Dr. Hoang Dang

Assistant Professor

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Biography

Hoang Dang is an Assistant Professor in the Department of Chemical Engineering at Queen’s University, Kingston, Canada, holding the Mitchell Professorship in Advanced Energy Storage Materials and Technology. He leads the Recharge Lab, where his team focuses on the development of functional materials for sustainable energy storage technologies, aiming to make clean energy reliable and widely accessible. Hoang has authored 17 peer-reviewed publications and is the inventor of 3 patents in the field of energy storage technologies. He is the recipient of several awards, including the Vallet Scholarship, VEF Fellowship, and the Young Lecturer Award. His research addresses the challenges associated with variable renewable energy sources such as solar and wind, which require efficient and cost-effective storage solutions to balance supply and demand. Lithium-ion batteries, although dominant due to their high performance and scalability, face significant challenges including cost, safety, lifespan, and recycling, issues that are critical in the rapid expansion of the electric vehicle market. Hoang is committed to tackling these challenges through the development of novel materials and chemistries, advancing sustainable practices in battery technology.

Research Interests

Experience

Product Development Manager

— Present

Universal Matter Inc. • Canada

Research Scientist

— Present

North Carolina State University • USA

Requirements for Queen's University

Master Program
Requirements
GPA Requirement
Required:3.3
TOEFL
Listening
Required:20
Reading
Required:22
Writing
Required:24
Speaking
Required:22
Total
Required:88
IELTS
Overall
Required:7
Prerequisites
Honours Bachelor degree Background in Computing, Mathematics, Statistics, or Engineering
Application Checklist
  • Online application
  • Statement of Research Interest
  • Curriculum Vitae
  • Two academic references
  • Transcripts
Specialization Notes

Department of Computing offers research-based, project-based, and course-based patterns.