Kaveh Amouzgar

Associate senior lecturer/Assistant Professor at Department of Civil and Industrial Engineering, Industrial Engineering and Management

Mobile phone:
+46 70 4250364
Visiting address:
Ångströmlaboratoriet, Lägerhyddsvägen 1
752 37 Uppsala
Postal address:
Box 169
751 04 Uppsala

Short presentation

I am an Assistant professor at the Department of Civil and Industrial Engineering. My research interests are focused on data analytics, simulation-based optimization, multi-objective optimization, and surrogate-assisted optimization. I am also actively working on the development and application of machine learning methods in industrial use cases.

Keywords: machine learning statistical modeling and machine learning data analytics artifical intelligence c61 optimization techniques and programming models meta-modelling multi-objective optimization

I have an engineering background with a BSc in Mechanical Engineering in 2003 from Iran. Afterward, I have worked in the automotive and oil and gas industry for 8 years, before moving to Sweden to pursue my MSc in Product Development and Materials Engineering in 2012. It was during my MSc thesis that I became fascinated by the application of multi-objective optimization and simulation-based optimization using the finite element method (FEM) in real-world industrial cases. To follow my interest I continued to research and develop machine learning methods when used in optimization algorithms as a Ph.D. student. After receiving my Ph.D. in Informatics from the University of Skövde in 2018, I focused my research on data analytics while teaching courses in optimization and operations research as a senior lecturer. I was also responsible for the Masters's program in Intelligent Automation at the University of Skövde for one year before moving to Uppsala University at the beginning of 2021 as an Assistant Professor. I am currently working in the newly formed industrial analytics group within the division of Industrial Engineering and Management. My research interests are in the application of data analytics specifically machine learning methods in industrial settings.

Please contact the directory administrator for the organization (department or similar) to correct possible errors in the information.

Kaveh Amouzgar