Hi, I’m Maciej and I’m experienced machine learning scientist, engineer and technical leader with over 8 years of academic and industry experience developing and deploying advanced Artificial Intelligence (AI) and Computer Vision (CV) systems.
I have a proven track record in leading interdisciplinary teams, defining R&D strategiesand driving projects from research and prototyping to production deployment.
I’m author and co-author of more than 10 peer-reviewed publications with over 200 citations and with research interests spanning 3D computer vision, generative modeling and medical imaging.
Experience
I lead AI & CV team of engineers and scientists in pioneering industrial research and innovation in advanced AI solutions for medical imaging and fluid simulations.
I drive the end-to-end lifecycle of AI projects — from conceptualization and strategic planning to execution and deployment — ensuring each project aligns with overarching corporate goals and yields tangible impact in healthcare. Leveraging close collaboration with executive leadership, I set short- and long-term research and development roadmaps, identify high-potential innovation areas and maintain seamless cross-functional coordination with clinical experts, product teams and external partners.
My responsibilities include supervising research and development of cutting-edge AI algorithms for medical imaging, keeping best practices in data engineering and deployment of models and working alongside IP and Regulatory experts in preparation of patent filings and documentation for FDA & MDR certification process.
Beyond day-to-day operations, I nurture a culture of mentorship and professional growth, guiding mid- and junior-level engineers toward excellence.
Wrocław University of Science and Technology
Teaching Assistant
Feb 2019 - Sep 2022
https://www.pwr.edu.pl
Prepared and taught bachelor-level courses on topics such as machine learning and modelling differential equations. Helped with thesis supervision of bachelor and master-level students.
Co-led and was involved in research projects that resulted in 3 major scientific publications, including acceptance to ICML 2020.
Led and co-led several commercial projects that included discovering client needs, performing feasibility studies, defining project scope for PoC and MVP milestones, and conducting R&D work in areas of deep learning and computer vision.
Involved in journal-published research project in bioinformatics & machine learning areas.
In commercial projects worked on implementation, testing, and documentation as well as providing reports to clients.
Worked in Test Automation team. Created tools to automate the job of manual testers, wrote & refactored Python libraries, management the SVN code repository.
As an intern I learnt about mobile network architecture, worked with technical documentation from Nokia and Texas Instruments and wrote source code in C and Assembly.
Education
Wrocław University of Science and Technology
Ph.D. in Computer Science Machine Learning
2018 - 2022
- Cum laude
- Area of research: Deep learning, neural networks, representation learning, 3D computer vision
- Thesis ‘‘Representation learning on point cloud data with deep neural networks’’
B.Eng. & M.Sc. in Computer Science
2013 - 2018
- Specialization in Artificial Intelligence
- Thesis ‘‘Adaptation of BiGAN models for semi-supervised learning’’
Publications
- Chojnacki, J., Gajowczyk, M., Teklak K., Konopczyński, T., Zamorski, M., (2024). The comparison of 2D and 3D based models for the problem of plaque segmentation and coronary artery calcium scoring on non-contrast cardiac CT imaging. MICCAI 2024 Workshop on Computational Biomechanics for Medicine.
- Pałachniak, J., Luniak, P., Zamorski, M., Kierepka, M., Miller, K., (2024). Towards objective assessment of the accuracy of coronary artery segmentation. MICCAI 2024 Workshop on Computational Biomechanics for Medicine.
- Zamorski, M., Stypułkowski, M., Karanowski, K., , Trzciński, T., Zięba, M. (2022). Continual learning on 3D point clouds with random compressed rehearsal. Computer Vision and Image Understanding (CVIU)
- Stypułkowski, M., Kania, K., Zamorski, M., Zięba, M., Trzciński, T., Chorowski, J. (2021). Conditional Invertible Flow for Point Cloud Generation. Pattern Recognition Letters
- Spurek, P., Winczowski, S., Tabor, J., Zamorski, M., Zięba, M., Trzciński, T. (2020). Hypernetwork approach to generating point clouds. International Conference on Machine Learning (ICML)
- Zamorski, M., Zięba, M., Świątek, J. (2020). Generative Modeling in Application to Point Cloud Completion. International Conference on Artificial Intelligence and Soft Computing (ICAISC)
- Zamorski, M., Zięba, M., Świątek, J. (2020). Comparison of Aggregation Functions for 3D Point Clouds Classification. Intelligent Information and Database Systems (IIDS)
- Zamorski, M., Zięba, M., Klukowski, P., Nowak, R., Kurach, K., Stokowiec, W., Trzciński, T. (2020). Adversarial Autoencoders for Compact Representations of 3D Point Clouds. Computer Vision and Image Understanding (CVIU)
- Stypułkowski, M., Zamorski, M., Zięba, M., Chorowski, J. (2019). Conditional Invertible Flow for Point Cloud Generation. NeurIPS 2019 Workshop on Sets and Partitions
- Zamorski, M., Zdobylak, A., Zięba, M., Świątek, J. (2019). Generative Adversarial Networks: recent developments. International Conference on Artificial Intelligence and Soft Computing (ICAISC)
- Zamorski, M., Zięba, M. (2019). Semi-supervised learning with Bidirectional GANs. Intelligent Information and Database Systems (IIDS)
- Klukowski, P., Augoff, M., Zamorski, M., Gonczarek, A., Walczak, M. J. (2018). Application of Dirichlet process mixture model to the identification of spin systems in protein NMR spectra. Journal of biomolecular NMR
Selected Activity
ML in PL Conference
2022
- Presented poster ‘Continual learning on 3D point clouds with random compressed rehearsal‘.
ML in PL Conference (prev. PL in ML)
2019
- Gave the oral presentation ”Adversarial Autoencoders for Compact Representations of 3D Point Clouds”
- Co-conducted a full-day workshop ”Flow-Based Generative models”.
PL in ML - Polish View on Machine Learning Conference
2018
- Co-conducted a full-day workshop ”Practical Aspects of Generative Models” for 30 attendees as a part of one of the biggest Polish machine learning conferences.
TEDx Wrocław
2014, 2015, 2016
- Volunteer for TEDx Wrocław main events. Worked in an international group. Responsible for cooperating with the audio engineer and continuous service of a conference rooms sound systems.
AIESEC Wrocław University of Technology
2014 - 2015
- Leader of the team organizing work & travel in Lower Silesia region for foreign student volunteers.