Matti:
I will teach geospatial data science and AI-related topics. I am responsible for STE-102 Data Science Methodology, STE-122 Geospatial Artificial Intelligence (GeoAI) in Management of Natural Resources and STE-123 Natural Resources Big Data Analysis and Management courses. I also participate in co-teaching on other courses in the SustTech programme.
Mohammad:
In the System Modelling and Simulation module, I teach modelling methods, system control and optimization, and simulation of production systems.
Matti:
My background comes from land surveying science, especially laser scanning, photogrammetry and geoinformation technology. I have 15 years of experience in various university-level teaching and research positions in the field of geospatial data science, primarily at Aalto University. I received my PhD degree in 2014 with the thesis title “Feasibility of mobile laser scanning for mapping and monitoring a riverine environment”. During 2014–2017 I worked as a postdoc researcher in the Center of Excellence in Laser Scanning Research and during 2017–2025, I served as an Assistant Professor at Aalto.
Mohammad:
My background is in Industrial Engineering and Management. During my PhD and postdoctoral research, I applied systems modelling methods to study industrial and food systems under different resource availability scenarios. My work has focused on understanding how emerging food technologies can contribute to more sustainable and resilient futures.
Matti:
I see the SustTech programme as an excellent opportunity to contribute to the development of sustainable technologies by combining advanced geospatial solutions, novel data acquisition and AI methods with environmental and societal needs. The field of geospatial technologies is moving towards sensor fusion, where satellites, drones, autonomous robots, work machines, mobile device sensors, and IoT systems produce continuous point cloud and image data for analysis in near real time. Sustainability challenges require this kind of accurate and up-to-date data, interdisciplinary collaboration, and innovative technological approaches, all of which are strongly represented in the programme.
I bring expertise in the measuring, mapping, and analysing natural resource data. What interests me most about the SustTech programme is the opportunity to apply advanced sensing and AI technologies to the sustainable management of renewable natural resources. I also look forward to collaborating with students and experts from diverse disciplinary backgrounds.
Mohammad:
The programme is important because it prepares students to address sustainability challenges through technological and systems-based approaches. I contribute expertise in modelling complex systems, enabling students to explore how automation and control strategies perform in realistic industrial environments.
What interests me most about the programme is its focus on real-world challenges and close collaboration with actors in Finland. Connecting academic knowledge with practical applications and working on solutions that can have a tangible impact is something I find especially rewarding.