M.Sc. Ana Petrovska
Technische Universität München
Informatik 4 - Lehrstuhl für Software & Systems Engineering (Prof. Pretschner)
- Tel.: +49 (89) 289 - 17830
- Raum: 5611.01.061
- ana.petrovska@tum.de
Office hours: Thursdays from 16:00 - 17:00.
ABOUT ME
Since February 2017 I am a doctoral candidate at the Chair of Software and Systems Engineering led by Prof. Alexander Pretschner at the Technical University Munich. I completed my master studies at TUM Department of Informatics, as well, in December 2016. The title of my M.Sc. thesis was "Impact of contention parameters on fair coexistence of Unlicensed-LTE and Wi-Fi in 5GHz ISM Band" and was done in collaboration with Intel Corporation. In 2014 I completed my B.Sc. with thesis titled "An embedded system for access control with a Bluetooth module" at the Faculty of Computer and Information Science, University of Ljubljana in Slovenia.
I am extremely passionate and active in the field of gender equality, especially when it comes to the representation of women in STEM.
RESEARCH INTERESTS
- Self-adaptive cyber-physical systems under uncertainties
- Learning in dynamic, open context
- Multi-agent systems
THESIS TOPICS AND SUPERVISION
If you are interested in writing a Bachelor or Master thesis which is related to my research interests, please contact me by email.
In progress:
- Logical Architecture for Engineering Smart Self-Adaptive Cyber- Physical Systems (Guided research)
- Decentralized Partially Observable Markov Decision Processes for Planning in Smart Self-Adaptive Cyber-Physical Systems (Guided research)
- Multi-Source Knowledge Aggregation in Subjective Logic (M.Sc. Thesis)
Completed:
- From simulation to a real system—A ROS-Based Multi-Robot System (B.Sc. Thesis), 2019
- Mining the unconscious bias in TUM (Application project), 2019
- Design and Implementation of ROS-Based Simulated Multi-Robot Systems for Data Collection (M.Sc. Thesis), 2018
- Runtime Verification of Dynamic Architectures (M.Sc. Thesis), 2018
- Self-adaptive cyber-physical systems utilizing different machine learning techniques (Guided research), 2018
- Anomaly detection and prediction in distributed software systems using machine learning (B.Sc. Thesis), 2017
TEACHING
Summer semester 2019
- Systems Engineering (MSE) (IN8015)
- Practical course: Smart Self-Adaptive Cyber-Physical Systems–A Road towards Autonomous Systems (IN0012, IN2106)
Summer semester 2018
Winter semester 2017/18
Summer semester 2017
VOLUNTARY PROJECTS AND ACTIVITIES
- IFF Officer at Women in CS @ TUM (Informatik Forum Frauen - IFF) (2015 - present)
- IN.TUM Gender Equality Officer (July 2017 - present)
PUBLICATIONS
- EURECA: Epistemic Uncertainty Classification Scheme for Runtime Information Exchange in Collaborative System Groups. SICS Software-Intensive Cyber-Physical Systems, 2019 more…
- Learning Approach for Smart Self-Adaptive Cyber-Physical Systems. 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), IEEE, 2019 more…
- Detecting Architectural Erosion using Runtime Verification. 12th Interaction and Concurrency Experience (ICE 2019), 2019 more…
- Machine learning-based run-time anomaly detection in software systems: An industrial evaluation. 2018 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE), IEEE, 2018 more…
- Requirements for modeling dynamic function networks for collaborative embedded systems. , Workshops at Modellierung 2018, Modellierung in der Entwicklung von kollaborativen eingebetteten Systemen (MEKES). , 2018 more…
- Towards Context Modeling for Dynamic Collaborative Embedded Systems in Open Context. , Tenth International Workshop Modelling and Reasoning in Context (MRC). , 2018 more…
- Nequivack: Assessing Mutation Score Confidence. 2016 IEEE Ninth International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2016, 152-161 more…