About me

Everything you want to know but were afraid to ask


A mixture of a strong software engineer, enthusiastic researcher and reputable leader. Software development is my passion as well as programming, designing architecture and planning flows . My mission is to deliver maintainable and scalable solutions using the most efficient workflows. In summary, I love the ability to build a functional system from nothing and have it be the best quality product.


II 2019 – present IAMIP Sverige AB – cto
  • Product Development Management
  • Business Management and Strategy
  • Team Management and Talent Retention
I 2017 – II 2019 PayBreak Ltd. (now Etika) – data & analytics architect
  • Machine Learning & AI
  • Python, AWS Lambda
  • SQL (MySQL), MongoDB
  • Tableau
  • Agile, Scrum
  • Open Source projects
  • PHP - OOP, Clean Architecture
X 2013 – XII 2016 PayBreak Ltd. (now Etika) – senior developer / scrum master
  • PHP - OOP, Clean Architecture
  • Laravel 5.0 & 4.2
  • Git, GitHub
  • Agile, Scrum
  • MySQL, MongoDB
  • Scrutinizer CI, Travis CI
  • Open Source projects
X 2011 – IX 2013 Black on White sp. z o.o. – technical director
  • PHP - OOP
  • Git, GitHub
  • MySQL
  • Smarty, jQuery, Bootstrap
  • E-commerce
  • SEO, eMarketing
  • Photography
VII 2010 – X 2011 Multideco.pl – IT manager
  • E-commerce
  • SEO, eMarketing
  • PHP - OOP
  • MySQL
  • Smarty, jQuery, Bootstrap
  • Photography
III 2010 – VI 2010 Partydeco.pl – webmaster, PHP and MySQL developer
2004 – 2010 Freelancer – webmaster/designer, PHP and MySQL developer


2021 – 2023 The West Pomeranian Business School, Executive MBA
2005 – 2010 West Pomeranian University of Technology Szczecin, Faculty of Computer Science, MSc Eng
2002 – 2005 XIV High School in Szczecin


An investment strategy based on the first derivative of the moving averages difference with parameters adapted by machine learning

Antoni Wilinski, Mateusz Sochanowski, Wojciech Nowicki Data Science in Finance and Economics, 2022, 2(2): 96-116. doi: 10.3934/DSFE.2022005
The article presents a certain investment strategy based on the difference between two moving averages, modified to allow the extraction of patterns. The strategy concept dropped the traditionally considered intersections of two averages and opening positions just after those intersections. Based on the observation of changes happening in the moving averages difference, it has been noticed that for some values of this difference and some values of additional strategy parameters, an interesting pattern appears that allows short-term prediction. These patterns also depended on the first derivative of the moving averages difference and the location of the current price relative to certain thresholds of the difference. Therefore, the strategy uses five parameters, including Stop Loss, adapted to the properties of the time series through machine learning. The importance of machine learning is highlighted by comparing simulation results with and without it. The strategy effectiveness was tested in the Matlab environment on the time series of the WIG20 (primary index of the Warsaw Stock Exchange) historical data. Satisfactory results were obtained considered in terms of minimizing investment risk measured by the Calmar indicator. on-line

Investment funds management strategy based on polynomial regression in machine learning

A. Wiliński, A. Smoliński, W. Nowicki Intelligent Systems for Computer Modelling: Proceedings of the 1st European-Middle Asian Conference on Computer Modelling 2015, EMACOM 2015
This paper presents the results of an investment strategy simulation. The strategy is based on common regression models in a time series, which yields the decision. A simple polynomial regression was the basic method used to achieve short-term value forecasts in the time series. Base params (number of steps in the past and a degree of a polynomial) were set based on a machine learning algorithm. The strategy is improved with some additional original (constitutes by the authors) parameters because using only the regression proved to be completely ineffective. Financial markets with bidirectional transactions (long and short transactions), as well as only long transaction markets, were both taken under research. on-line

Process of market strategy optimization using distributed computing systems

W. Nowicki, A. Bera, P. Błaszyński
Management and Production Engineering Review, volume 6, number 4, December 2015
If market repeatability is assumed, it is possible with some real probability to deduct short term market changes by making some calculations. The algorithm, based on logical and statistically reasonable scheme to make decisions about opening or closing position on a market, is called an automated strategy. Due to market volatility, all parameters are changing from time to time, so there is need to constantly optimize them. This article describes a team organization process when researching market strategies. Individual team members are merged into small groups, according to their responsibilities. The team members perform data processing tasks through a cascade organization, providing solutions to speed up work related to the use of remote computing resources. They also work out how to store results in a suitable way, according to the type of task, and facilitate the publication of a large amount of results. Read Article

Study on the Effectiveness of the Investment Strategy Based on a Classifier with Rules Adapted by Machine Learning

A. Wiliński, A. Bera, W. Nowicki, P. Błaszyński
ISRN Artificial Intelligence, Vol. 2014
Paper examines two transactional strategies based on the classifier which opens positions using some rules and closes them using different rules. A rule set contains time-varying parameters that when matched allow to make an investment decision. Researches contain the study of variability of these parameters and the relationship between learning period and testing (using the learned parameters). The strategies are evaluated based on the time series of cumulative profit achieved in the test periods. The study was conducted on the most popular currency pair EURUSD (Euro - Dollar) sampled with interval of 1 hour. An important contribution to the theory of algotrading resulting from presented research is specification of the parameter space (quite large, consisting of 11 parameters) that achieves very good results using cross validation. Read Article

Meaning of simple rules in investment strategies of algorithmic trading

A. Wiliński, P. Błaszyński, A. Bera, W. Nowicki, K. Buda
Materiały IV Konferencji Technologia Edukacja Wiedza Innowacja, 24 IX 2013
In article are shown studies of the possibly simplest investment strategy of algo trading. The authors’ intention was to prove the thesis that in the greedy algorithmic trading directed to the proper response, not to forecast, there are almost always opportunities to achieve profit. This paper presents the results of tests for over twenty core markets - currency pairs, indices and commodities (eight results included). Introduced the original concept of quadrant of openings on each bar. In principle, the strategy is not relevant investment (studies were conducted without transaction costs), only cognitive in order to develop.

Organizacja zespołowego procesu optymalizacji parametrów strategii rynkowych

W. Nowicki, A. Bera
Modele inżynierii teleinformatyki, t. 8., p. 199-206, 2013 Read Article (in polish)

Wizualne gesty użytkownika w sterowaniu prezentacją

W. Nowicki, A. Nowosielski
Metody Informatyki Stosowanej, Nr 2/2011 (27), p. 97-103, 2011
In the article the problem of visual gesture recognition for presentation steering is presented. Based on camera image analysis the idea of steering is proposed. Presented system operates without a specialized controller and bases on visual gestures of the presenter. Conducted experiments with users demonstrated high usability of the system. Read Article (in polish)