Farshad Farahnakian
Senior Researcher / Data Analytics / Postdoc
farshad.farahnakian@utu.fi Työhuone: Forth Floor You can usually find me at the office from 09:00 AM to 17:00 PM. |
Machine Learning, Deep Learning, Computer Vision, Sensor Fusion (Multimodal), GIS, Remote Sensing, Earth Observation, Data Analysis, and Cloud Computing.
Faculty of Technology, Department of Computing
I am a dedicated Remote Sensing Data Scientist specializing in leveraging AI to analyze Earth Observation (EO) data. I translate complex problems, from land cover mapping to change detection, into high-impact, automated solutions. My expertise spans the complete pipeline, from pre-processing petabytes of satellite imagery (GIS, Optical, SAR, LiDAR) to developing and deploying deep learning models for large-scale geospatial analysis.
Prize & Award
- Nokia Foundation Scholarship 2025
- First Prize EUSPA - EU Agency for the Space Program ThinkingEarth Hackathon at BiDS 2025
- Research Paper Award at ICPR2024
- Research Paper Award at CRITIS 2023
- Student Research Paper Competition (3rd place) at TLU 2022
I am currently working on a project called "USVA," which is funded by Business Finland. The primary goal of the UTU is to develop an innovative, robust, efficient, and user-friendly AI-based platform for detecting anomalies in the Baltic Sea. This initiative aims to create a comprehensive surveillance system that provides advanced sensor-fusion-based situational awareness, enhancing decision-making and safety for all maritime stakeholders.
Since the spring semester of 2024, I have had the privilege of serving as a Teaching Assistant for the TKO_796 Computer Vision and Sensor Fusion course. My responsibilities encompassed a range of educational support tasks, including:
1. Designing and evaluating course assignments.
2. Assisting students with the installation of necessary libraries for running Python scripts.
3. Delivering lectures on sensor fusion topics.
- Digital maritime monitoring: Enhancing situational awareness in shipping traffic using AI-based models (2026) Farahnakian, Farshad
(G5 Artikkeliväitöskirja) - Maritime vessel movement prediction: A temporal convolutional network model with optimal look-back window size determination (2025)
- Multimodal transportation
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Multi-modal Fusion of LiDAR and PRISMA Data for Cobalt Mapping: A Case Study from the Áramo Mine, Spain (2025)
- Lecture Notes in Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Wide-Area Ship Movement Prediction Using Random Forests (2025)
- Communications in Computer and Information Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A comparative study of state-of-the-art deep learning architectures for rice grain classification (2024)
- Journal of agriculture and food research
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - AI-ARC Baltic Demo: Detecting Illegal Activities at Sea (2024) 2024 27th International Conference on Information Fusion (FUSION) Svenson, Pontus; Holst, Anders; Wallberg, Anders; Nevalainen, Paavo; Farahnakian, Farshad; Álamo, Alfonso; Germinara, Vincenzo; Schweizer, Daniel; Leicht, Matthis; Anneken, Mathias; Hoppe, Adrian H.; Karalis, Aristeidis; Ashraf, Labib; Beltrán, Maria Eugenia; Hernandez, Liss; Partanen, Petteri; Markkanen, Minna
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Enhancing Peatland Classification using Sentinel-1 and Sentinel-2 Fusion with Encoder-Decoder Architecture (2024) 2024 27th International Conference on Information Fusion (FUSION) Zelioli, Luca; Farahnakian, Fahimeh; Farahnakian, Farshad; Middleton, Maarit; Heikkonen, Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Pose estimation of sow and piglets during free farrowing using deep learning (2024)
- Journal of agriculture and food research
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - SEDA: Similarity-Enhanced Data Augmentation for Imbalanced Learning (2024)
- Lecture Notes in Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Short and Long Term Vessel Movement Prediction for Maritime Traffic (2024)
- Lecture Notes in Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A Comprehensive Study of Clustering-Based Techniques for Detecting Abnormal Vessel Behavior (2023)
- Remote Sensing
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Ice-Water Segmentation Using Deep Convolutional Neural Network-Based Fusion Approach (2023) The 28th International Conference on Automation and Computing: Digitalisation for Smart Manufacturing and Systems Sheikh Javad, Farahnakian Fahimeh, Farahnakian Farshad, Heikkonen Jukka
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Sea Ice Concentration Estimation Via Fusion of Sentinel-1 and AMSR2 Based on Encoder-Decoder Architecture (2023)
- Proceedings of the IEEE international conference on intelligent transportation systems
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Abnormal Behaviour Detection by Using Machine Learning-Based Approaches in the Marine Environment: A Literature Survey (2022) 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) Farahnakian Farshad, Heikkonen Jukka, Nevalainen Paavo
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Driver Drowsiness Detection Using Deep Convolutional Neural Network (2021) 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Farahnakian Farshad, Leoste Janika, Farahnakian Fahimeh
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
