I am largely self-directed — someone who picked up the field through curiosity. I am an ML Researcher working across three areas: ML Optimization, where I study and apply techniques that improve how models learn — from loss functions and activation functions to training dynamics; NLP, where I focus on modeling, machine translation, and diffusion models; and ML for Biology, where I apply deep learning to biological sequences and problems at the intersection of life sciences and computation.

Across these areas, I build projects and research, some of which have been accepted at conferences. I am open to research collaborations, internships, job opportunities, or PhD scholarships where I can contribute meaningfully to these areas.

Here are a few technologies I work with:

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