Profileimage by Konstantinos Lampridis Artificial Intelligence expert from Amsterdam

Konstantinos Lampridis

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Last update: 09.10.2017

Artificial Intelligence expert

Graduation: Msc Artificial Intelligence UvA Amsterdam
Hourly-/Daily rates: show
Languages: English (Full Professional) | French (Limited professional) | Greek (Native or Bilingual)

Keywords

Programming Machine Learning Data Scientist Computer Vision Artificial intelligence natural language processing NLP Pattern Recognition neural networks Data Science C Big Data Software Development Software Engineering Business Intelligence Data Analysis Matlab Python Java SQL Deep-learning

Attachments

Konstantinos_Lampridis_resume.pdf

Skills

  • Knowledge
    • Machine Learning,
    • Natural Language Processing
    • Reinforcement Learning
    • Computer Vision
    • Bayesian and Causal Inference
    • Evolutionary Algorithms
    • Multi Agent Systems
    • Information Retrieval
    • Object Oriented Programming
    • Software Engineering
    • Game Theory
    • Statistics
    • Econometrics
  • Skills
    • Unix systems
    • python, java, perl, matlab, c, prolog, fortran, sql, r
    • git - version control
    • innovative mind
  • Academic experience
    • used Neural Networks for image classification
    • 3D image reconstruction from 2D motion
    • built an NLP system that predicts whether a quote is memorable or not
    • used Conditional Random Fields for image denoising
    • some experience with Ethereum and solidity programming
    • simulated the functionality of a beehive using the BDI agent development framework (computational intelligence)

Project history

  • 4 month internship at Textkernel BV, Amsterdam
    • Augmented Textkernel’s main product, Extract!, a CV (resume) parsing
      software, by building a computational model trained for the Greek language
      surpassing competition worldwide in performance
    • Trained Hidden Markov and Conditional Random Field ML models, was
      responsible for NLP related tasks such as feature engineering and token
      normalization, enhanced the in-house ontology with domain knowledge
       

Time and spatial flexibility

Leaving in Asmterdam

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