anubhavkafle / machine_learning

Python coded examples and documentation of machine learning algorithms.

Namaste 🙏, Hello

Welcome to my GitHub profile.

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Anubhav Kaphle publications

ORCiD ID

Anubhav Kaphle's ORCiD

About me:

Passionate about understanding and tackling human diseases by unlocking the power of the genome

Highly interested in building robust statistical models by integrating multimodal data (genomic data, health record, and other health data) for clinical and genomic diagnostics as well as for disease risk prediction

Working on the development of a novel statistical model to better quantify the contribution of genetics towards trait variation in a population (known as (SNP) heritability), and study the distribution of heritability across the functional regions in the genome. It can further be extended to develop better polygenic risk models (genetic risk prediction models), which is a step towards preventative and precision medicine.

Proficient in handling and analyzing biobank-sized genomic datasets such as the UK biobank datasets using High-Performance computing systems (HPCs).

Have a keen interest in studying trans-ethnic populations to better understand the genetic mechanisms behind common (and rare) diseases. Extensively collaborated with researchers in Taiwan to conduct large-scale heritability analysis on Taiwanese genomic datasets.

Experiences

• Genomic data analysis
• Bioinformatics analysis
• Statistical model development
• Python programming
• C++
• High-performance computing.

Interests

• Statistical Learning
• Deep Learning methods
• Human Genetics
• Digital Health
• Genetic Data Privacy
• Precision medicine
• Science outreach

and sometimes

• Economics
• Science policy research

Feel free to connect with me at

Email address: Anubhav's email
Visit us at: Melbourne Integrative Genomics (MIG)
MIG webpage
The University of Melbourne
Parkville, Melbourne 3010