Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Bernhard Geiger

Has grant

Graz University of Technology

Austria

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in Austria Professors in Artificial Intelligence Artificial Intelligence professors in Austria

Recent Grants

Grant: Open

GAINS - Green AI for INnovation and Sustainability

Open Date: 2025-06-16

Close Date: 2026-12-15

Grant: Open

Information Planes and Decompositions

Open Date: 2025-05-05

Close Date: 2029-05-04

Grant: Close

DiSpecs: Distant Spectators

Open Date: 2019-06-01

Close Date: 2021-08-01

Grant: Close

Information-Theoretic Markov Aggregation

Open Date: 2015-11-09

Close Date: 2018-07-08

Articles (20)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (6)

Barbara Schuppler

Graz University of Technology (90000)

AUSTRIA

View details

Mario Lovrić

Head of Laboratory

Graz University of Technology (90000)

AUSTRIA

View details

Kevin Innerebner

Graz University of Technology

AUSTRIA

View details

Roman Kern

Graz University of Technology

AUSTRIA

View details

Stephan Schmidt

Graz University of Technology (90000)

AUSTRIA

View details

Sascha Ranftl

Graz University of Technology (90000)

AUSTRIA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Bernhard Geiger

Research Interests

Make your next move.

Explore related searches

Recent Grants

Articles (20)

Meteorological Normalization or Deweathering for Predicting Air Pollutant Concentration: Pitfalls and Limitations

Geometric and Information Compression of Representations in Deep Learning

Bridging data-driven and physics-based models for lithium-ion battery state analysis and future performance assessment via active material volume fraction

Information-theoretic reduction of Markov chains

Understanding the Role of Domain Knowledge in Bayesian Optimization under Small-Data Constraints

What’s so complex about conversational speech? A comparison of HMM-based and transformer-based ASR architectures

Detecting abrupt changes in missing time series data

Trustworthy Representation Learning via Information Funnels and Bottlenecks

Diesel Combustion Parameter Estimation via Machine Learning -- A Comparative Study

Hybrid Modeling for Second-Life Battery Optimization in Light Electric Vehicles

B-PL-PINN: Stabilizing PINN Training with Bayesian Pseudo Labeling

Approximating families of sharp solutions to Fisher's equation with physics-informed neural networks

Robust Bayesian target vector optimization for multi-stage manufacturing processes

On the Role of Priors in Bayesian Causal Learning

Utilizing neural networks to supplant chemical kinetics tabulation through mass conservation and weighting of species depletion

Robust Bayesian target value optimization

Virtual Sensors in Small Engines - Previous Successes and Promising Future Use Cases

Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks

A Comparison of Virtual Sensors for Combustion Parameter Prediction of Gas Engines Based on Knock Sensor Signals

Solving multi-objective inverse problems of chained manufacturing processes

Collaborators (6)

Barbara Schuppler

Mario Lovrić

Kevin Innerebner

Roman Kern

Stephan Schmidt

Sascha Ranftl

Make your next move.