AI for Materials Discovery

Successful applicants will join the project as Master’s Students / PhD Students at the Center of Environmental Intelligence (CEI), College of Engineering and Computer Science (CECS), VinUniversity. 

Project Information 

This project explores the intersection between Artificial Intelligence (AI) and advanced fabrication processes in organic materials, devices, and systems, with the aim of revolutionizing the design and functionality of next-generation organic electronics.

As organic electronics increasingly require flexibility, high performance, and tunability, traditional trial-and-error methods reveal many limitations in terms of time and cost. The project therefore focuses on building a research framework in which machine learning models not only support data analysis but also directly participate in proposing and optimizing material structures prior to fabrication.

The research structure is defined around three closely interconnected pillars, including inverse design, few-shot learning, and data processing with organic devices, thereby jointly enabling the development of organic technologies in a more intelligent, adaptive, and efficient direction.

The project team includes: Asst. Prof. Nguyen Dang Tung (Principal Investigator) | Asst. Prof Le Duy Dung | Asst. Prof. Ahmad Hajjar | Dr. Vuong Dinh Trung

Research Objectives

Building upon these foundational pillars, the core objectives of the project are:

(i) To develop inverse design models capable of inferring material structures and fabrication parameters from target performance requirements (e.g., electrical conductivity, flexibility, thermal stability, optoelectronic properties).

(ii) To design machine learning algorithms that operate effectively under data-scarce conditions, enabling robust learning and generalization from limited experimental datasets.

(iii) To establish methods for processing and extracting knowledge from data collected from organic devices, while exploring the potential of using such devices as unconventional platforms for information processing.

The project expects to build a systematic and predictive research framework that accelerates materials discovery and enhances the performance of next-generation organic devices.

Project Contact 

For details, please contact Asst. Prof. Nguyen Dang Tung via email [email protected].

Graduate Admissions Contact 

• VinUni Graduate Admissions
•  0978 549 846
• [email protected]

Learn more about Master’s, PhD programs, and scholarships at: VinUni Graduate Research Excellence Program

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