About Me

I am a Machine Learning Engineer with a PhD background in Topological Dynamics and Ergodic Theory from BITS Pilani. My path from pure mathematics research into applied ML means I approach model design, optimization, and evaluation from first principles — not just from framework documentation. I specialize in building systems where the mathematics is load-bearing: feature engineering grounded in domain theory, loss functions that reflect the actual problem geometry, and evaluation frameworks that catch the failure modes that accuracy scores miss. I'm currently open to ML engineering and applied research roles.