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Use the science of tomorrow

Our cutting-edge R&D team harnesses the power of Machine Learning, Computer Vision, Natural Language Processing, Augmented Reality, and software development to create futuristic solutions that streamline your and your clients business operations, reduce costs, and enhance the quality of products and services.
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Applying the latest scientific innovations to optimize and boost your business operations in the present

Major R&D areas
Artificial Intelligence
AI is aimed at creating a simulation of human intelligence by machines. Adopting it helps to fine-tune business forecasting, optimize research and development, fully automate or perform various functions at a lower cost and of higher quality.
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Machine Learning
Creating, deploying, and managing machine learning models used to solve a wide scope of problems, such as natural language processing, image recognition, fraud detection, and predictive maintenance. Created models can be customized for specific needs and integrated with other applications, enabling accurate and reliable results.
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Deep Learning
Neural networks, used in DL, self-learn based on existing data to find patterns and generate predictions about new data. This made already widely used computer vision, speech recognition, and natural language processing possible.
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Agumented Reality
Enhancing the real surrounding with computer-generated data drastically changes the way how idea testing, demos, training, manufacturing, business workflows and many other processes look like.
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Robotic Process Automation
RPA automates processes with software "bots" that learn and mimic human actions. This unburdens staff from tedious tasks and allows them to focus on more meaningful work. Embrace the digital workforce and improve efficiency with RPA.
Natural Language Processing
Natural language processing involves the use of artificial intelligence, machine learning, and linguistics to enable machines to identify and comprehend human language, which can be difficult due to exceptions, ambiguities, and contextual nuances.
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Recommender systems
Recommender systems are utilized across different industries to provide users with personalized recommendations based on their preferences, previous actions, ratings, and interests. By suggesting relevant content, they aim to boost sales and engagement.
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Computer Vision
Computer vision algorithms are used to recognize people, places, and objects to collect information, analyze it, and build innovative products. Computer vision solutions support process automation and informed decision-making based on the analysis of collected data.
Predictive modeling
Usage of statistical and machine learning algorithms to predict future events and behaviors based on historical data. Predictive modeling is used in various applications, identifying patterns and relationships beyond what is visible to the naked eye. The technique leverages aggregated data to provide insights enabling informed decisions based on accurate predictions about the future.
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Big data analysis
The combination of unstructured, semistructured, and structured data makes for a priceless asset to utilize in business and scientific operations. Big data brings together data from various sources and applications and its analysis enables uncovering hidden patterns to make better-informed decisions based on in-depth insights.
Amazon Web Services (AWS) and Microsoft Azure are cloud computing services meant for developing, testing, and deploying applications. Flexible and cloud solutions support the automation and optimization of mundane operations, contributing to faster decision-making and increased productivity.
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Data Processing
Data processing allows converting its given forms into usable structures, enabling extracting and organizing insights from carried-out operations, discovering dependencies, and seeing the bigger picture behind collected data.
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Audio processing
Artificial intelligence algorithms are used for audio signal processing, recognizing multiple sound categories and human languages. Machine learning solutions understand patterns, distinguish, and interpret sounds recorded by digital devices to be utilized in message dictation, voice communication, and numerous applications across industries.
R&D Consulting Services
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Case Studies

Applications of cutting-edge solutions

Our R&D team pushes the limits to create sci-fi solutions to the real-world problems of today
AI/Machine learning
Software Development
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The R&D Team

The Brains Behind Our Cutting-Edge Technology

Tomasz golan
Tomasz Golan
R&D Manager

Tomasz Golan, a Ph.D. holder in theoretical physics, has been working at NeuroSYS since 2017, focusing on computer vision and machine learning algorithms. With a background in particle physics, he has an extensive research history, including being a member of the T2K collaboration and receiving the 2016 Breakthrough Prize in Fundamental Physics. He has also contributed to the GENIE Neutrino Monte Carlo Generator and MINERvA collaboration, where he coordinated the Monte Carlo generators group and pioneered the use of machine learning for physics reconstruction. With over 50 scientific publications and presentations at international conferences, his expertise encompasses neutrino interactions, theoretical modeling, and automated validation systems.

Citations by 3,331 documents
Tomasz Cakala
Tomasz Cąkała
R&D Software Engineer

Tomasz Cąkała is a backend software developer with several years of experience in developing IT solutions, ranging from the development of computationally-oriented software to complex enterprise applications. His work has been primarily targeted at creating systems that facilitate robust and fast deployment of AI applications. Tomasz graduated from the University of Warsaw (M.Sc. in Applied Mathematics and B.Sc. in Computer Science). During his stay at the university, he has participated in many research projects, some of which have been published in peer-reviewed journals (most notably Genome Biology and Journal of Computational and Graphical Statistics).

Daniel Popek
Daniel Popek
Machine Learning Researcher

Daniel Popek is an experienced Machine Learning Engineer specializing in NLP, Computer Vision, Deep Learning, Social Media Analysis, and Voice Processing. With a background in both Data Science and Software Engineering, he has been applying deep learning algorithms to various tasks, training Computer Vision models, enhancing search engines, and designing data pipelines at NeuroSYS since August 2020. He holds a master's degree in Data Science and a Bachelor's degree in Computer Science from WUST, with a thesis focused on emotional style transfer of the human voice using deep generative models.

Jakub Jaszczuk
R&D Software Engineer

Jakub Jaszczuk is a double graduate of the Wroclaw University of Technology, holding degrees in computer science as an engineer and in applied computer science as a Master of Engineering. His master's thesis focused on COVID-19 epidemic modeling, comparing parameter estimation methods and evaluating Python language environments. He supports the team with programming tasks, including object tracking, environment mapping, human pose detection, and optimizing hardware solutions for efficient development.

Mikolaj Patalan
Mikołaj Patalan
Machine Learning Researcher

Mikołaj Patalan is a master's graduate in Automation and Robotics from the Technical University of Denmark, specializing in computer vision applications for robotics. Notably, he won the first edition of the Shell Eco-marathon Autonomous Challenge and worked on comparing localization methods for mobile robotics during his studies. With a track record of success, his expertise extends to machine learning and classical methods in computer vision. As a valuable member of the NeuroSYS team since March 2020, he actively contributes to various computer vision projects, demonstrating skills in image detection, segmentation, object positioning, place recognition, tracking, pose estimation, and point cloud processing.

Paweł Mielniczuk
Machine Learning Researcher

Paweł Mielniczuk is a highly skilled Machine Learning Researcher specializing in NLP and Computer Vision. With a master's degree in Data Science, he joined NeuroSYS in 2020, bringing a wealth of experience from the telecommunications and insurance industries. He excels in designing and implementing robust machine learning pipelines and application solutions from scratch, leveraging his expertise in Deep Learning and Python. His pragmatic problem-solving approach and passion for innovation drive him to find new and effective ways to apply Machine Learning techniques. With a deep understanding of NLP and Computer Vision, he is a valuable asset to any team he works with, consistently delivering cutting-edge solutions to complex problems.

Bartosz Lenar
Bartosz Lenar
Machine Learning Researcher

Bartosz Lenar holds a Bachelor's degree in Applied Computer Science from the AGH University of Science and Technology, specializing in databases and software architectures, as well as a master's degree in Computer Science from the Wrocław University of Technology, specializing in IT system security and reliability. With a strong academic background, he has contributed to advanced solutions for processing financial and medical data throughout his career. At NeuroSYS, he has held roles as a Solutions Architect, developing AI-based solutions for medical research labs and the pharmaceutical industry, as well as working on a smart home IoT platform. Currently serving as the Engineering Lead, he successfully oversees a team of approximately 100 software engineers, coordinating operational and technical activities to achieve the company's technical objectives.


Collaboration with Scientists and Researchers

Jarosław Pawłowski, Ph.D., is an assistant professor at the Department of Theoretical Physics at the Wroclaw University of Science and Technology, specializing in theoretical physics and nanoscale device modeling for quantum computing in graphene-like structures. He has an extensive record of publications and presentations at international conferences and has collaborated with industry partners on projects involving magnetic materials, power fault current limiters, realistic visualization of medical data on AR devices, and ECG arrhythmia detection systems.
Jarosław Pawłowski
Assistant Professor at Wrocław University of Science and Technology, Deep Learning Freelancer
Sylwia Majchrowska, Ph.D., completed her Mathematics and Technical Physics studies at the University of Wrocław and the Wrocław University of Science and Technology. Her research focused on nonlinear optical phenomena in microstructured and multimode optical fibers. It resulted in contributions to the development of deep learning algorithms for image processing, particularly in automating the analysis of microbial colonies. She has co-authored scientific publications and presentations in this field and actively mentors in volunteering programs promoting STEM disciplines.
Sylwia Majchrowska
Artificial intelligence specialist, Doctor of Physical Sciences, Educator
Daniel Śliwowski holds an engineering degree in Robotics and a Master's in Embedded Robotics from the Wrocław University of Science and Technology. He is currently a Ph.D. researcher at TU Wien, specializing in computer vision, deep learning, and autonomous robots. His research focuses on understanding complex manipulation tasks, robot learning, and human-robot interaction at the Autonomous Systems Lab.
Daniel Śliwowski
Ph.D. Researcher at Vienna University of Technology
Adam holds a Bachelor of Science degree in Control Engineering and Robotics and a Master of Science in Computer Science from the Wrocław University of Science and Technology, currently pursuing a Ph.D. in High-Performance Vision Systems at AIT Austrian Institute of Technology. He has contributed to the development of computer vision algorithms for NeuroSYS products and has extensive experience as a PLC developer and control engineer.
Adam Loch
Ph.D. Student at AIT Austrian Institute of Technology
Michał Adamski holds a Bachelor of Engineering and Master of Science degrees in Biomedical Engineering. Focusing on the intersection of healthcare and technology, he has contributed to developing VR applications in cognitive disorder diagnosis and microvascular brain surgery simulation. Currently pursuing a Ph.D. in Biomedical Engineering, he explores the role of cognition and visual signal processing in balance maintenance using VR technology.
Michał Adamski
Ph.D. Student at Wrocław University of Science and Technology

Where science and tech collide

Interdisciplinary cooperation results in state-of-the-art technology harnessed to serve scientific and industrial results. Visit our blog to read about recent findings.
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The focus on connecting science and industry through innovative projects

Our dedicated, 15-person research and development team solves real-world problems with artificial intelligence, deep learning, and augmented reality.
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MOZART program

At NeuroSYS, we are open to combining the scientific field with business. A model example of these collaborations is the MOZART project.

The MOZART program is a competition organized by the Municipality of Wrocław represented by the Director of the Office for Cooperation with Higher Education Institutions. The project's objective is to support the Wrocław labour market by providing companies with access to the intellectual potential of scientists.

The competition is addressed to partnerships formed by scientists - academics of universities and scientific institutes of the Polish Academy of Sciences, research institutes, international scientific institutes, and entrepreneurs employing staff in Wrocław. As a result of the cooperation of partnerships, new innovative solutions, products, and services are created.

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