Hey! I'm Ali 👋

Often, we try to improve model performance by building domain-specific methods tuned to particular modalities or benchmarks. I'm interested in building cross-domain methods along two axes: learning stable noise-invariant latent representations and designing model architectures that support reliable long-horizon inference in noisy environments. I develop these methods in both robotics and computational biology. In both settings, I work on self-supervised objectives that learn robust latents and on reward-guided inference methods that correct long-horizon trajectory drift.

I work on these problems at Northwestern University and am fortunate to be advised by Prof. Han Liu and Prof. Zhaoran Wang. My work on virtual cell models and cellular reprogramming is conducted in collaboration with the Chan Zuckerberg Biohub. I like to understand the systems that my methods interact with, so I build accessible robotics hardware. Outside of research, I enjoy mountain biking and swimming.