- Przemysław Biecek, PhD, DSc (Team Leader)
- Hubert Baniecki, MSc student
- Mustafa Cavus, PhD
- Maciej Chrabąszcz, MSc student
- Adrianna Grudzień, BSc student
- Mateusz Grzyb, BSc
- Stanisław Giziński, MSc student
- Weronika Hryniewska, PhD student
- Anna Kozak, MSc
- Adam Kozłowski, MSc
- Mateusz Krzyziński, BSc student
- Stanisław Łaniewski, PhD student
- Piotr Piątyszek, BSc student
- Hubert Ruczyński, BSc student
- Barbara Rychalska, PhD student
- Nuno Sepúlveda, PhD
- Bartek Sobieski, BSc student
- Tomasz Stanisławek, PhD
- Hoang Thien Ly, BSc student
- Paulina Tomaszewska, PhD student
- Jakub Wiśniewski, BSc
- Emilia Wiśnios, MSc student
- Katarzyna Woźnica, PhD student
- Piotr Czarnecki, MSc
- Alicja Gosiewska, MSc
- Maria Kałuska, BSc student
- Marcin Kosiński, MSc
- Wojciech Kretowicz, BSc
- Michał Kuźba, MSc
- Szymon Maksymiuk, BSc
- Tomasz Mikołajczyk, PhD
- Katarzyna Pękala, MSc
- Adam Rydelek, BSc
- Bartosz Sawicki, BSc student
- Michał Sokólski, MSc
- Szymon Szmajdziński, BSc student
- Zuzanna Trafas, BSc student
- Kinga Ułasik, BSc student
- Anna Wróblewska, PhD
- Hanna Zdulska, BSc
- Artur Żółkowski, BSc student
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
Master’s student in Data Science at Warsaw University of Technology. Developing and maintaining open-source Python & R packages for explainability of predictive models. Researching explainable machine learning, responsibility, evaluation and adversarial attacks.
Google Scholar: H72DRC0AAAAJ
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
Master’s student in mathematical statisctics at Warsaw University of Technology. Interested in deep learning on text and images, explainable and responsible AI.
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
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
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
Graduated in Computer Science at ICM at the University of Warsaw. Currently working in a lab as Research Software Engineer in xLungs. Interested in image processing, deep learning on medical images, and computation acceleration.
BSc student in Data Science at Warsaw University of Technology. Interested in explainable artificial intelligence, machine learning on graphs and data visualization.
Google Scholar: i_r7EUgAAAAJ
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
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.
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
BSc student in Mathematics and Data Analysis at Warsaw University of Technology. Interested in deep learning and hyperparameter optimization.
BSc student in Data Science at Warsaw University of Technology. Interested in explainable artificial intelligence, data vizualization and survival analysis.
PhD candidate in computer science at Warsaw University of Technology. Mainly interested in deep learning for natural language processing (NLP).
Google Scholar: gq8NY_UAAAAJ
BSc student in Data Science at the Warsaw University of Technology. Interested in exploring various explanation methods for image classification models and visualizing the results.
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.
Google Scholar: eO245iMAAAAJ
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
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
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.
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
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.
A BSc Data Science student at Warsaw University of Technology. Interested in artificial intelligence, data visualization and metaheuristic optimization.
Works towards Bachelor’s degree in Data Science at Warsaw University of Technology. Interested in Maching Learning, Neural Networks and Fairness.