Dr. Tatjana Pavlenko

Professor

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Biography

Tatjana Pavlenko is a Professor in the Department of Statistics at Uppsala University. Her research interests are centered around statistical inference, applied probability in high-dimensional dimensions, and computational statistics, particularly Bayesian graph structure learning. She focuses on the detection and identification of sparse signals and works extensively with large-scale biomedical data. Her current research methodology revolves around the theory of mathematical statistics, with a specific emphasis on developing inferential and algorithmic procedures for complex datasets. Recently, she has gained an interest in the theoretical foundations of modeling and analyzing high-dimensional data and sparsity patterns. Her aim is to develop theory and tools for data-driven statistical learning algorithms. Uppsala University facilitates her involvement in AI4Research, a project driven by the advancements of Artificial Intelligence and machine learning. She supervises PhD students and actively engages in theoretical and practical applications of her research.

Research Interests

Experience

Professor

2017-08-01 — Present

Uppsala University • Uppsala, Sweden

Leads research in statistical inference and computational statistics, mentoring PhD candidates and developing advanced statistical algorithms.

Requirements for Uppsala University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:5.5
Reading
Required:5.5
Writing
Required:5.5
Speaking
Required:5.5
Overall
Required:6.5
TOEFL
Writing
Required:20
Total
Required:90
Prerequisites
Bachelor's degree equivalent to a Swedish Kandidatexamen (180 ECTS) 90 credits in a subject relevant to the specific program
Application Checklist
  • Bachelor's degree certificate and diploma
  • Official transcripts of records
  • Proof of English proficiency
  • Copy of passport photo page
  • Statement of Purpose (for most programs)
  • Curriculum Vitae (CV)
  • Application Summary Sheet (if required by department)
Specialization Notes

General Master's requirements applying across Science, Technology, and Humanities departments.