Peeyush Dyavarashetty

I'm a Machine Learning Engineer and graduate student at the University of Maryland, where I serve as Chair of the CMNS Graduate Student Council and Machine Learning Representative —leading initiatives to solve problems faced by Science Academy and CMNS as a whole in academia. When my work mode is switched off, you'll find me hiking rugged trails, speeding down hills on my bike (occasionally testing gravity's patience), or diving into video games.

My work is fueled by a love for problem-solving and I'm passionate about building AI systems that solve real-world problems at scale. My work sits at the intersection of research and engineering —whether I'm pretraining LLMs from scratch, optimizing ETL pipelines, or deploying real-time deep learning models. I thrive on translating complex technical concepts into impactful solutions, balancing rigorous experimentation with practical execution. Just like my cycling adventures, I believe the best solutions emerge from momentum, adaptability, and a dash of fearless experimentation.

What drives me is the belief that AI should empower people, not just automate tasks. Let's collaborate to push AI's boundaries—responsibly and creatively.