Dimitris Sykas

Dimitris Sykas

Chief Technology Officer @ cloudeo

Dimitris Sykas is a Remote Sensing and a Surveying Engineer. He received his degree from NTUA in 2010, where he also received his Ph.D. in hyperspectral remote sensing in 2016.

He started his career as a Researcher Associate and Teaching Associate in the Laboratory of Remote Sensing of NTUA, since 2010 and worked at Planetek Hellas as a Remote Sensing Expert and Geospatial Analyst. From the beginning of 2015 Dimitris was positioned as Senior Technical Specialist - EO Engineer. From 2018 Dimitris works in Neuropublic as a Senior Earth Observation Expert and Data Scientist. In Neuropublic,

Dimitris has been working on developing/implementing algorithms and machine learning models for smart farming and CAP applications. Continuing, he performed PostDoc research in National Observatory of Athens regarding earth observation on agricultural applications with deep learning techniques.

Following, Dimitris joined cloudeo as the Chief Technological Officer (CTO) of the group. Dimitris is also the founder of GEO University, an online learning platform on GIS and Earth Observation. Currently, Dimitris is a researcher at the Agricultural University of Athens. He has participated in more than 18 funded EU and ESA projects, has over 19 peer reviewed scientific publications in the field of Remote Sensing, and has an international patent in hyperspectral data compression.

One of his startups, cloudeo Hellas, was recently recognised by “Elevate Greece” (Greece’s official startup registry) as the fastest growing startup of the year among 717 companies competing for the prize.

All Sessions by Dimitris Sykas

14:20 - 16:20

Workshop - Creating optical-based Earth Observation Applications

Workshop Room 105

Saturday 11.Nov / 14:20


The purpose of the workshop is to help attendees understand how optical satellite images work, how they are processed to extract results from wildfire events and predict the severity of a potential wildfire event.

They will learn about the data sources that are needed to predict the severity of wildfire events, like EFFIS, NASA Power, Sentinel-2, etc.

They will also learn how to process ESA’s COPERNICUS Sentinel-2 data using ESA’s SNAP software. SNAP is an open source common architecture for ESA Toolboxes ideal for the exploitation of Earth Observation data.

TAGS: #AI, #EarthObservation

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