Dr. Elad Liebman

Assistant Professor

Build a Statement of Purpose

Generate a tailored SOP for Dr. Elad Liebman. Improve your application with a focused, well-structured draft.

Biography

Elad Liebman is an Assistant Professor of Instruction in the Department of Computer Science at the University of Texas at Austin. He is a member of the Learning Agents Research Group and has a foundational background as a PhD student. His research primarily focuses on sequential decision-making in content recommendation systems, with a specific emphasis on music. Elad's research interests are wide-ranging and include machine learning, artificial intelligence, data mining, multiagent systems, and their applications across diverse domains such as bioinformatics and robotics. His academic journey has been marked by a commitment to bridging theory and practical application, enhancing understanding of complex systems. Throughout his career, he has received several accolades for his academic excellence, reflecting his contributions to the field.

Research Interests

Experience

Assistant Professor of Instruction

2021-01-01 — Present

University of Texas at Austin • Austin, TX

Teaching and research in various areas of Computer Science.

Applied Scientist

— Present

Amazon •

Working on research and application of machine learning in product development.

Awards

#

Dean’s Excellence Award

2012-09-01
#

Blavatnik School of Computer Science Excellence Prize

2012-06-01
#

Ruth Allen Ziegler Excellence Scholarship

2007-01-01
#

Makor Haim Award

2004-01-01

Requirements for University of Texas at Austin

Master Program
Requirements
GPA Requirement
Required:3
GRE General
TOEFL
Total
Required:79
IELTS
Overall
Required:6.5
Prerequisites
Bachelor's degree from a regionally accredited institution
Application Checklist
  • Online application
  • Application fee
  • Official transcripts
  • Statement of Purpose
  • Three letters of recommendation
  • CV/Resume
Specialization Notes

General requirements for the Graduate School at UT Austin apply to all programs unless otherwise specified.