I am passionate about solving complex problems. One of the most sophisticated phenomena in the nature is human cognition. I studied the way human organism interacts with the surrounding environment both from the theoretical point of view and for practical applications. Along the way I also had to learned data science methods and programming. What I usually do is: I gather the data, I analyze them, I interpret the results, and I have fun doing so.
Behnke, M., Buchwald, M., Bykowski, A., Kupiński, S., & Kaczmarek, L. D. (2022). Psychophysiology of positive and negative emotions, dataset of 1157 cases and 8 biosignals. Scientific Data, 9(1), 1-15. doi: 10.1038/s41597-021-01117-0
Buchwald, M. (2021). Functional Magnetic Resonance Imaging Signal Modelling and Contrasts: an Example of Manual Praxis Tasks. Computational Methods in Science and Technology, 27(4), 159-167. doi: 10.12921/cmst.2021.0000033 [Project at GitHub]
Kroliczak, G., Buchwald, M., Kleka, P., Klichowski, M., Potok, W., Nowik, A.M., Randerath, J., Piper, B.J. (2021). Manual praxis and language-production networks, and their links to handedness. Cortex, 140, 110-127. doi: 10.1016/j.cortex.2021.03.022 [Project at Open Science Foundation][Python Jupyter Notebook]
Buchwald, M., Przybylski, L., Kroliczak, G. (2018). Decoding Brain States for Planning Functional Grasps of Tools: A Functional Magnetic Resonance Imaging Multivoxel Pattern Analysis Study. Journal of the International Neuropsychological Society. 24, 1013-1025. doi: 10.1017/S1355617718000590
Jukiewicz, M., Buchwald, M., & Cysewska-Sobusiak, A. (2018). Finding Optimal Frequency and Spatial Filters Accompanying Blind Signal Separation of EEG Data for SSVEP-based BCI. International Journal of Electronics and Telecommunications, 64. doi: 10.24425/123543 [PDF]
Buchwald, M., & Jukiewicz, M. (2017). Project and evaluation EMG/EOG human-computer interface. Przegląd Elektrotechniczny (Electrotechnical Review), 93, 128-131. doi: 10.15199/48.2017.07.28 [PDF][Project at GitHub]
[Biomedical Data Scientist] ECBiG-MOSAIC – European Center for Bioinformatics and Genomics — Multiomics clinical research platform (infrastructure) (2021–present). [Project web page]. Funding: European Funds, Polish Governmental Programme & Partner’s funds, in total: 250M PLN (~$60M).
[Research specialist] PosEmo – An automatic tool for estimating person’s engagement and emotional valence based on camera video (March 2022–present). [posemo.io]. Funding: Polish National Research and Development Center grant TANGO-5-A/0051/2021: 247.5K PLN (~$50k).
[MA/PhD student] Manual Skills, Handedness and the Organization of Language in the Brain: Interrelations between the Planning of Tool Use, Gestures and Concepts (2015–2017). [OSF project][Jupyter IPython Notebook][Python module at GitLab]. Funding: National Science Center in Poland grant Maestro 2011/02/A/HS6/00174 awarded to G. Kroliczak, Adam Mickiewicz University in Poznań: 3M PLN (~$820K).
[Data analysis, Web & Mobile apps development] PELOSHA: Personalizable services for supporting healthy aging (2018–present). Funding: EU Commission Program AAL, Poznań Supercomputing and Networking Center: 3.08M € (~$3.77M).
[Data management, Co-lead] POPANE DATASET – Psychophysiology Of Positive And Negative Emotions (2020–2022). Lead: Maciej Behnke, Adam Mickiewicz University in Poznań. [Sci. Data publication ][OSF project]
Certificates and awards
Buchwald, M. (2022). The human face of technology: empowering psychology with AI (in Polish). Impact’22. https://www.youtube.com/watch?v=cu22vD9KXho
Buchwald, M., Nowik, A., Króliczak, G. (2019). What planning interactions with tools can tell us about bimanuality: an fMRI study. Poster presented at the 14th International Congress of the Polish Neuroscience Society, Katowice.
Buchwald, M., Kupiński, S., Bykowski, A., Marcinkowska, J., Ratajczyk, D., & Jukiewicz, M. (2019). Electrodermal activity as a measure of cognitive load: a methodological approach. Presentation at 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) (pp. 175-179). doi: 10.23919/SPA.2019.8936745
Jukiewicz, M., Buchwald, M., & Czyż, A. (2019). Optimizing SSVEP-based brain-computer interface with CCA and Genetic Algorithms. Presentation at 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) (pp. 164-168). doi: 10.23919/SPA.2019.8936758
Buchwald, M. (2018). Analyzing functional magnetic resonance (fMRI) data with machine learning algorithms. PyConPl’18. https://www.youtube.com/watch?v=2gKEWv8kpbo
Buchwald, M., Przybylski, Ł. & Króliczak, G. (2016). Planning functionalgrasps of tools vs. Non-tools: decoding conditions from brain activity. Poster presented at 22nd Annual Meeting of the Organization for Human Brain Mapping, Geneva, Swizz Confederation.