View Proposal

---

Proposer

Chengjia Wang

Title

Toward Reliable Drug-Target Interaction Predictions in Out-of-Distribution Data Scenarios

Goal

To develop more robust models that can generalize effectively to unseen data and improve the reliability of DTI predictions in real-world applications.

Description

Given the increasing complexity of drug-target interaction (DTI) predictions and the challenges posed by out-of-distribution (OOD) data, this project will address this issue.

Resources

Background

Url

Difficulty Level

Easy

Ethical Approval

None

Number Of Students

1

Supervisor

Chengjia Wang

Keywords

blockchain, finance, machine learning, deep learning, agentic, graphic neural network

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Computer Systems Management
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Engineering in Robotics
Bachelor of Science in Computer Science (Cyber Security)
Master of Science in Robotics with Industrial Application
Bachelor of Science in Statistical Data Science
BSc Data Sciences