Dominik Filipiak

Data Scientist, Academic Teacher

Department of Information Systems

Poznań University of Economics and Business


Majored in Computer Science, now doing two PhDs (Computer Science and Economics/Business Information Systems) and BSc in Mathematics – a mixture of technical experience and theoretical background. Has hands-on experience with collecting data sets from scratch, building ML models, transferring them to code and inferring new findings. Interested in doing new and exciting things connected to AI, Data Science, Machine Learning, Computer Vision, and Big Data. Preferably in Python, R, or Java.

Keywords: Artificial Intelligence, Machine Learning, Computer Vision, Digital Humanities, Quantitative Analysis, Big Data, Alternative Investments
Fig. 1. Wilhelm Sasnal, poster project for the movie Afterimage (2016)

1. Introduction

My personal interests encapsulate (in random order): machine learning, computer vision, big data, philosophy, art market, software development, literature, modern and contemporary art, music, foreign languages, pure mathematics, architecture, and politics. Perhaps more relevant data on me are placed below.

Table 1. Tertiary education
t degree course & university
2018–now PhD Computer Science
Universität Innsbruck
2018–now BSc Mathematics
Adam Mickiewicz University in Poznań
2014–now PhD Information Systems (Economics)
Poznań University of Economics and Business
2013–2014 MScEng Computing, with distinction
Poznań University of Technology
2009–2013 BEng Information Engineering
Poznań University of Technology

2. Professional Experience

Department of Information Systems. Sep 2011–now, position: Data Scientist, Academic Teacher. Responsibilities: carrying out research, mostly connected to data science and machine learning (in domains such as art markets, telecommunications, and maritime surveillance), software development (Python, R, Java) for research and commercial purposes as well, planning scientific projects and writing proposals, maintaining the department's infrastructure (physical and virtual servers and clusters, networking), teaching undergraduate and postgraduate students (courses on machine learning, artificial intelligence, big data, software architecture, cryptography).

$$Y=\lambda f.(\lambda x.f\ (x\ x))\ (\lambda x.f\ (x\ x))$$

NSense (now F-Secure). August 2011–September 2011, position: Software Developer (intern). Responsibilities: Development of a vulnerability scanner in C#.

$$e^{i\pi }+1=0$$ Verax Systems, March 2010–July 2010, position: Junior Linux Administrator (intern). Responsibilities: Researching and enrolling technologies related to LDAP protocol in the existing systems architecture (CentOS authentication, SMB, Radius, Postfix et cetera).

3. Skills, Awards, and Certificates

Technical Skills. Machine learning, statistical analysis, image processing, data crawling and wrangling, software development (Python, Java, R), software architecture (UML, design patterns), linux, big data (Apache Spark), databases (SQL, NoSQL, SPARQL).

Languages. Polish (native), English (fluent – C1, CAE certificate), French (beginner – A2), and very elementary Dutch and Russian.

Table 2. Awards and certificates
t award description
2018 Best Paper Award 4th Workshop on Semantic Deep Learning (SemDeep-4) collocated with the 17th International Semantic Web Conference, for the paper Semantic Image-Based Profiling of Users' Interests with Neural Networks
2018 Best Paper Award The 8th International Tech-Science Conference NATCON "Naval Technologies for Defence and Security", for the paper Big Data for Anomaly Detection in Maritime Surveillance: Spatial AIS Data Analysis for Tankers (waiting for publication)
2017 Research Grant Microsoft Azure for Data Science Research Grant, for the project Data Science for Improving the Quality of Art Market Data
2016 Best Paper Award 19th BIS Conference in Leipzig, Germany, for the paper Quantitative Analysis of Art Market Using Ontologies, Named Entity Recognition and Machine Learning: A Case Study (see Section 5)
2014 Certificate CAE Certificate in Advanced English (CEFR C1)

5. Media Appereance

Selected, mostly in Polish.
  1. - Sztuczna Inteligencja dla Sztuki
  2. Życie UAM - Debata Akademicka o Sztucznej Inteligencji

6. Bibliography

Perhaps outdated! See references for my Google Scholar profile. Anyhow, here's some of them (clickable):

  1. Stróżyna, M., Eiden, G., Abramowicz, W., Filipiak, D., Małyszko, J., Węcel, K., 2018, A framework for the quality–based selection and retrieval of open data – a use case from the maritime domain, Electronic Markets, 28, s. 1–15.
  2. Filipiak, D., Perkowski, B., Filipowska, A., 2017, User Authentication with Neural Networks Based on CDR Data, NetMob 2017: Book of Abstracts. Poster, s. 57–59.
  3. Filipiak, D., Agt-Rickauer, H., Hentschel, C., Filipowska, A., Sack, H., 2016, Quantitative Analysis of Art Market Using Ontologies, Named Entity Recognition and Machine Learning: A Case Study, Lecture Notes in Business Information Processing, 255, s. 79–90.
  4. Stróżyna, M., Małyszko, J., Węcel, K., Filipiak, D., Abramowicz, W., 2016, Architecture of Maritime Awareness System Supplied with External Information, Annual of Navigation, 23, s. 135–149.
  5. Filipiak, D., Filipowska, A., 2016, Towards Data–Oriented Analysis of the Art Market: Survey and Outlook, e–Finanse, 12 (1), s. 21–31.
  6. Mucha, M., Filipiak, D., Filipowska, A., 2015, Evolving classification based on CDR–derived behavior patterns, Net Mob 2015 : Book of Abstracts :: Posters, s. 76–78.

7. References

  1. Department of Information Systems
  2. LinkedIn
  3. Research Gate
  4. GitHub
  5. Google Scholar
  6. Scopus
  7. ORCID
  8. Web of Science
© 2017, Dominik Filipiak.