Chang Gung University

Quantum AI Biomedical Research Lab

Renata Wong
https://renatawong.github.io/

Research Field

Physics

Introduction

Positions: 

  • 11/2021 - 08/2023: Postdoctoral researcher at the Physics Division, National Center for Theoretical Sciences, National Taiwan University, Taipei. 
  • 08/2023 - present: Assistant Professor at the Department of Artificial Intelligence, Chang Gung University, Taoyuan. 
  • 01/2025 - present: Assistant Research Fellow (joint appointment) at the Department of Neurology, Chang Gung Memorial Hospital, Keelung. 

Memberships: 

  • American Physical Society
  • The Physical Society of Taiwan
  • IEEE

Volunteering: 

  • IBM Quantum Qiskit Advocate 

Quantum AI Biomedical Research Lab is located at the Department of Artificial Intelligence, Chang Gung University. Website: https://renatawong.github.io/. Our research focuses on the following areas: 

  1. quantum computing and quantum information, 
  2. physics-informed machine learning, 
  3. artificial intelligence for healthcare and medical applications

Our members come from fields such as physics, data science, mathematics, electrical engineering, and computer science. 


Research Topics
  • Quantum Computing, 
  • Quantum Information, 
  • Quantum Machine Learning, 
  • Physics-informed Machine Learning, 
  • Artificial Intelligence for Medical Applications, 
  • Quantum Chemistry

Honor

Prof. Wong leads the Quantum AI Biomedical Research Lab, fostering interdisciplinary research that bridges quantum computing and biomedical sciences. She is also actively involved in IBM Quantum Qiskit Advocate program that aims to educate and inform about quantum computing and its applications. 

In 2025 she received the Chang Gung University Excellence in Teaching award. For more details, please visit her LinkedIn profile: https://www.linkedin.com/in/renata-wong/, or her university website: https://pure.lib.cgu.edu.tw/en/persons/renata-wong/

 


Educational Background
  • PhD in Quantum Computing (Nanjing University, China)
  • MSc in Computer Science (Leipzig University, Germany)
  • BSc in Computer Science (Leipzig University, Germany)
  • MA in Sinology (Warsaw University, Poland, and Leipzig University, Germany)

Job Description

(2) Quantum information, quantum computing, quantum machine learning

The intern will undertake a project in quantum information, depending on their background, skills, and proposed topic. The specific project scope and objectives will be determined by mutual agreement.

The project will be carried out at the Quantum AI Biomedical Research Lab, Department of Artificial Intelligence, Chang Gung University. For more information about the laboratory’s research profile, please visit: https://renatawong.github.io/

Preference will be given to applicants with a strong background in quantum information. 

 

Preferred Intern Educational Level

PhD, master's, or final-year undergraduate student

Skill sets or Qualities

  • familiarity with quantum information and quantum computing
  • solid mathematics skills
  • solid understanding of Python, Qiskit, and Pennylane
  • knowledge of other libraries for quantum computing is advantageous
  • for project in quantum machine learning: familiarity with classical machine learning and variational quantum circuits

Job Description

(1) Quantum information, quantum computing, quantum machine learning

The intern will undertake a project in quantum information, depending on their background, skills, and proposed topic. The specific project scope and objectives will be determined by mutual agreement.

The project will be carried out at the Quantum AI Biomedical Research Lab, Department of Artificial Intelligence, Chang Gung University. For more information about the laboratory’s research profile, please visit: https://renatawong.github.io/

Preference will be given to applicants with a strong background in quantum information. 

 

Preferred Intern Educational Level

PhD, master's, or final-year undergraduate student

Skill sets or Qualities

  • familiarity with quantum information and quantum computing
  • solid mathematics skills
  • solid understanding of Python, Qiskit, and Pennylane
  • knowledge of other libraries for quantum computing is advantageous
  • for project in quantum machine learning: familiarity with classical machine learning and variational quantum circuits