The Vienna PhD School of Informatics (VPSI) is a highly competitive, researchoriented graduate program that expects applicants to provide a strong letter of recommendation (LoR). The letter is a decisive component of the application packet because it offers admissions committees insight into the candidates academic abilities, research potential, and personal qualities that are not evident from transcripts or CVs alone.
Admissions committees read dozens of applications and rely on the LoR to answer questions such as:
A wellwritten recommendation provides concrete examples that illustrate these points and helps differentiate the applicant from other qualified candidates.
VPSI prefers letters from individuals who have supervised the applicants recent academic or research work. Ideal recommenders include:
Letters from family members, personal acquaintances, or generic character references are not considered appropriate.
A recommendation for VPSI should cover the following areas, each supported by specific evidence:
Describe the applicants performance in relevant courses, highlighting grades, the difficulty of the material, and any outstanding achievements (e.g., topranked projects, published course work). Mention analytical abilities, problemsolving skills, and familiarity with foundational concepts such as algorithms, data structures, or machine learning.
Detail any research projects the applicant participated in: the goals, methodology, the applicants specific contributions, and outcomes (publications, presentations, or software artifacts). Emphasize originality, independence, and the capacity to formulate research questionsqualities essential for a doctoral trajectory.
List programming languages, tools, and platforms the candidate mastered, especially those relevant to informatics (e.g., Python, Java, C++, SQL, TensorFlow, ROS). Cite concrete instances where these skills were applied to solve challenging problems.
Provide examples of the applicants ability to present ideas clearlyboth in writing and orallyand to collaborate within a team. Mention contributions to group projects, leadership roles, or mentorship of junior members.
Discuss traits such as perseverance, creativity, critical thinking, and ethical conduct. Illustrate with anecdotes that reveal the applicants motivation and resilience in the face of setbacks.
Explain why the candidate is particularly suited for VPSI. Reference the schools research focus areas (e.g., data science, distributed systems, humancomputer interaction) and how the applicants interests align with ongoing faculty projects.
Academic performance: In the Advanced Algorithms course (CS521), Mr. Mller earned an A+ and ranked first among 45 participants. His final project, which explored novel graphpartitioning heuristics, demonstrated deep theoretical insight and produced code that was later incorporated into the departments opensource library.
Research potential: During his masters thesis, Ms. Novak designed a scalable datafusion pipeline for autonomous vehicles. She independently implemented the core sensorfusion module, resulting in a 30% reduction in latency compared with the baseline. Her work was presented at the IEEE International Conference on Robotics and Automation.
By providing a thorough, specific, and timely recommendation, you help the Vienna PhD School of Informatics identify candidates who have the expertise and drive to succeed in cuttingedge research. Thank you for contributing to the future of informatics.
