class: top, left, inverse, title-slide .title[ # Personal & Company Profile ] .author[ ### Lampros Sp. Mouselimis ] .institute[ ### Monopteryx ] .date[ ### 2022
mlampros.github.io/
monopteryx-dashboard/
] --- class:hide_logo # Details .pull-left[ <img src="images/photo_small_JPG.jpg" width="45%" /> - Degree in *Business Administration* from the *University Tuebingen, Germany* - Working experience as an *external Auditor* in a *Market Research Company* - *Post-Graduate education* in *Programming* and *Data Science* - [Open source developer](https://github.com/mlampros) utilizing *R, Python, C++* - Additional details are included in my [Curriculum Vitae](https://raw.githubusercontent.com/mlampros/My.CVitae/master/docs/cv.pdf) ] .pull-right[ <img src="images/monopteryx.png" width="45%" style="display: block; margin: auto;" /> - Small-Medium-Enterprise (SME) established in October 2021 - *Business Activity:* *Data and Remote Sensing analysis* - *Office:* Rahouli, Paramythia, North-West Greece <img src="images/location.png" width="65%" height="50%" style="display: block; margin: auto;" /> - *Website:* https://monopteryx.netlify.app/portfolio/ - *VAT Nr.* EL127583185 - *Regristration Nr.* 161143028000 ]
--- class:hide_logo # Expertise .pull-left[ <img src="images/r.jpg" width="35%" /> <img src="images/shiny.png" width="35%" /> <img src="images/python.jpg" width="35%" /> <img src="images/cpp.png" width="35%" /> ] .pull-right[ - More than 10 years experience in using *R*, *Python* and the hybrid *Rcpp* R package - Utilizing *R programming* and *Rstudio* on a daily basis <img src="images/rstudio.png" width="25%" style="display: block; margin: auto;" /> - Capable of developing solutions that cover the majority of the data analysis spectrum: - machine learning based on, - tree-models (*randomforest*, *xgboost*) - rule-models (*cubist*) - algorithms for regression or classification (*support vector machines*, *generalized linear models*, *linear regression*, *extreme learning machines*) - a combination of multiple algorithms to improve the evaluation metric (*ensemble modelling*, *stacking*) - unsupervised (Clustering) & self-supervised algorithms - *Deep learning* frameworks <img src="images/keras.png" width="80" height="20" /> & <img src="images/pytorch.png" width="100" height="40" /> - implementation of R programming *shiny web application prototypes* ] --- class:hide_logo # Remote Sensing Analysis .pull-left[ <img src="images/country_level.png" width="75%" height="100%" /> <img src="images/segmentation.png" width="75%" height="100%" /> <img src="images/change_detection.png" width="100%" height="100%" /> ] .pull-right[ <img src="images/object_detection.png" width="75%" height="100%" /> Processing and analysis of satellite imagery based on *geospatial R programming packages* and *Python Deep Learning algorithms*: - *Sentinel-1* Radar Data (*ship classification* & *change detection*) - *Sentinel-2* Analysis Ready Data (*object detection* & *segmentation*) - *Copernicus* Land Cover segmentation & Digital Elevation Models - *NASA MODIS* & *Sentinel-5 TROPOMI* to monitor *air pollution* (*pm2.5*, *CH4*, *CO*, *NO2*) - *NASA VIIRS* data (*combustion* & *fire* sources monitoring) - *Planetscope* imagery for forest *change detection* (*NICFI*) - *ICESat-2* *altimeter point* data to measure ice and canopy height - *ERA-5* ECMWF data (temperature, wind & solar potential) - *Insitu* data (aeronet, OpenStreetMap) ] --- # Video Recordings & Use Cases .panelset[ .panel[.panel-name[Object Detection] <img src="images/object_detection_thumbnail.png" width="75%" height="100%" /> [https://youtu.be/3NBI-LbCsqI](https://youtu.be/3NBI-LbCsqI) ] .panel[.panel-name[OpenStreetMap DEM] <img src="images/OpenStreetMap_Digital_Elevation_Models.png" width="75%" height="100%" /> [https://www.youtube.com/watch?v=YFasPbHu_zA&t=6s](https://www.youtube.com/watch?v=YFasPbHu_zA&t=6s) ] .panel[.panel-name[Wind Energy Potential] <img src="images/wind_energy_potential.png" width="75%" height="100%" /> ] ] --- class: inverse, middle, center background-size: contain # Thank you!