Getnet Demil

Doctoral Researcher
Hold Triple MSc. in Image Processing and Computer Vision
Computer Vision, Artificial Intelligences, Remote Sensing

Center for Machine Vision and Signal Analysis (CMVS)
Faculty of Information Technology and Electrical Engineering

I am Getnet Demil, a Doctoral Researcher at the University of Oulu, Finland, where my work centers on the application of artificial intelligence and remote sensing technologies in hydrology modeling.

I hold a triple Master’s degree in Image Processing and Computer Vision, earned through a collaborative program involving the University of Bordeaux (France), the Autonomous University of Madrid (Spain), and Pazmany Peter Catholic University (Hungary), completed between 2022 and 2024. Additionally, I earned an MSc in Communication System Engineering (2020–2022) and a BSc in Electrical Engineering (2013–2018) from Bahir Dar University, Ethiopia.

My research explores the integration of advanced image processing, computer vision, and deep learning techniques to address challenges in hydrological data analysis and environmental modeling.

I aim to contribute to the development of robust methodologies for water resource management and climate change adaptation. My academic and professional efforts are guided by a commitment to advancing scientific understanding through interdisciplinary approaches.

Portfolio website: https://getnetdemil.github.io

Research interests

Computer Vision
Artificial Intelligence
Remote Sensing
Hydrology Modeling
Image Processing

Researcher information

Researcher profiles

Scientific merits

Artificial Intelligence and Remote Sensing Technology for Hydrology Modeling (Ongoing, University of Oulu, Finland)
- Leading cutting-edge research at the intersection of AI and remote sensing to improve hydrology modeling.
- Developed advanced image processing techniques to extract snow-water characteristics from satellite imagery, enhancing estimation accuracy with state-of-the-art deep learning methodologies.
- Aims to optimize water resource management and inform climate change mitigation strategies.
Publication: Advances in Image-Based Estimation of Snow Variables (Journal of Hydrology, May 2024)
- Authored a systematic literature review on image-based estimation of snow hydrology parameters.
- Highlighted the transformative potential of deep learning architectures and uncertainty quantification in snow hydrology modeling.
- DOI: https://doi.org/10.1016/j.jhydrol.2025.132855.
Conference Presentation: Leveraging Social Media for Real-Time Monitoring of Local Climate Impact (SIGIR 2024 Workshop)
- Presented research on using social media as a dynamic, real-time data source for monitoring localized climate change impacts.
- Emphasized the value of informal publications for providing timely insights into community and ecosystem responses.
Deep Learning Based Snow Hydrology Parameter Estimation from Image Sensors (2024)
- Designed a comprehensive data processing pipeline using deep learning to estimate snow hydrology parameters from imagery data.
- Incorporated data acquisition, model selection, training methodologies, and performance evaluation metrics.
Vision Aided Recognition of Objects to Grasp with a Robot Arm (2022–2023)
- Implemented 6D pose estimation using the DenseFusion model to assist individuals with upper-limb disabilities.
- Created a proprietary dataset with Unity and HTC VIVE headsets, integrating RGB, depth, and binary mask images.
Advanced Image Processing Method on UAV Images (2023)
- Applied semantic segmentation (UNet, Attention U-Net, DeepLabV3+) to UAV imagery for crop field, background, and weed classification.
Design and Implementation of a Smart Microscope for Protozoan Disease Detection (2018)
- Developed an automated detection and diagnosis system using Python, earning accolades as the Best Bahir Dar University Project of the Year (2018) and a Top 50 African Project of the Year (Africa Innovation Week 2019).

Contact information

E-mail

getnet.demil@oulu.fi

Social media

Visiting address

Office Number: TS377

Postal address

Pentti Kaiteran katu 1, 90570 Oulu

Keywords

Computer science artificial intelligence machine learning machine vision robotics recognition of emotions and visual speech

Getnet Demil

Research interests

Researcher information

Researcher profiles

Scientific merits

Contact information

E-mail

Social media

Visiting address

Postal address

Keywords

Related to the researcher

Center for Machine Vision and Signal Analysis (CMVS)

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