design experiments, acquire and analyse large amounts of behavioural data using an unsupervised machine learning algorithm for computer vision. I developed a module for real-time stimulus delivery dependent on a behavioural cue. Recently this has been used to show that chronic sleep deprivation is non-lethal for fruit flies!

Gilestro Lab

Department of Life Sciences

Imperial College London


# Contact

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