Blog

This post summarizes 2019. Things I've done and what went well, what I've learned and what didn't go went.

In memory of Christodoulos K. Chatzidimitiou 1944-2019

I review (and implement an online version of) the paper "Data Outlier Detection using the Chebyshev Theorem" as a first paper in a series of paper reviews (and implementations) I would like to do on online (streaming) outlier detection algorithms.

This is a really short introduction on what is a (startup) mastermind group, some heuristics and way to structure it.

A fun project where I tried to create an RNN model with LSTMs to generate plausible paper titles from a small corpus of IEEE transactions paper titles.

An example on how to fit two well know equations for bacterial growth, modified Gompertz and Baranyi, using non-linear least-squares in R

Performing GraphQL queries (to GiHub) using a basic http.Client in Go

A short presentation of my new personal website

Sixteen (16) simple rules for building robust machine learning models. Invited talk for the AMA call of the Research Data Alliance (RDA) Early Career and Engagement Interest Group (ECEIG).

My presentation in ECESCON 2019. It contains advices and strategies from my first business attempt with Cyclopt PC.

An example of how one can calculate the running average and the running variance of a stream of numbers using redis, lua (and python in this example)

How and if collinearity or multicollinearity interferes with features selection and machine learning goals in general

In this post I explain how I use the "making the software more fragile in order to make it more robust” strategy by Yegor Bugayenko to robustify my node.js apps.

2018 is over and this post tries to summarize my personal and professional activities, what went well, what didn't and what I've learned this year.

Coarse-to-Fine Decoding for Neural Semantic Parsing paper summary

Some notes and takeaways from the Devit 2018 conference that took place in Thessaloniki on Monday, June the 11th, 2018 and that will also help my long-term memory.

Creating a mini-site for machine learning using R markdown and Github

This is a post I wrote for the S-CASE project blog. S-CASE or Scaffolding Scalable Software Services is an EU funded FP7 project I am currently working on as a technical coordinator.

So you are working in AngularJS, you are using the Bootstrap framework and the requirement is to create a dropdown button, which will include several (list) items and that a) is scrollable and b) is searchable because the menu items are many.

eCommerce in the Cloud book review

Tutorial on how to create an SSL/HTTPS server with Node.js and Expressjs

Explanation why I choose the MEAN stack for web application development

Inspired by the Introduction to Complexity course and the unit on Fractals, I though it would be fun to make a rough calculation of the fractal dimension of the Greek coastline using the box counting method.

2013 resolutions

My trip to Budapest

This is a short tutorial on how to fit data points that look like a sigmoid curve using the nls function in R

3rd place in the Pac-Man vs Ghost Competition at CEC 2011 with MsAriadne bot

My process for keeping up with bibliography

My trip to Rome

My participation in the IEEE ICDM content

Academia jokes

My ECAI 2010 paper entitled 'A NEAT Way for Evolving Echo State Networks'