Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Hanyu Gao

Assistant Professor

The Hong Kong University of Science and Technology

Hong Kong

Research Interests

Articles (19)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Collaborators (2)

Wen-Jun Wang

Professor

McMaster University

CANADA

View details

Linyan Li

City University of Hong Kong

HONG KONG

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Hanyu Gao

Research Interests

Articles (19)

Generating protein hydrogels with customizable stress relaxation behavior via deep learning-driven entanglement design

Understanding Polymer Zip Length through the Lens of Mechanistic Modeling

Enantioselective synthesis of ring-constrained biaryls via a twist-expand-seal strategy

Encapsulated droplet array for intensified micromole-scale high-throughput reaction screening

MG-3D: Multi-grained knowledge-enhanced vision-language pre-training for 3D medical image analysis

Integrating equivariant architectures and charge supervision for data-efficient molecular property prediction

ProcedureT5: adaptive experimental procedure prediction with data-augmented pre-training and multi-source data integration

Synthesis of Cross-Linked Polyolefin Elastomers with High Performance Yet Good Reprocessability

Kinetic modeling for radical polymerization and depolymerization

A Multitask Learning Model for Predicting Various Types of Metal–Organic Framework Stability

Designing Catalysts to Accelerate a Protein–Peptide Assembly-Reaction Cascade

De Novo Design of Polymers with Specified Properties Using Reinforcement Learning

Deep Learning-Assisted Discovery of Protein Entangling Motifs

Computational discovery and systematic analysis of protein entangling motifs in nature: from algorithm to database

Towards large-scale chemical reaction image parsing via a multimodal large language model

An automatic end-to-end chemical synthesis development platform powered by large language models

Using Active Learning for the Computational Design of Polymer Molecular Weight Distributions

Scaling Acceleration Algorithm for Hybrid Kinetic Monte Carlo Simulation of Linear Radical Polymerization

Effect of SiO2 nano-interphase on the water absorption mechanism of natural fiber reinforced composites: A multi-scale study

Collaborators (2)

Wen-Jun Wang

Linyan Li

Make your next move.