Marco Kryda

Marco Kryda, M.Sc.

Room: -

Phone: -

E-Mail: -

Office hours: -

Since 2019 | Ph.D. Student at Engineering Risk Analysis Group, Technical University of Munich
2017 (Aug - Dec) | Exchange Semester, Nanyang Technological University (Singapore)
2016 - 2019 | M.Sc. Applied and Engineering Physics, Technical University of Munich
2015 (Aug - Dec) | Exchange Semester, Hong Kong University of Science and Technology
2015 (Feb - Aug) | Internship Production Planning, Dr. Ing. h.c. F. Porsche AG (Stuttgart, Germany)
2013 - 2016 | B.Sc. Physics, Technical University of Munich

Learning the reliability of perception sensors in autonomous driving from fleet-based data
Definition of environment perception errors
Development of stochastic models for sensor dependence

SS 20: Teaching assistant for the lecture “ Reliability of Engineering Systems ”, TUM.
WS19/20: Teaching assistant for the lecture “Risk Analysis”, TUM.

Master's thesis: Dominik Hesping (2020) - Construction and Evaluation of Machine Learning Models for Predicting a Multivariate Probability Distribution of Design Soil Parameters

M. Kryda, M. Qiu, M. Berk, B. Buschardt, T. Antesberger, R. German, D. Straub (2021). Associating sensor data and reference truth labels: A step towards SOTIF validation of perception sensors. Sixth IEEE International Workshop on Automotive Reliability, Test and Safety (ARTS).

M. Qiu, M. Kryda, F. Bock, T. Antesberger, D. Straub, R. German (2021). Parameter tuning for a Markov-based multi-sensor system. Euromicro SEAA 2021.

M. Kryda, M. Berk, B. Buschardt, and D. Straub (2021). Application of a statistical approach to assess the sensor perception reliabilities of automated driving vehicles. SAE WCX World Congress Experience Digital Summit.

M. Hauke, D. Weidlich, C. Ganter, D. Karampinos (2019). Insights from the Configuration Model theory accelerate Bloch simulations for dictionary-based T2 mapping. ISMRM 27th Annual Meeting & Exhibition, Montreal, Canada.