Personal Picture

Daniele Gadler

daniele.gadler at


You may download the latest version of my CV at this link.

I am a trilingual Data scientist (English, German, Italian) with a passion for data management and productionizing machine learning models, and hold a MSc. in Computer Science and Networking (cum laude) from Scuola Superiore Sant’Anna and the University of Pisa - graduation year 2019.

Data scientist experience: Starting from March 2021, I have been working as a data scientist at ONE LOGIC GmbH in Frankfurt am Main, Germany. Before that, I worked at Südtiroler Informatik AG on modelling and predicting vehicles' traffic trends on the main roads of the Province of Bolzano, Italy and developed models to predict COVID insurgence in patients based on their symptons.

Research experience: Previously, at the National Research Institute of Pisa, I worked on research for Recurrent Neural Network quantization in IoT devices. At the Free University of Bolzano, I investigated the usage of Hidden Markov Models for modelling system usage in complex systems, and at the Technische Universität Kaiserslautern studied techniques to identity Wi-Fi devices in networks based on packets’ electromagnetic fingerprint.


🚀~/Work Experience

🏆~/Awards and Scholarships

📄~/Habilitations and certificates




Proficient - fluent
Advanced - fluent

💻 ~/Projects

Automatic Hidden Markov Model Generation (2016 - 2019)

Scripts to generate Hidden Markov Models automatically and manually, based on the paper Mining Logs to Model the Use of a System implemented in Java Hadoop and R.

Sobel Filter on CUDA, C and OpenCV (2019)

Native C, CUDA, OpenCV versions of the Sobel Filter, an algorithm computing the countour of an image based on the partial derivatives of an image over the X and Y axes.

OpenMined - PySyft project (2019 -)

Collaborator to the PySyft project of the OpenMined community with code fixes for the training of Recurrent Neural Networks, Long-Short Term Memory Models, Gated Recurrent Units and optimizations for low-power IoT devices such as Raspberry PIs.
SPADE - Sensing, Processing and Analyzing Data in an Embedded IoT Device (2019)

Implementation of a machine-learning powered system for the predictive maintenance of machines based on a Beagleboard green and an accelerometer.

Persistent World Scripts for Warband (2014 - 2018)

Set of scripts for the "Persistent World" and "Persistent Kingdoms" mod of Mount & Blade: Warband that add roleplay and persistent functionalities to the game, connected to a MySQL Database and a PHP backend.
Data Mining (2018-2019)

Application of data mining techniques such as clustering, supervised classification and association rules to the task of banking customer default prediction in Python. "Lost in Data" team in the 2018-2019 Kaggle challenge.

Dot Matrix Printer (2014-2015)

Hand-made printer using felt tip pens as ink, created based on an Arduino and a Raspberry PI. The system is fully accessible via a web-based interface for uploading images to be printed.
JSnake (2015)

The famous Nokia phone game "Snake" implemented in the Java programming language using, among others, multithreading and generics.

💼 ~/Lecture Notes

Lecture Notes taken in class during the Master's in Computer Science and Networking 2017-2019 in Pisa and during my Bachelor. All the material released is intended for didactic use only.

Academic Year 2018-2019

Academic Year 2017-2018

Academic Year 2016-2017 - Technische Universität Kaiserslautern