Abstract: In this talk, I will explore key research contributions in efficient deep learning, with a focus on training smaller yet highly capable language models. I will discuss approaches such as curating high-quality datasets and designing effective training curricula. The talk will cover different stages of training, including pre-training, mid-training, and agentic reasoning and highlight…

Speaker: Lu Lu, Yale University Abstract: As an emerging paradigm in scientific machine learning (SciML), deep neural operators pioneered by us can learn nonlinear operators of complex dynamic systems via neural networks. In this talk, I will present the vanilla deep operator network (DeepONet) and several extensions of DeepONet, such as DeepONet with Fourier decoder…

Title: Accelerating Biomolecular Design with Generative AI Abstract:  The discovery of biomolecules with desired properties is critical to advances in drug discovery and synthetic biology. This problem is challenging due to the combinatorial search space of biomolecules. In this talk, I will present how generative AI can be used to accelerate the discovery process across…