Ioannis Lamprou
Data ScientistMember since June 25, 2026
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
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.