My background is in developing algorithms using the latest image processing and computer vision technologies to harness the power in medical imaging technologies such as CT, MRI, Digital pathology images, and so on to deliver various scientific insights. I have always been thrilled about using cutting-edge technology to transform drug discovery and personalise medicine for patients.

At Carnegie Mellon University, my focus was on computational neuroscience. My research was on understanding the early visual cortex using simulation and deep learning technologies while obtaining my master’s in biomedical engineering.

I stepped into the industry as a consultant with Definiens in 2018. We partnered with various pharmaceutical industries to develop imaging solutions for digital pathology images to deliver insights to Immuno-oncology studies.

In 2019, I joined AstraZeneca as Senior Data Scientist in Data Science and AI. I have contributed to a variety of R&D functions to identify digital imaging biomarkers, accelerate pre-clinical studies, and stratify patient populations based on baseline characteristics. I have had the chance to collaborate with colleagues from diverse backgrounds and contribute towards the common goal of transforming patient lives using digital technologies.


I am thrilled to be in the center of innovation and work every day with diverse individuals to find novel solutions to key scientific challenges. The highlight of my work is applying the latest and innovative technologies in the field of computing to drive innovation in the biopharmaceutical industry.

Gayathri Mohankumar Senior Data Scientist, Computer Vision, AstraZeneca

Gayathri Mohankumar, Senior Data Scientist, Computer Vision, AstraZeneca

CURRENT ROLE: 2019-2022

Senior Data Scientist, Computer Vision, AstraZeneca

2019-2022

Senior Data Scientist, Computer Vision, AstraZeneca

2018-2019, Consultant Datafication at Definiens Inc.

Developed image analysis pipeline to understand tumor microenvironment in mIF and brightfield images to deliver insights to various immune-oncology studies

2016-2018, Master’s in biomedical engineering

Research was focused on computational neuroscience to understand the early visual cortex of the macaque monkeys

2012-2016

Bachelor’s in biomedical engineering

Publications


Automated quantification of whole-slide multispectral immunofluorescence images to identify spatial expression patterns in the lung cancer microenvironment

Automated quantification of whole-slide multispectral immunofluorescence images to identify spatial expression patterns in the lung cancer microenvironment. L Rognoni, V Pawar, T Heng Tan, F Segerer, P Wortmann, S Batelli, P Bonneau, A Fisher, G Mohankumar, D Chain, M Surace, K Steele, J Rodriguez-Canales. Society for Immunotherapy of Cancer (SITC) 2018.

Ultra-high-density scalp EEG outperforms localized invasive ECoG grids in inferring depth of seizure foci

Ultra-high-density scalp EEG outperforms localized invasive ECoG grids in inferring depth of seizure foci. R Kumar, P Venkatesh, R Sun, G Mohankumar, A Arun, M Richardson, P Grover. Clinical Neurophysiology volume 129, supplement 1, e113 (May [WL(LPR1] 2018) | doi10.1016/j.clinph.2018.04.286

http://www.sciencedirect.com/science/article/pii/S1388245718305686

Recurrent networks fitting neural temporal responses to natural images exhibit contextual modulation

Recurrent networks fitting neural temporal responses to natural images exhibit contextual modulation. H Rockwell, YM Zhang, G Mohankumar, S Tsou, TS Lee. Poster Presentation, Computational and Systems Neuroscience (Cosyne) 2021.


Veeva ID: Z4-66291
Date of preparation: July 2024