Education — Konrad Chmielinski<\/title>\n <link rel=\"preconnect\" href=\"https:\/\/fonts.googleapis.com\">\n <link rel=\"preconnect\" href=\"https:\/\/fonts.gstatic.com\" crossorigin>\n <link rel=\"stylesheet\" href=\"https:\/\/fonts.googleapis.com\/css2?family=JetBrains+Mono:wght@400;500;700&family=Sora:wght@300;400;600;700&display=swap\" media=\"print\" onload=\"this.media='all'\">\n <noscript>\n <link rel=\"stylesheet\" href=\"https:\/\/fonts.googleapis.com\/css2?family=JetBrains+Mono:wght@400;500;700&family=Sora:wght@300;400;600;700&display=swap\">\n <\/noscript>\n <style>\n :root {\n --accent: #2563EB;\n --accent-dim: #1D4ED8;\n --accent-bg: #EFF6FF;\n --mono: 'JetBrains Mono', monospace;\n --sans: 'Sora', sans-serif;\n }\n\n * {\n box-sizing: border-box;\n margin: 0;\n padding: 0;\n }\n\n body {\n background: #fff;\n color: #111;\n -webkit-overflow-scrolling: touch;\n overflow-x: hidden;\n }\n\n .blog-root {\n font-family: var(--sans);\n color: #111;\n max-width: 100%;\n margin: 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{\n font-size: 12px;\n color: #555;\n line-height: 1.5;\n }\n\n .finding-body strong {\n color: #111;\n display: block;\n margin-bottom: 2px;\n font-size: 13px;\n }\n\n .tag-cloud {\n display: flex;\n flex-wrap: wrap;\n gap: 5px;\n margin: .75rem 0 0;\n }\n\n .tag {\n font-family: var(--mono);\n font-size: 10px;\n padding: 3px 8px;\n border-radius: 100px;\n border: .5px solid #ddd;\n color: #666;\n background: #fff;\n }\n\n .tag.primary {\n background: var(--accent-bg);\n border-color: #BFDBFE;\n color: var(--accent-dim);\n font-weight: 500;\n }\n\n .result-chip {\n display: inline-flex;\n align-items: center;\n gap: 6px;\n background: var(--accent-bg);\n border: .5px solid #BFDBFE;\n color: var(--accent-dim);\n border-radius: 6px;\n padding: 5px 12px;\n font-size: 13px;\n font-weight: 600;\n margin: .75rem 0 0;\n }\n\n .result-chip.gold {\n background: #FFFBEB;\n border-color: #FDE68A;\n color: #92400E;\n }\n\n .section-header {\n display: flex;\n align-items: center;\n gap: 10px;\n margin: 2.5rem 0 1.25rem;\n }\n\n .section-header h2 {\n font-family: var(--sans);\n font-size: 1rem;\n font-weight: 600;\n color: #111;\n white-space: nowrap;\n }\n\n .sh-line {\n flex: 1;\n height: .5px;\n background: #eee;\n }\n\n .footer-note {\n font-family: var(--mono);\n font-size: 11px;\n color: #777;\n border-top: .5px solid #ddd;\n margin-top: 3rem;\n padding-top: 1rem;\n display: flex;\n justify-content: space-between;\n flex-wrap: wrap;\n gap: 4px;\n }\n <\/style>\n<\/head>\n<body>\n <div class=\"blog-root\">\n\n <div class=\"eyebrow\">Konrad Chmielinski · Academic Background<\/div>\n <p class=\"subtitle\">From applied mathematics and physics at secondary school, through engineering and AI research at one of Poland’s leading technical universities.<\/p>\n\n <div class=\"meta-row\">\n <span class=\"meta-chip blue\">MSc Data Science (AI\/ML)<\/span>\n <span class=\"meta-chip\">BSc Automation & Robotics<\/span>\n <span class=\"meta-chip\">Silesian University of Technology<\/span>\n <span class=\"meta-chip\">Gliwice, PL<\/span>\n <\/div>\n\n <div class=\"timeline\">\n\n \n <div class=\"tl-entry\">\n <div class=\"tl-dot\"><\/div>\n <div class=\"tl-header\">\n <div class=\"tl-degree\">Master of Science (MSc) — Data Science (AI\/ML)<\/div>\n <div class=\"tl-institution\">Silesian University of Technology<\/div>\n <div class=\"tl-faculty\">Faculty of Automatic Control, Electronics and Computer Science · Macrofaculty programme<\/div>\n <div class=\"tl-period\">\n\n March 2020 — September 2021\n \n <span class=\"tl-badge\">International · conducted in English<\/span>\n <\/div>\n <\/div>\n\n <div class=\"tl-body\">\n <p>The MSc programme at the Silesian University of Technology was an international, English-language course within the Macrofaculty — a cross-disciplinary structure bringing together automation, electronics, and computer science. The programme focused on applied machine learning, statistical modelling, data engineering, and AI system design. Coursework covered neural network architectures, statistical inference, signal processing, and applied data science across healthcare and engineering domains.<\/p> \n <p>The research environment was strongly interdisciplinary — my thesis, supervised by Professor Joanna Polanska, sat at the intersection of epidemiology, environmental science, and predictive modelling. This shaped how I think about data problems today: always asking what the real-world phenomenon is before choosing a model.<\/p><p><\/p>\n <\/div>\n<div style=\"display:flex;gap:16px;align-items:stretch;\">\n <div style=\"flex:1;overflow:hidden;border-radius:8px;\">\n <img decoding=\"async\" src=\"https:\/\/chmielinski-konrad.info\/wp-content\/uploads\/2025\/12\/Zrzut-ekranu-2026-05-6-o-23.36.37.png\" \n alt=\"\" \n style=\"width:100%;height:100%;object-fit:cover;display:block;\">\n <\/div>\n <div style=\"flex:1;overflow:hidden;border-radius:8px;\">\n <img decoding=\"async\" src=\"https:\/\/chmielinski-konrad.info\/wp-content\/uploads\/2025\/12\/CDE0A413-4A8E-4FB7-B329-9602AC6AD286_1_201_a.jpeg\" \n alt=\"\" \n style=\"width:100%;height:100%;object-fit:cover;display:block;\">\n <\/div>\n<\/div>\n <div class=\"thesis-block\">\n <div class=\"th-label\">Master’s Thesis<\/div>\n <div class=\"th-title\">Predictive Models of Type 1 Diabetes Mellitus Incidence Rate in Upper Silesian Children<\/div>\n <div class=\"th-supervisor\">Supervisor: Professor Joanna Polanska, DSc PhD — Department of Data Science and Engineering, Silesian University of Technology<\/div>\n <div class=\"th-body\">\n <p style=\"margin-bottom:.75rem;\">Type 1 diabetes mellitus (T1DM) is a sudden-onset, ultra-rare autoimmune disease affecting newborns and very young children — and its causes remain only partially understood. My research investigated the environmental and epidemiological factors that correlate with T1DM incidence rates in children from the Upper Silesian region of Poland, one of the most industrialised areas in Central Europe.<\/p>\n <p style=\"margin-bottom:.75rem;\">The core hypothesis was that T1DM onset might correlate with external environmental triggers rather than purely genetic predisposition. I built predictive models incorporating multiple external datasets and discovered statistically significant correlations across several unexpected variables.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"finding-row\">\n <div class=\"finding-card\">\n <div class=\"finding-icon\">☀<\/div>\n <div class=\"finding-body\">\n <strong>Solar cycle (sunspot number)<\/strong>\n\n Significant correlation between solar activity cycles and T1DM incidence rates — suggesting a potential link via UV radiation and vitamin D synthesis.\n \n <\/div>\n <\/div>\n <div class=\"finding-card\">\n <div class=\"finding-icon\">🌛<\/div>\n <div class=\"finding-body\">\n <strong>Influenza infection rate<\/strong>\n\n Seasonal flu infection volume showed correlation with T1DM onset timing — consistent with the viral trigger hypothesis for autoimmune activation.\n \n <\/div>\n <\/div>\n <div class=\"finding-card\">\n <div class=\"finding-icon\">🌡<\/div>\n <div class=\"finding-body\">\n <strong>Weather & temperature factors<\/strong>\n\n Ambient temperature patterns, particularly prolonged cold periods, correlated with elevated incidence — aligning with known seasonal patterns in T1DM epidemiology.\n \n <\/div>\n <\/div>\n <\/div>\n\n <div class=\"tag-cloud\" style=\"margin-top:.875rem;\">\n <span class=\"tag primary\">Predictive modelling<\/span>\n <span class=\"tag primary\">Epidemiological data analysis<\/span>\n <span class=\"tag primary\">Statistical correlation<\/span>\n <span class=\"tag primary\">Python<\/span>\n <span class=\"tag\">Pandas \/ NumPy \/ SciPy<\/span>\n <span class=\"tag\">Time series analysis<\/span>\n <span class=\"tag\">Multi-variable regression<\/span>\n <span class=\"tag\">Environmental data integration<\/span>\n <span class=\"tag\">Scikit-Learn<\/span>\n <span class=\"tag\">Data visualisation<\/span>\n <\/div>\n\n <div class=\"result-chip\">✓ Graduated with distinction — very good (5.0)<\/div>\n <\/div>\n\n \n <div class=\"tl-entry\">\n <div class=\"tl-dot\"><\/div>\n <div class=\"tl-header\">\n <div class=\"tl-degree\">Bachelor of Science (BSc) — Automation and Robotics<\/div>\n <div class=\"tl-institution\">Silesian University of Technology<\/div>\n <div class=\"tl-faculty\">Faculty of Automatic Control, Electronics and Computer Science<\/div>\n <div class=\"tl-period\">\n\n October 2015 — February 2020\n \n <span class=\"tl-badge gray\">5 years<\/span>\n <\/div>\n <\/div>\n\n <div class=\"tl-body\">\n <p>The BSc programme in Automation and Robotics at the Faculty of Automatic Control, Electronics and Computer Science is one of the most technically demanding engineering programmes in Poland. The curriculum covers control systems theory, electronics, signal processing, embedded systems, and computer science fundamentals — building a rigorous engineering foundation before any specialisation.<\/p>\n <p>In the later years of the programme, the focus shifted toward applied AI and computer vision — which led directly to my engineering thesis, conducted under Dr. Franciszek Binczyk from the Department of Data Engineering and Exploratory Analysis. The thesis applied deep learning to a challenging real-world medical imaging problem, combining computer vision with clinical relevance.<\/p>\n <\/div>\n\n <div class=\"thesis-block\">\n <div class=\"th-label\">Engineering Thesis<\/div>\n <div class=\"th-title\">Application of U-Net Convolutional Neural Network for Detection of C1, C2, C3 Type Lung Nodules in 3D MRI Images<\/div>\n <div class=\"th-supervisor\">Supervisor: Dr. Franciszek Binczyk — Department of Data Engineering and Exploratory Analysis, Silesian University of Technology, Gliwice<\/div>\n <div class=\"th-body\">\n <p style=\"margin-bottom:.75rem;\">Lung nodule detection in 3D MRI volumes is a challenging computer vision problem — nodules are small, their boundaries are ambiguous, and false negatives carry serious clinical consequences. The thesis explored whether a U-Net architecture, originally developed for biomedical image segmentation, could be effectively applied to detect and classify nodules of types C1, C2, and C3 in volumetric MRI data.<\/p>\n <p style=\"margin-bottom:.75rem;\">U-Net’s encoder–decoder structure with skip connections makes it particularly well-suited to medical image segmentation tasks where spatial context at multiple scales is important. The research involved building and training the network on annotated MRI volumes, evaluating segmentation performance across nodule types, and analysing the model’s sensitivity to the class imbalance inherent in rare nodule detection.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"tag-cloud\" style=\"margin-top:.875rem;\">\n <span class=\"tag primary\">U-Net architecture<\/span>\n <span class=\"tag primary\">Convolutional Neural Networks<\/span>\n <span class=\"tag primary\">3D medical image segmentation<\/span>\n <span class=\"tag primary\">TensorFlow \/ Keras<\/span>\n <span class=\"tag\">PyTorch<\/span>\n <span class=\"tag\">OpenCV<\/span>\n <span class=\"tag\">Medical imaging (MRI volumes)<\/span>\n <span class=\"tag\">Class imbalance handling<\/span>\n <span class=\"tag\">Encoder–decoder networks<\/span>\n <span class=\"tag\">Lung nodule classification<\/span>\n <span class=\"tag\">Biomedical computer vision<\/span>\n <\/div>\n <\/div>\n\n \n <div class=\"tl-entry\">\n <div class=\"tl-dot school\"><\/div>\n <div class=\"tl-header\">\n <div class=\"tl-degree\">Secondary School — Mathematics & Physics Profile<\/div>\n <div class=\"tl-institution\">VII Liceum Ogolnoksztalcace im. Groszkowskiego w Zabrzu<\/div>\n <div class=\"tl-faculty\">Mathematics and Physics specialisation<\/div>\n <div class=\"tl-period\">\n\n Completed before 2015\n \n <span class=\"tl-badge gold\">Graduated with distinction<\/span>\n <\/div>\n <\/div>\n\n <div class=\"tl-body\">\n <p>The mathematics and physics profile at Liceum Groszkowskiego in Zabrze provided a rigorous analytical foundation — advanced calculus, mechanics, electromagnetism, and formal logic — that directly underpins my later work in machine learning, signal processing, and data modelling. Graduating with distinction from this profile required not only technical competence but the ability to construct and communicate formal reasoning under examination conditions.<\/p>\n <p>The school has a strong tradition in STEM education in the Zabrze region. The choice of the maths-physics profile was deliberate — a direct stepping stone toward the engineering and data science programmes at the Silesian University of Technology.<\/p>\n <\/div>\n\n <div class=\"result-chip gold\">✓ Graduated with distinction<\/div>\n <\/div>\n\n <\/div>\n \n\n <div class=\"section-header\">\n <h2>What my education means in practice<\/h2>\n <div class=\"sh-line\"><\/div>\n <\/div>\n <p class=\"body\">Both academic theses reflect the same underlying approach I bring to professional work: start with a real-world problem, build a rigorous data pipeline, apply appropriate models, and interpret results in context rather than chasing benchmark numbers. The T1DM research taught me to look for unexpected correlations in complex multi-source datasets. The U-Net work taught me that model architecture choices have real consequences when the cost of false negatives is clinical.<\/p>\n <p class=\"body\">The combination of a strong engineering foundation from the BSc and applied AI\/ML specialisation from the MSc is what allows me to bridge the gap between automation engineering and data science — understanding both the system-level constraints and the mathematical models that sit on top of them.<\/p>\n\n <div class=\"footer-note\">\n <span>konrad.chmielinski@outlook.com<\/span>\n <span>linkedin.com\/in\/konrad-chmielinski<\/span>\n <span>Open to remote · Full-time \/ B2B<\/span>\n <\/div>\n\n <\/div>\n<\/body>\n<\/html>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Education — Konrad Chmielinski Konrad Chmielinski · Academic Background From applied mathematics and physics at secondary school, through engineering and AI research at one of Poland’s leading technical universities. MSc Data Science (AI\/ML) BSc Automation & Robotics Silesian University of Technology Gliwice, PL Master of Science (MSc) — Data Science (AI\/ML) Silesian University of Technology Faculty of Automatic Control, Electronics […]<\/p>\n","protected":false},"author":1,"featured_media":512,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-180","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-about-me"],"views":31,"_links":{"self":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts\/180","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/comments?post=180"}],"version-history":[{"count":15,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts\/180\/revisions"}],"predecessor-version":[{"id":547,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts\/180\/revisions\/547"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/media\/512"}],"wp:attachment":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/media?parent=180"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/categories?post=180"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/tags?post=180"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

{"id":180,"date":"2025-12-06T00:36:49","date_gmt":"2025-12-05T23:36:49","guid":{"rendered":"http:\/\/serwer402453.lh.pl\/autoinstalator\/serwer402453.lh.pl\/wordpress143401\/?p=180"},"modified":"2026-05-08T09:49:30","modified_gmt":"2026-05-08T07:49:30","slug":"education","status":"publish","type":"post","link":"https:\/\/chmielinski-konrad.info\/index.php\/2025\/12\/06\/education\/","title":{"rendered":"Education"},"content":{"rendered":"\n\n\n\n \n \n Education — Konrad Chmielinski<\/title>\n <link rel=\"preconnect\" href=\"https:\/\/fonts.googleapis.com\">\n <link rel=\"preconnect\" href=\"https:\/\/fonts.gstatic.com\" crossorigin>\n <link rel=\"stylesheet\" href=\"https:\/\/fonts.googleapis.com\/css2?family=JetBrains+Mono:wght@400;500;700&family=Sora:wght@300;400;600;700&display=swap\" media=\"print\" onload=\"this.media='all'\">\n <noscript>\n <link rel=\"stylesheet\" href=\"https:\/\/fonts.googleapis.com\/css2?family=JetBrains+Mono:wght@400;500;700&family=Sora:wght@300;400;600;700&display=swap\">\n <\/noscript>\n <style>\n :root {\n --accent: #2563EB;\n --accent-dim: #1D4ED8;\n --accent-bg: #EFF6FF;\n --mono: 'JetBrains Mono', monospace;\n --sans: 'Sora', sans-serif;\n }\n\n * {\n box-sizing: border-box;\n margin: 0;\n padding: 0;\n }\n\n body {\n background: #fff;\n color: #111;\n -webkit-overflow-scrolling: touch;\n overflow-x: hidden;\n }\n\n .blog-root {\n font-family: var(--sans);\n color: #111;\n max-width: 100%;\n margin: 0 auto;\n padding: 2rem 1rem 4rem;\n line-height: 1.7;\n }\n\n .eyebrow {\n font-family: var(--mono);\n font-size: 11px;\n letter-spacing: .12em;\n color: var(--accent-dim);\n text-transform: uppercase;\n margin-bottom: .75rem;\n display: flex;\n align-items: center;\n gap: 8px;\n }\n\n .eyebrow::before {\n content: '';\n display: inline-block;\n width: 24px;\n height: 1.5px;\n background: var(--accent);\n }\n\n 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justify-content: space-between;\n flex-wrap: wrap;\n gap: 4px;\n }\n <\/style>\n<\/head>\n<body>\n <div class=\"blog-root\">\n\n <div class=\"eyebrow\">Konrad Chmielinski · Academic Background<\/div>\n <p class=\"subtitle\">From applied mathematics and physics at secondary school, through engineering and AI research at one of Poland’s leading technical universities.<\/p>\n\n <div class=\"meta-row\">\n <span class=\"meta-chip blue\">MSc Data Science (AI\/ML)<\/span>\n <span class=\"meta-chip\">BSc Automation & Robotics<\/span>\n <span class=\"meta-chip\">Silesian University of Technology<\/span>\n <span class=\"meta-chip\">Gliwice, PL<\/span>\n <\/div>\n\n <div class=\"timeline\">\n\n \n <div class=\"tl-entry\">\n <div class=\"tl-dot\"><\/div>\n <div class=\"tl-header\">\n <div class=\"tl-degree\">Master of Science (MSc) — Data Science (AI\/ML)<\/div>\n <div class=\"tl-institution\">Silesian University of Technology<\/div>\n <div class=\"tl-faculty\">Faculty of Automatic Control, Electronics and Computer Science · Macrofaculty programme<\/div>\n <div class=\"tl-period\">\n\n March 2020 — September 2021\n \n <span class=\"tl-badge\">International · conducted in English<\/span>\n <\/div>\n <\/div>\n\n <div class=\"tl-body\">\n <p>The MSc programme at the Silesian University of Technology was an international, English-language course within the Macrofaculty — a cross-disciplinary structure bringing together automation, electronics, and computer science. The programme focused on applied machine learning, statistical modelling, data engineering, and AI system design. Coursework covered neural network architectures, statistical inference, signal processing, and applied data science across healthcare and engineering domains.<\/p> \n <p>The research environment was strongly interdisciplinary — my thesis, supervised by Professor Joanna Polanska, sat at the intersection of epidemiology, environmental science, and predictive modelling. This shaped how I think about data problems today: always asking what the real-world phenomenon is before choosing a model.<\/p><p><\/p>\n <\/div>\n<div style=\"display:flex;gap:16px;align-items:stretch;\">\n <div style=\"flex:1;overflow:hidden;border-radius:8px;\">\n <img decoding=\"async\" src=\"https:\/\/chmielinski-konrad.info\/wp-content\/uploads\/2025\/12\/Zrzut-ekranu-2026-05-6-o-23.36.37.png\" \n alt=\"\" \n style=\"width:100%;height:100%;object-fit:cover;display:block;\">\n <\/div>\n <div style=\"flex:1;overflow:hidden;border-radius:8px;\">\n <img decoding=\"async\" src=\"https:\/\/chmielinski-konrad.info\/wp-content\/uploads\/2025\/12\/CDE0A413-4A8E-4FB7-B329-9602AC6AD286_1_201_a.jpeg\" \n alt=\"\" \n style=\"width:100%;height:100%;object-fit:cover;display:block;\">\n <\/div>\n<\/div>\n <div class=\"thesis-block\">\n <div class=\"th-label\">Master’s Thesis<\/div>\n <div class=\"th-title\">Predictive Models of Type 1 Diabetes Mellitus Incidence Rate in Upper Silesian Children<\/div>\n <div class=\"th-supervisor\">Supervisor: Professor Joanna Polanska, DSc PhD — Department of Data Science and Engineering, Silesian University of Technology<\/div>\n <div class=\"th-body\">\n <p style=\"margin-bottom:.75rem;\">Type 1 diabetes mellitus (T1DM) is a sudden-onset, ultra-rare autoimmune disease affecting newborns and very young children — and its causes remain only partially understood. My research investigated the environmental and epidemiological factors that correlate with T1DM incidence rates in children from the Upper Silesian region of Poland, one of the most industrialised areas in Central Europe.<\/p>\n <p style=\"margin-bottom:.75rem;\">The core hypothesis was that T1DM onset might correlate with external environmental triggers rather than purely genetic predisposition. I built predictive models incorporating multiple external datasets and discovered statistically significant correlations across several unexpected variables.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"finding-row\">\n <div class=\"finding-card\">\n <div class=\"finding-icon\">☀<\/div>\n <div class=\"finding-body\">\n <strong>Solar cycle (sunspot number)<\/strong>\n\n Significant correlation between solar activity cycles and T1DM incidence rates — suggesting a potential link via UV radiation and vitamin D synthesis.\n \n <\/div>\n <\/div>\n <div class=\"finding-card\">\n <div class=\"finding-icon\">🌛<\/div>\n <div class=\"finding-body\">\n <strong>Influenza infection rate<\/strong>\n\n Seasonal flu infection volume showed correlation with T1DM onset timing — consistent with the viral trigger hypothesis for autoimmune activation.\n \n <\/div>\n <\/div>\n <div class=\"finding-card\">\n <div class=\"finding-icon\">🌡<\/div>\n <div class=\"finding-body\">\n <strong>Weather & temperature factors<\/strong>\n\n Ambient temperature patterns, particularly prolonged cold periods, correlated with elevated incidence — aligning with known seasonal patterns in T1DM epidemiology.\n \n <\/div>\n <\/div>\n <\/div>\n\n <div class=\"tag-cloud\" style=\"margin-top:.875rem;\">\n <span class=\"tag primary\">Predictive modelling<\/span>\n <span class=\"tag primary\">Epidemiological data analysis<\/span>\n <span class=\"tag primary\">Statistical correlation<\/span>\n <span class=\"tag primary\">Python<\/span>\n <span class=\"tag\">Pandas \/ NumPy \/ SciPy<\/span>\n <span class=\"tag\">Time series analysis<\/span>\n <span class=\"tag\">Multi-variable regression<\/span>\n <span class=\"tag\">Environmental data integration<\/span>\n <span class=\"tag\">Scikit-Learn<\/span>\n <span class=\"tag\">Data visualisation<\/span>\n <\/div>\n\n <div class=\"result-chip\">✓ Graduated with distinction — very good (5.0)<\/div>\n <\/div>\n\n \n <div class=\"tl-entry\">\n <div class=\"tl-dot\"><\/div>\n <div class=\"tl-header\">\n <div class=\"tl-degree\">Bachelor of Science (BSc) — Automation and Robotics<\/div>\n <div class=\"tl-institution\">Silesian University of Technology<\/div>\n <div class=\"tl-faculty\">Faculty of Automatic Control, Electronics and Computer Science<\/div>\n <div class=\"tl-period\">\n\n October 2015 — February 2020\n \n <span class=\"tl-badge gray\">5 years<\/span>\n <\/div>\n <\/div>\n\n <div class=\"tl-body\">\n <p>The BSc programme in Automation and Robotics at the Faculty of Automatic Control, Electronics and Computer Science is one of the most technically demanding engineering programmes in Poland. The curriculum covers control systems theory, electronics, signal processing, embedded systems, and computer science fundamentals — building a rigorous engineering foundation before any specialisation.<\/p>\n <p>In the later years of the programme, the focus shifted toward applied AI and computer vision — which led directly to my engineering thesis, conducted under Dr. Franciszek Binczyk from the Department of Data Engineering and Exploratory Analysis. The thesis applied deep learning to a challenging real-world medical imaging problem, combining computer vision with clinical relevance.<\/p>\n <\/div>\n\n <div class=\"thesis-block\">\n <div class=\"th-label\">Engineering Thesis<\/div>\n <div class=\"th-title\">Application of U-Net Convolutional Neural Network for Detection of C1, C2, C3 Type Lung Nodules in 3D MRI Images<\/div>\n <div class=\"th-supervisor\">Supervisor: Dr. Franciszek Binczyk — Department of Data Engineering and Exploratory Analysis, Silesian University of Technology, Gliwice<\/div>\n <div class=\"th-body\">\n <p style=\"margin-bottom:.75rem;\">Lung nodule detection in 3D MRI volumes is a challenging computer vision problem — nodules are small, their boundaries are ambiguous, and false negatives carry serious clinical consequences. The thesis explored whether a U-Net architecture, originally developed for biomedical image segmentation, could be effectively applied to detect and classify nodules of types C1, C2, and C3 in volumetric MRI data.<\/p>\n <p style=\"margin-bottom:.75rem;\">U-Net’s encoder–decoder structure with skip connections makes it particularly well-suited to medical image segmentation tasks where spatial context at multiple scales is important. The research involved building and training the network on annotated MRI volumes, evaluating segmentation performance across nodule types, and analysing the model’s sensitivity to the class imbalance inherent in rare nodule detection.<\/p>\n <\/div>\n <\/div>\n\n <div class=\"tag-cloud\" style=\"margin-top:.875rem;\">\n <span class=\"tag primary\">U-Net architecture<\/span>\n <span class=\"tag primary\">Convolutional Neural Networks<\/span>\n <span class=\"tag primary\">3D medical image segmentation<\/span>\n <span class=\"tag primary\">TensorFlow \/ Keras<\/span>\n <span class=\"tag\">PyTorch<\/span>\n <span class=\"tag\">OpenCV<\/span>\n <span class=\"tag\">Medical imaging (MRI volumes)<\/span>\n <span class=\"tag\">Class imbalance handling<\/span>\n <span class=\"tag\">Encoder–decoder networks<\/span>\n <span class=\"tag\">Lung nodule classification<\/span>\n <span class=\"tag\">Biomedical computer vision<\/span>\n <\/div>\n <\/div>\n\n \n <div class=\"tl-entry\">\n <div class=\"tl-dot school\"><\/div>\n <div class=\"tl-header\">\n <div class=\"tl-degree\">Secondary School — Mathematics & Physics Profile<\/div>\n <div class=\"tl-institution\">VII Liceum Ogolnoksztalcace im. Groszkowskiego w Zabrzu<\/div>\n <div class=\"tl-faculty\">Mathematics and Physics specialisation<\/div>\n <div class=\"tl-period\">\n\n Completed before 2015\n \n <span class=\"tl-badge gold\">Graduated with distinction<\/span>\n <\/div>\n <\/div>\n\n <div class=\"tl-body\">\n <p>The mathematics and physics profile at Liceum Groszkowskiego in Zabrze provided a rigorous analytical foundation — advanced calculus, mechanics, electromagnetism, and formal logic — that directly underpins my later work in machine learning, signal processing, and data modelling. Graduating with distinction from this profile required not only technical competence but the ability to construct and communicate formal reasoning under examination conditions.<\/p>\n <p>The school has a strong tradition in STEM education in the Zabrze region. The choice of the maths-physics profile was deliberate — a direct stepping stone toward the engineering and data science programmes at the Silesian University of Technology.<\/p>\n <\/div>\n\n <div class=\"result-chip gold\">✓ Graduated with distinction<\/div>\n <\/div>\n\n <\/div>\n \n\n <div class=\"section-header\">\n <h2>What my education means in practice<\/h2>\n <div class=\"sh-line\"><\/div>\n <\/div>\n <p class=\"body\">Both academic theses reflect the same underlying approach I bring to professional work: start with a real-world problem, build a rigorous data pipeline, apply appropriate models, and interpret results in context rather than chasing benchmark numbers. The T1DM research taught me to look for unexpected correlations in complex multi-source datasets. The U-Net work taught me that model architecture choices have real consequences when the cost of false negatives is clinical.<\/p>\n <p class=\"body\">The combination of a strong engineering foundation from the BSc and applied AI\/ML specialisation from the MSc is what allows me to bridge the gap between automation engineering and data science — understanding both the system-level constraints and the mathematical models that sit on top of them.<\/p>\n\n <div class=\"footer-note\">\n <span>konrad.chmielinski@outlook.com<\/span>\n <span>linkedin.com\/in\/konrad-chmielinski<\/span>\n <span>Open to remote · Full-time \/ B2B<\/span>\n <\/div>\n\n <\/div>\n<\/body>\n<\/html>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Education — Konrad Chmielinski Konrad Chmielinski · Academic Background From applied mathematics and physics at secondary school, through engineering and AI research at one of Poland’s leading technical universities. MSc Data Science (AI\/ML) BSc Automation & Robotics Silesian University of Technology Gliwice, PL Master of Science (MSc) — Data Science (AI\/ML) Silesian University of Technology Faculty of Automatic Control, Electronics […]<\/p>\n","protected":false},"author":1,"featured_media":512,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-180","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-about-me"],"views":31,"_links":{"self":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts\/180","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/comments?post=180"}],"version-history":[{"count":15,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts\/180\/revisions"}],"predecessor-version":[{"id":547,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/posts\/180\/revisions\/547"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/media\/512"}],"wp:attachment":[{"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/media?parent=180"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/categories?post=180"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/chmielinski-konrad.info\/index.php\/wp-json\/wp\/v2\/tags?post=180"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}