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👋 Hey! I'm a 20-year old student exploring the intersection between human longevity, immunology, and cancer, with a dream to eradicate age-related diseases and develop prophylactic (preventative) vaccines for cancer.

🔬 I am currently working as an undergraduate researcher at the Rauh lab at Queen's University to working on a novel project developing an artificially intelligent model to diagnose clonal hematopoiesis of indeterminate potential (CHIP), a pre-malignant blood condition. Further, I am also investigating the link between mosaic chromosomal loss & CHIP, under the supervision of Caitlyn Vlasschaert, PhD-candidate at the Rauh Lab.

🎂 I am also the Chief Scientific Officer and part of the co-founding team at Biotein, a longevity startup aimed at eradicating age-related diseases. We are currently developing a protein-based saliva bio-age test to equip the general population with the information necessary to improve their health and extend their healthspan. In the future, Biotein plans to expand into developing preventative therapies for dementias, which affects 50 million people worldwide, with 10 million new patients every year.

💉 As a passion project, I am also exploring the potential of immunotherapies directed against cancer stem cells (CSCs) to prevent cancer relapse and as prophylactic vaccines against cancer.

🏫 Studying Biomedical Computing at Queen's University.

📫 Find out more about me on my personal website or on my LinkedIn.

Akshaj Darbar's Projects

akshajd icon akshajd

Config files for my GitHub profile.

attentivechrome icon attentivechrome

NeurIPS17: [AttentiveChrome] Attend and Predict: Using Deep Attention Model to Understand Gene Regulation by Selective Attention on Chromatin

elevation icon elevation

End-to-end guide design for CRISPR/Cas9 with machine learning

epigenetic-clock icon epigenetic-clock

This program analyzes methylation levels at six CpG sites in the genome of blood cells to produce a prediction of an individual's biological age, using different machine learning and deep learning models.

mutaguide icon mutaguide

Use homology analysis, secondary structure prediction, and relative solvent accessibility prediction to optimize amino acid residue replacements.

tensorflow-lifetime-value icon tensorflow-lifetime-value

Predict customer lifetime value using AutoML Tables, or ML Engine with a TensorFlow neural network and the Lifetimes Python library.

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