The Team

Members

Collaborators

Alumni

  • Piotr Czarnecki, MSc
  • Alicja Gosiewska, MSc
  • Adrianna Grudzień, BSc
  • Maria Kałuska, BSc
  • Marcin Kosiński, MSc
  • Adam Kozłowski, MSc
  • Wojciech Kretowicz, BSc
  • Michał Kuźba, MSc
  • Szymon Maksymiuk, BSc
  • Tomasz Mikołajczyk, PhD
  • Katarzyna Pękala, MSc
  • Adam Rydelek, BSc
  • Bartosz Sawicki, BSc
  • Patryk Słowakiewicz, BSc
  • Michał Sokólski, MSc
  • Mateusz Stączek, BSc
  • Szymon Szmajdziński, BSc
  • Zuzanna Trafas, BSc
  • Kinga Ułasik, BSc
  • Anna Wróblewska, PhD
  • Hanna Zdulska, BSc

Przemysław Biecek

My personal mission is to enhance human capabilities by supporting them through access to data-driven and knowledge-based predictions. I execute it by developing methods and tools for responsible machine learning, trustworthy artificial intelligence and reliable software engineering.

I work as an associate professor at Warsaw University of Technology and the University of Warsaw. I graduated in software engineering and mathematical statistics and now work on model visualisation, explanatory model analysis, predictive modelling and data science for healthcare. In 2016, I formed the research group MI² which develops methods and tools for predictive model analysis.

Google Scholar: Af0O75cAAAAJ

GitHub: pbiecek

LinkedIn: pbiecek

Mariusz Adamek

I work at two Medical Universities (Silesia and Gdańsk) holding a Professorship in Medicine and Health Sciences. My interests are focused on lung cancer prevention and screening, the latter by means of low-dose computed tomography (LDCT) with special emphasis put on molecular biology methods, prediction models and image analysis aimed to enhance the performance of lung screening outcomes.

Website: www.mariuszadamek.io

Hubert Baniecki

I’m a PhD student in Computer Science at the University of Warsaw. I previously did my MSc (2022) and BSc (2021) in Data Science at Warsaw University of Technology. My main research interest is explainable machine learning, with particular emphasis on adversarial attacks & evaluation of explanations. I care about human-model interaction with applications in biomedicine. I support the development and maintenance of several open-source Python & R packages for building predictive models responsibly.

Website: hbaniecki.com

Mustafa Cavus

I work as an assistant professor at Warsaw University of Technology and the Eskisehir Technical University. I joined the MI² DataLab as a post-doc researcher in 2021. I work on explainable artificial intelligence and AutoML.

Google Scholar: I63d1WIAAAAJ&hl

GitHub: mcavus

LinkedIn: mcavus

Twitter: mcavus

Julian Sienkiewicz

I work as an assistant professor at Faculty of Physics, WUT. My main research area links with sociophysics, complex networks and agent-based models. In the scope of MI² DataLab I follow my other interest - scientometrics.

Google Scholar: mIwu11QAAAAJ

LinkedIn: julek-sienkiewicz-873829

Maciej Chrabąszcz

Master’s student in mathematical statisctics at Warsaw University of Technology. Interested in deep learning on text and images, explainable and responsible AI.

GitHub: maciejchrabaszcz

LinkedIn: maciej-chrabaszcz

Stanisław Giziński

A Research Software Engineer and student of Machine Learning at Faculty of Mathematics Informatics and Mechanic, University of Warsaw. His work in the lab focuses on using natural language processing and network analysis to better understand the spread of AI public policies. Interested also in applying machine learning in bioinformatics.

Google Scholar: Stanisław Giziński

GitHub: Gizzio

LinkedIn: stanislaw-gizinski

Mateusz Grzyb

MSc student in Data Science at Warsaw University of Technology. Interested in artificial intelligence and scientific computing, but above all simply enjoys programming.

GitHub: mgrzyb99

Weronika Hryniewska

PhD candidate in computer science at Warsaw University of Technology. Interested in deep learning modelling on medical images in the context of explainability and responsible AI.

Google Scholar: aJeg3IQAAAAJ

GitHub: Hryniewska

LinkedIn: weronikahryniewska

Piotr Komorowski

Master’s student in Machine Learning at the University of Warsaw. Mainly interested in image processing and XAI applied to medical images.

GitHub: piotr-komorowski

LinkedIn: Piotr-Komorowski

Anna Kozak

Graduated in mathematical statistics at Warsaw University of Technology. Interested in explainable artificial intelligence and data visualization. Organizes projects related to education.

Google Scholar: JIrqf9kAAAAJ

GitHub: kozaka93

LinkedIn: kozakanna

Mateusz Krzyziński

MSc student in Data Science at Warsaw University of Technology. Interested in explainable artificial intelligence, with particular emphasis on XAI methods for survival analysis models and XAI applications in the medical field. Also an enthusiast of data visualization.

Google Scholar: i_r7EUgAAAAJ

GitHub: krzyzinskim

LinkedIn: krzyzinskim

Tymoteusz Kwieciński

BSc student in Data Science at Warsaw University of Technology. Particularly interested in explainable artificial intelligence, computer vision and NLP.

GitHub: Fersoil

LinkedIn: Tymoteusz-Kwieciński

Stanisław Łaniewski

PhD student in Quantitative Psychology and Economics at University of Warsaw, Machine Learning Researcher at MI2 Data Lab, Msc in Actuarial Science and Mathematical Finance at University of Amsterdam, former Quantitative Researcher at Flow Traders His research focuses on enhancing classical methods used in discrete choice and finance with machine learning and how to apply them to explain behavioral phenomena and heuristics. He is also keen on finding balance between best predictive models and their explainability. Avid gamer who applies statistical techniques to deepen the understanding of best strategies

LinkedIn: Stanisław-Łaniewski

Piotr Piątyszek

Undergraduate Data Science student at Warsaw University of Technology. Works as a research software engineer on enhancing accessibility and completeness of explainable AI. During pandemic contributes to a system of monitoring covid variants.

Github: piotrpiatyszek

Bartosz Pieliński

I am an Assistant Professor at the Faculty of Political Science and International Studies at Warsaw University. I am interested in applying quantitative methods to study public policies. I am a founding member of the Institutional Grammar Research Initiative, which is focused on developing a new way of analysing social rules. I have participated in several research projects covering social policy, non-profit organizations, social enterprises, and international organizations.

Website: https://pielinski.info/

Google Scholar: hnWiaVEAAAAJ

LinkedIn: Bartosz Pieliński

Hanna Piotrowska

Information designer, focusing mainly on data visualization, branding and book design, with a strong interest in Data Science and perception studies. Winner of numerous awards, including The Kantar Information Is Beautiful Awards, HOW International Design Awards, Polish Graphic Design Awards and KTR.

LinkedIn: hanna-piotrowska

Twitter: hannapio

Behance: hannapio.

Hubert Ruczyński

I am working towards Masters’s degree in Data Science at Warsaw University of Technology. I am also teaching students about data exploration and visualisation. My major interests are: AutoML | Natural Language Processing | Data Visualization | Fairness.

GitHub: HubertR21

LinkedIn: Hubert Ruczyński

Barbara Rychalska

PhD candidate in computer science at Warsaw University of Technology. Mainly interested in deep learning for natural language processing (NLP), recommender systems and graph-based learning.

Google Scholar: Wp0wHJoAAAAJ

LinkedIn: Barbara-Rychalska

Bartek Sobieski

MSc student in Data Science at Warsaw University of Technology. Interested in deep learning and hyperparameter optimization.

GitHub: sobieskibj

LinkedIn: Bartłomiej-Sobieski

Mikołaj Spytek

MSc student in Data Science at Warsaw University of Technology. Interested in explainable artificial intelligence, data vizualization and survival analysis.

Google Scholar: 1u49AqYAAAAJ

GitHub: mikolajsp

LinkedIn: Mikołaj-Spytek

Tomasz Stanisławek

PhD candidate in computer science at Warsaw University of Technology. Mainly interested in deep learning for natural language processing (NLP).

Google Scholar: gq8NY_UAAAAJ

GitHub: tstanislawek

LinkedIn: Tomasz-Stanisławek

Paulina Tomaszewska

PhD candidate in Computer Science at Warsaw University of Technology. Gained experience in AI at leading universities during: Deep Learning Summer School at Tsinghua University (China), one-semester exchange at Nanyang Technological University (Singapore) and research internships at Gwangju Institute of Science and Technology (South Korea) and Institute of Science and Technology (Austria). Mainly interested in Deep Learning, Computer Vision and Transfer Learning. Recently, focused on digital pathology.

Google Scholar: eO245iMAAAAJ

LinkedIn: paulina-tomaszewska

Hoang Thien Ly

Bachelor student in Maths and Data Analysis at Warsaw University of Technology. Interested in working with data, and learning explainable artificial intelligence methods.

Google Scholar: JkysewYAAAAJ

GitHub: lhthien09

LinkedIn: hthienly

Piotr Wilczyński

BSc student in Data Science at Warsaw University of Technology. Interested in ontologies, semantic similarity, hyperparameter optimization and NLP.

GitHub: wi1lku

LinkedIn: Piotr-Wilczyński

Jakub Wiśniewski

Research Software Engineer and third year Data Science student at Warsaw University of Technology. Developer of tools for bias detection and fairness. Currently researching responsible applications of deep learning. President of Data Science Science Club at WUT.

Google Scholar: _6eQsXMAAAAJ

GitHub: jakwisn

LinkedIn: jakwisn

Emilia Wiśnios

Research Software Engineer and student of Machine Learning at Faculty of Mathematics, Informatics and Mechanics, University of Warsaw. Interested in natural language processing and reinforcement learning.

GitHub: emiliawisnios

LinkedIn: emilia-wisnios

Paweł Wojciechowski

Graduated with a bachelor’s degree in Data Science from Warsaw University of Technology. Interested in explainable artificial intelligence, computer vision, and active learning.

GitHub: p-wojciechowski

LinkedIn: wojciechowski-p

Katarzyna Woźnica

PhD candidate in computer science at Warsaw University of Technology. Graduated in mathematical statistics. Interested in automated machine learning especially in hyperparameter tuning for tabular data. Carrying statistical analysis and predictive modelling for healthcare.

Google Scholar: tAQS1gQAAAAJ

GitHub: woznicak

LinkedIn: woznicak

Vladimir Zaigrajew

PhD candidate in computer science at Warsaw University of Technology. Interested in deep learning, primarily on images, with a focus on representation learning.

GitHub: WolodjaZ

LinkedIn: vladimir-zaigrajew

Artur Żółkowski

BSc student in Data Science at Warsaw University of Technology. Interested in explainable artificial intelligence, computer vision and NLP.

GitHub: arturzolkowski

LinkedIn: Artur-Żółkowski