X_raw → X*Build the dataset
I like the unglamorous work that makes later analysis defensible: data cleaning, integration, curation, pipeline design, and reproducible compute.
02f(me)
I work where data engineering meets statistical reasoning.
My projects move between social-media discourse, instructional-media research, GPU computing, and computational genomics. The domain changes. The working pattern stays consistent: structure the data, make the assumptions visible, and evaluate the result.
A How I work
My background began in computer science and expanded into data science, research computing, statistical modeling, and machine learning. That combination makes me comfortable moving from raw records and compute constraints to tests, models, visualizations, and written research.
The strongest example is my graduate research capstone: an end-to-end system that transformed more than 4.3 million comments into a curated 351,501-comment dataset, tested distributional differences, adapted a 9B-parameter language model, and audited its errors. Newer projects extend the same care toward GWAS, molecular QTL evidence, gene networks, and spatial transcriptomics.
H₀ ↔ H₁Test the claim
The model is not the whole answer. I use statistical tests, baselines, sensitivity analysis, and explicit evaluation to understand what the evidence supports.
P(θ | evidence)Keep uncertainty
My current project work in statistical genetics uses Bayesian and probabilistic methods to combine incomplete or conflicting molecular evidence.
B Current questions
What I am exploring now
- How should GWAS, cis-eQTL, cis-pQTL, and colocalization evidence be combined without hiding uncertainty?
- Can probabilistic gene networks identify core disease genes while accounting for conflicting evidence and degree bias?
- Where do genes associated with neurological disease show enriched expression across human brain regions?
C Education
Aug 2024 – May 2026
M.S. Data Science
Rochester Institute of Technology
Rochester, NY · GPA 3.710 / 4.0
Sep 2020 – May 2024
B.E. Computer Science and Engineering
RMK Engineering College
Chennai, India · GPA 3.825 / 4.0