Ashish Kumar

I am working in the domain of complex disease medical research, specializing in bioinformatics, biostatistics, computational genetics, and high-performance computing (HPC). I am a deep-tech enthusiast with expertise in big-data analytics spanning genetic epidemiology, computer science, cloud computing, and data sciences, particularly at the convergence of biophysics, nanotech, and AI & ML applications for biomedical and translational re-engineering. 

At Karolinska (since 2012), I'm providing consultancy to Prof. Erik Melén's group and affiliated to Department of Clinical Science and Education at the Södersjukhuset (KI SÖS) - one of the largest hospitals in Stockholm.

Previously, I was working in Diabetes Research group, led by Prof. Mark McCarthy at the Wellcome Centre for Human Genetics, University of Oxford (from 2006-2014) and Genetic Epidemiology group, led by Prof. Nicole Probst-Hensch at the Swiss Tropical and Public Health Institute, University of Basel in Switzerland (from 2010-2018). I am also into developing new Indo-European collaborative research projects in complex diseases as well as technology convergence in the genomics domain.

Research Summary:

• OMICs data integration involving GWAS and imputed datasets, sequencing (genomic and exomes), methylation/epigenomics data, transcriptomics, expression arrays, proteomics and biological pathways.
• Application of methodologies in artificial intelligence/machine learning into genomics.
• Complex diseases like asthma, type-2 diabetes, pulmonary function traits like lung function, COPD, eczema, rhinitis, obesity, BMI and related phenotypes.
• GWAS analysis in consortium projects like DIAGRAM , ENGAGE , EGG, EAGLE, SpiroMeta, MAGIC, GoDMC, etc.
• EWAS analysis in consortium projects with PACE and MeDALL
• Discovery, genotyping and association evaluation of variants in projects like GoT2D, GABRIEL and SUMMIT project (developing SOPs and pipelines for discovery/analysis on HPC servers and super-computing clusters).
• Evaluations of methylation chip data using various normalisation methods
• Annotation challenges with genetics and epigenetics datasets.

Expertise:

• Statistical genetics and multivariate analytics.
• AI/ML applications in genomics.
• Diverse range of OMICs platforms including low-coverage sequencing, exome-sequencing, dense-array genotyping on various chips from Illumina & Affy, methylation arrays from Illumina, custom i-Select chips like Metabochip, HumanCoreExome, etc.
• Gene and environment interactions, rare variants and fine mapping analysis.
• Building and incorporating large QC and bioinformatics-pipelines for various types of -omics datasets like genotyped/imputed SNPs, methylation CpGs, RNA-seq, proteomics, expression, etc.
• Managing Data centre, high-performance computing resources and big-data analytics pipeline development.
• Large scale data storage, handling, formatting and visualisation.
• Bioinformatics education and training.

For detailed publications list, please follow this link:

http://scholar.google.co.uk/citations?user=j-eQjGEAAAAJ&hl=en