Aman Sunesh

I’m passionate about building reliable and interpretable AI systems that perform robustly in real-world, data-imperfect settings. My work spans probabilistic modeling, time-series analysis, and generative modeling — with a focus on missing-data mechanisms (MNAR), diffusion models, and uncertainty-aware learning. I’m especially interested in bridging machine learning with sensing pipelines, physics-informed models, and applications in healthcare and scientific domains.