Kris Krystosiak
Assistant Professor
The Creative School
School of Graphic Communication Management
Toronto, Ontario
kkrystosiak@torontomu.ca
Office:
(416) 979-5000 ext. 556067
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Bio/Research
Dr. Krzysztof (Kris) Krystosiak is an Assistant Professor in the School of Graphic Communications Management at Toronto Metropolitan University, where he has been teaching and conducting research since July 2022. He holds a PhD in Mechanical Engineering from the Warsaw University of Technology in...
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Bio/Research
Dr. Krzysztof (Kris) Krystosiak is an Assistant Professor in the School of Graphic Communications Management at Toronto Metropolitan University, where he has been teaching and conducting research since July 2022. He holds a PhD in Mechanical Engineering from the Warsaw University of Technology in Poland. His PhD thesis, recognized by StatSoft and the Polish Statistical Association, received an award for its innovative use of data mining tools in engineering research.
With over 16 years of experience in the package printing industry, Dr. Krystosiak has worked in diverse roles across production, quality management, technology development, and R&D. His practical background spans both operational and strategic levels, from machine operation to technical leadership.
His research focuses on applying data mining and machine learning techniques to industrial processes, with an emphasis on waste reduction and production optimization, particularly within the context of Industry 4.0, Smart Manufacturing, and sustainable development in the package printing sector. He is currently engaged in collaborative research projects aimed at reducing environmental impact and implementing smart technologies in industrial settings across Canada and Poland.
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With over 16 years of experience in the package printing industry, Dr. Krystosiak has worked in diverse roles across production, quality management, technology development, and R&D. His practical background spans both operational and strategic levels, from machine operation to technical leadership.
His research focuses on applying data mining and machine learning techniques to industrial processes, with an emphasis on waste reduction and production optimization, particularly within the context of Industry 4.0, Smart Manufacturing, and sustainable development in the package printing sector. He is currently engaged in collaborative research projects aimed at reducing environmental impact and implementing smart technologies in industrial settings across Canada and Poland.
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