Tinglin Huang

I am a third-year Ph.D. student at Yale University, advised by Prof. Rex Ying.

Previously, I worked with Prof. Jie Tang from Tsinghua University, and Prof. Tat-Seng Chua from National University of Singapore.

My research interests revolve around (1) computational biology, including equivariant macromolecule modeling and multi-modality biological representation learning; and (2) the application of large language models (LLMs) in the healthcare domain.

Email: tinglin.huang[at]yale.edu

Propose STPath, a generative foundation model that infers spatially resolved gene expression across 38,984 genes and 17 organs directly from WSIs.

Propose STFlow, a flow matching generative model to directly infer the spatial gene expression from whole slide images.

Propose an equivariant transformer architecture based on frame averaging and an unsupervised aptamer screening approach.

A surface-based functional protein designer.

An extensive review of the landscape of negative sampling techniques across different domains.

A routing-based molecule dataset grouping method.

A global negative sampling method for contrastive learning.

A scalable GNN framework for semi-supervised graph learning.

A general negative sampling plugin for GNN-based recommender systems.

We proposed KGIN which (1) uncovers useritem relationships at the granularity of intents, and (2) applies relational path-aware aggregation.

Last updated February 2024.
Template from Jon Barron.