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AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
TSP-AI-cup
August 7, 2021 – August 7, 2021
Local search solver for TSP instances (AI Cup 2012 - University of Lugano)
View Projectyiannislamprou.github.io
December 1, 2019 – Present
yiannislamprou.github.io — GitHub repository
View ProjectGauss-Jordan
October 4, 2019 – October 4, 2019
Gauss-Jordan (KJI variation) implementation via MPI - University project
View ProjectFastDiskEvacuation
September 7, 2018 – September 7, 2018
Experimental computations for strategies in "Fast Two-Robot Disk Evacuation with Wireless Communication" by Lamprou, Martin, Schewe
View ProjectAvgRWA
February 26, 2018 – July 17, 2018
Experiments for Cover Time in Edge-Uniform Stochastically-Evolving Graphs, I. Lamprou, R. Martin, P. Spirakis, Algorithms, 11(10), 149, 2018.
View Projecttrie
June 5, 2015 – June 7, 2015
Trie trees case study on Leon (Scala) - University project
View ProjectCultural Fit Analysis
The candidate's project history shows a strong academic and research-oriented background, with a focus on algorithms and scientific computing. The diversity of technologies and project types (personal, university, research) suggests adaptability and a willingness to explore different domains. However, without specific information on team roles or project outcomes, it's difficult to fully assess cultural fit for a collaborative industry role. The projects align with a data scientist's analytical and algorithmic needs, but lack explicit data science project examples (e.g., machine learning model development, data pipeline construction, statistical analysis of large datasets).
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise and technical, but do not provide insight into collaboration, problem-solving approach, or communication style in a team setting.