Software and AI engineer here. I love building beautiful and functional softwares and training AI systems that solve real problems. I also enjoy writing about my experiences and sharing my knowledge with others. I believe in open source, open knowledge, and the power of community.
At a glance
Actively seeking a Master's/PhD opportunity to contribute to pioneering research. My work usually lives somewhere between research and implementation, moving through computer vision, biomedical signal processing, cloud-backed systems, and carefully crafted interfaces.
How I work
I like work that starts with careful thinking and still makes it all the way to something usable, testable, and practical.
My projects regularly move between product UI, backend APIs, model experimentation, and deployment details without treating those as separate worlds.
Lab support, survey work, and team projects pushed me toward clear explanations, structured handoffs, and patience when the details get messy.
Capabilities
A curated slice of the stack I work with most often, pulled from the broader experience across the site.
Recurring themes
The titles and methods change, but these threads keep connecting the work.
From anomaly detection in surveillance footage to automated fabric defect detection, I keep returning to visual systems where the signal is subtle and the constraints are real.
snoRNA-disease prediction and EEG-based motor movement classification both reflect a broader pull toward biomedical signal processing and applied intelligence.
Energy footprint measurement, cloud architecture, and reproducible ML workflows all come from the same instinct: build things that are not only impressive, but responsible.