I am a PhD candidate at IST Austria at the research group of Tom Henzinger. My research focuses on Machine Learning, Formal Methods, and Robotics.

Publications

* denotes equal contributions

2022

Stability Verification in Stochastic Control Systems via Neural Network Supermartingales
Mathias Lechner*, Đorđe Žikelić*, Krishnendu Chatterjee, Thomas A. Henzinger
Accepted at the AAAI Conference on Artificial Intelligence (AAAI) , 2022
GoTube: Scalable Stochastic Verification of Continuous-Depth Models
Sophie Gruenbacher, Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A. Henzinger, Scott A. Smolka, Radu Grosu
Accepted at the AAAI Conference on Artificial Intelligence (AAAI) , 2022
Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars
Axel Brunnbauer*, Luigi Berducci*, Andreas Brandstätter*, Mathias Lechner, Ramin Hasani, Daniela Rus, Radu Grosu
Accepted at the IEEE International Conference on Robotics and Automation (ICRA), 2022

2021

Infinite Time Horizon Safety of Bayesian Neural Networks
Mathias Lechner*, Đorđe Žikelić*, Krishnendu Chatterjee, Thomas A. Henzinger
In Conference on Neural Information Processing Systems (NeurIPS), 2021
Causal Navigation by Continuous-time Neural Networks
Charles J Vorbach*, Ramin Hasani*, Alexander Amini, Mathias Lechner, Daniela Rus
In Conference on Neural Information Processing Systems (NeurIPS), 2021
On-Off Center-Surround Receptive Fields for Accurate and Robust Image
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu
In International Conference on Machine Learning (ICML), 2021
Adversarial Training is Not Ready for Robot Learning
Mathias Lechner, Ramin Hasani, Radu Grosu, Daniela Rus, Thomas A. Henzinger
In IEEE International Conference on Robotics and Automation (ICRA), 2021
Scalable Verification of Quantized Neural Networks
Thomas A. Henzinger*, Mathias Lechner*, and Djordje Zikelic* (alphabetical)
In AAAI Conference on Artificial Intelligence (AAAI) , 2021
Liquid Time-constant Networks
Ramin Hasani*, Mathias Lechner*, Alexander Amini, Daniela Rus, and Radu Grosu
In AAAI Conference on Artificial Intelligence (AAAI) , 2021
On the Verification of Neural ODEs with Stochastic Guarantees
Sophie Grünbacher, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, and Radu Grosu
In AAAI Conference on Artificial Intelligence (AAAI) , 2021

2020

Neural circuit policies enabling auditable autonomy
Mathias Lechner*, Ramin Hasani*, Alexander Amini, Thomas A. Henzinger, Daniela Rus, and Radu Grosu
In Nature Machine Intelligence, 2020
The Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
Ramin Hasani*, Mathias Lechner*, Alexander Amini, Daniela Rus, and Radu Grosu
In International Conference on Machine Learning (ICML), 2020
Learning Representations for binary classification without backpropagation
Mathias Lechner
In International Conference on Learning Representations (ICLR), 2020
An SMT Theory of Fixed-Point Arithmetic
Marek Baranowski, Shaobo He, Mathias Lechner, Thanh Son Nguyen, and Zvonimir Rakamaric
In International Joint Conference on Automated Reasoning (IJCAR), 2020
Gershgorin Loss Stabilizes the Recurrent Neural Network Compartment of an End-To-End Robot Learning Scheme
Mathias Lechner*, Ramin Hasani*, Daniela Rus, and Radu Grosu
In IEEE International Conference on Robotics and Automation (ICRA), 2020
How Many Bits Does it Take to Quantize Your Neural Network? Scheme
Mirco Giacobbe*, Thomas A. Henzinger*, and Mathias Lechner* (alphabetical)
In International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 2020
Lagrangian Reachtubes: The Next Generation
Sophie Gruenbacher, Jacek Cyranka, Mathias Lechner, Md. Ariful Islam, Scott Smolka, and Radu Grosu
TC-DES and TC-HS Outstanding Student Paper Prize
In IEEE Conference on Decision and Control (CDC), 2020

2019

Response characterization for auditing cell dynamics in long short-term memory networks
Ramin Hasani*, Alexander Amini*, Mathias Lechner, Felix Naser, Radu Grosu, and Daniela Rus
In International Joint Conference on Neural Networks (IJCNN), 2019
Designing worm-inspired neural networks for interpretable robotic control
Mathias Lechner*, Ramin Hasani*, Manuel Zimmer, Thomas A. Henzinger, and Radu Grosu
In IEEE International Conference on Robotics and Automation (ICRA), 2019

Awards

Outstanding Reviewer Award 2021 at the IEEE International Conference on Robotics and Automation (ICRA)

Distinguished Young Alumnus-Award 2018 Faculty of Informatics at TU Wien

Competitions

First Place In F1TENTH - Autonomous Racing Grand Prix at IFAC 2020