Suriyah Dhinakaran
Bolzano
Summary
Skilled Geospatial Data Engineer with a strong background in developing machine learning workflows for environmental and meteorological applications. Expertise in handling multi-dimensional data, statistical downscaling, and geospatial analysis.
Overview
2
2
years of professional experience
Work History
Junior Researcher - Advanced Computing Group
Institute for Earth Observation – Eurac Research
04.2024 - Current
- Designed and implemented a two-stage downscaling approach for climate variables, increasing resolution from 0.25 x 0.25 to 1 km using machine learning (ESRGAN) and regression techniques
- Developing downScaleML, a Python package for high-performance environmental data processing in digital twin applications
- Researching data fusion techniques for flood and drought forecasting, leveraging hydrological simulations in the Alpine region
- Contributing in a key role to the development of the first EOPF ZARR format for Sentinel images, in collaboration with European Space Agency (ESA)
- Established strong working relationships with stakeholders including participants, community partners, and other academic collaborators.
- Collaborated with cross-functional teams to develop comprehensive research strategies and methodologies.
- Regularly updated knowledge base through attending workshops, seminars, and professional development events related to the field of study.
- Demonstrated adaptability by flexibly adjusting to changing project requirements and evolving research objectives.
- Supported senior researchers in the development of grant proposals, leading to increased funding opportunities.
Trainee Researcher Advanced Computing Group – AI/ML for Climate Data Augmentation
Institute for Earth Observation – Eurac Research
04.2023 - 03.2024
- As an ERASMUS+ trainee, initiated downscaling development for ECMWF SEAS5 seasonal forecast data (2m temperature and precipitation) using machine learning, leading to a master's thesis titled ‘Enhancing Seasonal Climate Forecasting for the Alpine Region Through Machine Learning Statistical Downscaling’
- Actively contributed to the environmental aspect of the interTwin project by creating and maintaining the open-source Python package ‘interTwin-downScaleML’, a thematic module under the Horizon Europe digital twin initiative.
- Developed strong working relationships with trainees, fostering a supportive learning environment that eventually led me to a full-time researcher position.
Student Assistant – Under the Supervision of Prof. Edzer Pebesma
Spatio-Temporal Modelling Laboratory - Institut für Geoinformatik(ifgi)
10.2022 - 03.2023
- Enhanced accessibility and functionality of 'Spatial Data Science with Applications in R' online book by developing Python codes complementing existing R counterparts, facilitating comprehensive geospatial data analysis
Education
Master of Science - Geoinformatics and Spatial Data Science
University of Münster
Münster, Germany04.2024
Bachelor of Engineering - Geoinformatics
Anna University, College of Engineering, Guindy
Chennai, India04.2019
Skills
- Data Science & Analytics
- Geospatial Applications Expertise
- Workflow Management
- Python Development
- R Statistical Modeling
- Bash Scripting
- Proficient in Machine Learning
- Advanced Deep Learning
- Skilled in Scikit-learn for Machine Learning
- PyTorch Framework Expertise
- Skilled in TensorFlow Development
- Keras Framework Proficiency
- Computer Vision
- Image Analysis Techniques
- Spatial and Temporal Analysis
- Python Scripting
- Workflow Automation Expertise
- Data Visualization
- Multi-dimensional data processing
- Xarray
- Dask Data Processing
- NetCDF File Handling
- GRIB
- TileDB
- Zarr File Format Expertise
- Earth observation
- Satellite Imagery Interpretation
- OpenEO Implementation Skills
- STAC Implementation Experience
- Cdo
- Big Data Processing
- Environmental Modeling
- Implementation of Digital Twins
- Advanced High Performance Computing
- Proficient in Containerization
- Docker Deployment Skills
- Continuous Integration/Continuous Deployment
- AWS
- Linux Proficiency
- Version Control Expertise - Git
- Research methodology
- Microsoft office
- Effective communication
- Team collaboration
- Multitasking capacity
Conference Proceedings
- IEEE IGARSS 2024, Athens, Greece, Dhinakaran, Suriyah, Crespi, Alice, Jacob, Alexander, Pebesma, Edzer, Enhancing Seasonal Climate Forecasting for the Alpine Region Through Machine Learning Statistical Downscaling, 1683-1688, 10.1109/IGARSS53475.2024.10642272
- EGU 2024, Vienna, Austria, Application of Machine Learning Statistical Downscaling to Seasonal Climate Forecasts for the Alpine Region, Oral Presentation, Downscaling: methods, applications and added value
Hackathon Endeavours
- OEMC Hackathon: EU Land Cover Classification, 09/01/23, Championed the hackathon collaboratively (team of two), defeating global competition to classify 72 diverse land cover classes across Europe using Earth Observation data and machine learning, aimed to enhance land cover mapping capabilities for the European Union. Implemented a combination of Light Gradient Boosting Machine (LGBM) Classifier with Stratified K-Fold cross-validation and a Keras Multi-Layer Perceptron (MLP), leveraging comprehensive feature engineering of 416 Earth Observation data layers (satellite imagery, climate data, topography, human influence) for land cover classification.
- OEMC Hackathon: Global FAPAR Modeling, 09/01/23, Collaboratively secured the runner-up position in a global competition of data scientists and researchers. Employed LGBM Regression, advanced cross-validation, and feature engineering to predict vegetation health in a complex dataset with 32 Earth Observation data layers, including satellite, climate, and topographic information.
Languages
English
Advanced (C1)
Tamil
Bilingual or Proficient (C2)
Timeline
Junior Researcher - Advanced Computing Group
Institute for Earth Observation – Eurac Research
04.2024 - Current
Trainee Researcher Advanced Computing Group – AI/ML for Climate Data Augmentation
Institute for Earth Observation – Eurac Research
04.2023 - 03.2024
Student Assistant – Under the Supervision of Prof. Edzer Pebesma
Spatio-Temporal Modelling Laboratory - Institut für Geoinformatik(ifgi)
10.2022 - 03.2023
Master of Science - Geoinformatics and Spatial Data Science
University of Münster
Bachelor of Engineering - Geoinformatics
Anna University, College of Engineering, Guindy
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