SPS Interactive Signal Processing Day: Engage, Learn, Inspire for Highschool Students and under Graduate Students
- The tutorial for high school graduates on Signal Processing (SP) and Artificial Intelligence (AI) aims to introduce core concepts, real-world applications, and career opportunities. Students will learn how signals represent information (audio, images, sensors) and how AI interprets them for tasks like voice recognition, health monitoring, and environmental impact studies. The program connects high school math and science with practical technology, inspires further studies in STEM, and highlights the role of SP and AI in addressing challenges such as
climate change.
Overall, the tutorial is designed to spark curiosity, build confidence, and lay a solid foundation for students interested in pursuing modern technology fields that are shaping the future.
Date and Time
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- Sundbyberg
- stockholm, Stockholms lan
- Sweden 17452
- Building: Lötsjövägen 6
- Starts 27 September 2025 10:00 PM UTC
- Ends 04 October 2025 01:00 PM UTC
- No Admission Charge
Speakers
Dr. Amleset Kelati of consultant AMVSOC / University of Turku
What is Signal Processing? – An introductory talk with real-life examples (audio, image, medical signals,
Biography:
https://www.utu.fi/en/people/amleset-kelati
Chair, IEEE Sweden Signal Processing Society
Dr. Amleset (Amli) Kelati is a senior researcher and engineer with over 20 years of experience in electronic design, embedded systems, and hardware–software integration. She holds a Ph.D. in Information and
Communication Technology from KTH Royal Institute of Technology, Sweden, and master’s degrees from
Chalmers University of Technology and UCLV. Her career includes senior roles at Ericsson, NXP, and u-Blox, focusing on ASIC/FPGA design, RFIC integration, and communication systems. Currently is researcher at with the University of Turku, her research explores DSP, FPGA/GPU-based instrumentation, SoC design, and energy-efficient embedded systems. She is a Senior IEEE Member and active mentor.
Email:
Address:Skvadronsbacken 23, , Stockholms lan, Sweden, 17447
Yonathan Tekeste of Royal Institute of Techology
Case Study Signal Processing and Artificial Intelligence (AI) application on Climate change and Enviromental Impact
Recent graduate from Department of --- KTH with Masters Degree on Enviromental and Geothecnical Enginnering will talk on he folowing agenda:
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Hybrid Models for Environmental Monitoring
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SP cleans and processes sensor data, which AI then analyzes for trends and predictions.
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Example: AI models trained on denoised satellite imagery to detect illegal logging.
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Early Warning Systems
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Real-time sensor data (SP) combined with AI models for fast disaster response.
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Example: Earthquake or tsunami alerts using seismic signal classification.
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Climate Change Attribution
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SP extracts signals of anthropogenic vs. natural influences; AI models help quantify their contributions.
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Example: AI explains which factors most influence regional climate change patterns.
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Biography:
https://www.kth.se/profile/ytekeste
Yonathan Alem Tekeste earned his MSc in Environmental Engineering and Sustainable Infrastructure from KTH (2025) and holds a BSc in Earth Science from Stockholm University (2022). His focus areas include environmental geology,
hydrogeology, geotechnics, contaminated land, and LCA. He has industry experience from LCA projects and skills in geotechnical investigations, slope stability analyses, and environmental monitoring. Proficient in GIS, AutoCAD, SLOPE, Python, and RStudio, he is passionate about sustainable infrastructure and real-world environmental solutions.
Address:Sweden, 17447