Joint Lab Künstliche Intelligenz & Data Science

Kooperation des Leibniz-Instituts für Agrartechnik und Bioökonomie Potsdam und der Universität Osnabrück

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Promovierende und ihre Projekte

Kevin von Bargen

Intelligent Processes for High-Quality Fruit Drying

Viacheslav Barkov (Slava)

Modeling sensor data for knowledge discovery and explainable decision-making in fruit storage

Lennart Kaiser

Networks as a Sensor in Agriculture

Clara Lößl

Integrated AI analysis of geometric and spectral UAV data using machine learning to derive
high-resolution bio-physical and bio-chemical plant properties in agroforestry systems

Moritz Lucas

Monitoring biodiversity of agroforestry systems, using multisensor Earth-Observation data and deep learning

Anh-Duy Pham

Informed Machine Learning on Sparse Data and Information in the context of barn climate and emissions

David Rolfes

Reconfigurable ROS Nodes for Modular Agricultural Robots

Jonas Schmidinger

Trustworthy Intelligent Soil Mapping

Verena Tessaro

Simulation of Environment Sensors – towards digital twins of autonomous agricultural machines

Tim Wollschläger

Development of predictive models to control the anaerobic digestion process

zu besetzen

Deployment Strategies for in-situ Sensors in Agriculture

zu besetzen

Explainable AI Methods for Multimodal Data in the Bioeconomy


Dr. Thomas Hänel

Postdoc für den Forschungsbereich 2:
Autonome Systeme - Sensornetzwerke, Robotersteuerung und Datenerfassung

Dr. Olivier Kashongwe

Postdoc für den Forschungsbereich 3:
Hybride Prozess- und Systemmodellierung - Anwendungsbasierte Entwicklung von Prozesssteuerungen und Digitalen Zwillingen

zu besetzen

Postdoc für den Forschungsbereich 1:
Künstliche Intelligenz und Data Science - Methodenentwicklung und Datenanalyse

Assoziierte Promovierende

Daniel Barrelmeyer

Systematic Testing of Agricultural Robots in Simulation and Reality with a Focus on automatic Design and Optimization of Sensor Configurations for Tractor-Implement Combinations

Deepak Hanike Basavegowda

Biodiversity monitoring in semi-natural grasslands using deep learning and Unmanned Aerial Vehicles (UAVs)

Ingvar Daute

Liability for Artificial Intelligence – A Discourse History

Maren Pukrop

Analysis of the segetal flora of agro-ecosystems in high-resolution UAV data using deep learning techniques

Nora Rüter

Patent infringement standards in the field of medical law with regard to the duty of care

Jörg Schemminger

Hybrid physics-based digital twins accounting for process and product variability in postharvest applications

Andreas Schliebitz

Continuous Image Classification on Data Streams using Contrastive Learning and Cluster Analysis

Lisa Schulz-Nielsen


Tjark Schütte

Navigation of Unmanned Ground Vehicles in Horticulture Using A-Priori Information Derived from Remote Sensing Data

Leonid Schwenke

Decomposing Time Series into Symbolic High-Level Features and Relations using Saliency Methods

Muhammad Tayyab

Development of an intelligent optical control drying system for fruits and vegetables

Jason Tenta

Access to and legal protection of (non-personal) data; Data contract law

Mandala von Westenholz

Poisson Point Processes in application of data analysis