Location
PolandRate
Years of experience
5+About
Throughout my career, I have excelled in transforming business cases into AI solutions and vice versa, ensuring that the machine learning solutions I deliver precisely meet client requirements. My expertise lies in finding the most effective analytical models to address specific problems, and I am adept at visualizing and presenting analytical conclusions in a clear, comprehensible manner for business users. Additionally, I have a strong background in implementing solutions within comprehensive software systems and conducting government-funded projects, particularly in R&D and through the National Centre for Research and Development (NCBiR). In my current role at the Chancellery of the Prime Minister (GRAI), I serve as an AI expert focusing on smart buildings and energy efficiency. Concurrently, at APA Group, I lead AI and big data engineering projects, where I have successfully implemented several AI systems, including anomaly detection in industrial machines, electricity consumption analysis, and non-contact monitoring for healthcare. My academic contributions include lecturing at various universities on AI applications in Industry 4.0. Additionally, I have held positions at Knowledge.io, DMP Systems, and Bombardier Transportation, where I developed AI algorithms for safety improvements, designed end-to-end visualization systems, and conducted sensitivity analysis for traffic control systems. My educational background includes a PhD in Data Science and Electronics from the Silesian University of Technology.Tech Stack
AI, Agile, Data Analysis, Data Science/AI, Jira, ScrumExperience
- Exceling at turning business requirements into actionable AI solutions and translating AI capabilities into viable business cases.
- Specializing in delivering machine learning solutions that are precisely tailored to match client requirements, ensuring optimal outcomes.
- Possessing strong skills in identifying and selecting the most suitable analytical models to solve specific business problems effectively.
- Adept at visualizing and presenting the conclusions from my analyses in a clear and understandable way for business users.
- Extensive experience in implementing AI solutions as part of complete software systems, ensuring seamless integration and functionality.
- Proven track record of conducting and managing government-funded R&D projects, particularly through the National Centre for Research and Development (NCBiR).
- Contributing to academia as a visiting lecturer, sharing my expertise on the application of artificial intelligence methods in Industry 4.0 at MBA and postgraduate levels.
Employment history
• Designing and implementing artificial intelligence and machine learning solutions to optimize the functionality and efficiency of smart buildings.
• Creating AI-driven strategies to improve energy efficiency in various infrastructures, ensuring sustainable and cost-effective energy usage.
vCollecting and analyzing data related to building operations to identify patterns and insights that can lead to improved management and energy savings.
• Ensuring seamless integration of AI systems with current building management technologies to enhance overall performance.
• Working closely with engineers, data scientists, and other stakeholders to develop • Visualizing and presenting data analysis results and AI recommendations to government officials and stakeholders in a clear and actionable manner.
• Keeping abreast of the latest advancements in AI and smart building technologies to continually improve solutions and maintain cutting-edge expertise in the field.
Education history
• Overseeing and executing government-funded research and development projects, particularly those funded by the National Centre for Research and Development (NCBiR).
• Conceptualizing, realizing, and implementing anomaly detection reasoning systems to monitor industrial machines, predict machine damage, and optimize production processes, ensuring compliance with ISO standards.
• Creating and deploying AI systems to analyze electricity consumption in various settings, including production plants, machines, houses, and apartments, and assessing the quality of electric energy parameters against ISO standards.
• Designing and implementing a fuzzy expert system to predict optimal conditions for charging cooling accumulators, ensuring the continuity and efficiency of cooling supply systems.
• Conceptualizing and implementing AI systems for non-contact monitoring of sick and elderly individuals using computer vision and movement analysis algorithms to enhance healthcare and safety.
• Conducting extensive data analysis, interpreting results, and presenting findings in a clear and actionable manner to stakeholders, ensuring that insights are effectively communicated and utilized for decision-making.
• Designing and developing course materials, syllabi, and lecture content for MBA and postgraduate studies, ensuring that they are up-to-date with the latest advancements in AI and industry practices.
• Providing engaging and informative lectures that facilitate a deep understanding of AI concepts and their practical applications in Industry 4.0 among students.
• Offering mentorship and guidance to MBA and postgraduate students, assisting them with their projects, research work, and career development in the field of AI.
• Working closely with other faculty members and industry experts to ensure a comprehensive and interdisciplinary approach to teaching AI in Industry 4.0.
• Engaging in research activities related to AI applications in Industry 4.0, contributing to academic knowledge, and integrating research findings into teaching materials.
• Assessing and evaluating student performance through exams, assignments, and projects, providing constructive feedback to help them improve and excel in their studies.
• Performing comprehensive analysis and evaluation of hardware solutions used in traffic signal systems, ensuring they meet safety, efficiency, and reliability standards. This includes assessing the design, implementation, and operational aspects of traffic control hardware, identifying potential issues, and recommending improvements to enhance traffic flow and safety.
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