I am a PhD-trained physicist and data scientist
working at the intersection of fundamental research,
computational science, machine learning, and
software engineering.
My scientific background is rooted in astrophysics
and cosmology, with research spanning active
galactic nuclei, galaxy evolution, gas kinematics,
variability, time-series analysis, statistical
inference, and computational modeling.
Alongside academic research, I develop practical
data and machine-learning systems, including
scalable ETL pipelines, analytics platforms,
predictive models, APIs, and full-stack web
applications.
My work is driven by a simple principle:
use rigorous scientific thinking and modern
computational tools to transform complex data into
useful knowledge and intelligent systems.
PhD
Physics — Astrophysics & Cosmology
5+
Years of International Experience
12+
Peer-Reviewed Publications
3
Core Domains: Physics, Data & AI