People

Andrzej Wasowski

Head of Group

Professor of software engineering at IT University of Copenhagen, expert on software quality and reliability. He has experience with probabilistic modeling including formal semantics of programs, concurrency, model checking, model-driven engineering, variability-modeling, testing and software architecture. Prof. Wasowski has worked with quality of robotics software platforms and bug elimination in other open source projects. This interest is shifting towards safety and reliability of robotics and AI software in general.

Christoph Seidl

… is an Associate Professor for Software Engineering at IT University of Copenhagen. His research interests are highly-configurable software systems/variability modeling (e.g., Software Product Lines), software evolution, model-driven software engineering, language engineering, and software visualization. As part of his research, he has worked with companies, among others, in the automotive industry, aerospace engineering, and virtual reality.

Willard Rafnsson

… is an Associate Professor at the IT University of Copenhagen (ITU). His research is at the intersection of formal methods, programming languages, and security. His research focuses on proving that software preserves the confidentiality of data. He is building tools for this task, that scale to real programming languages and platforms.

Mahsa Varshosaz

… is an assistant professor in the SQuaRe group at IT University of Copenhagen. Mahsa’s research is mostly focused on quality assurance and safety of software systems. She is interested in both theoretical and practical aspects of modeling, testing and verification of systems and the challenges in application of such techniques in different domains. She has experience with application of model-based testing techniques for families of software systems also known as software product lines. Mahsa’s latest research includes testing of underwater robotic systems in the REMARO project and automatic program repair for Linux kernel as a part of the INSIGHT project.

Raul Pardo Jimenez

… is an Assistant Professor in the SQUARE group at the IT University of Copenhagen. His research is focused on developing rigorous techniques to design, analyze and build software to protect online privacy. His interests lie at the intersection of formal methods, online privacy and computer security. He has done research on privacy for social networks, Internet of Things (IoT) and data analytics. Within these topics, he is working on privacy risk analysis, formal verification of privacy legal requirements, probabilistic programming, and Bayesian data analysis.

Alfredo Cruz

… is a PhD student at the SQUARE group. Currently his focus is on Automatic Program Repair of API misuses with a closer aim at Locking API misuses in the Linux Kernel. Alfredo started his (quasi) research adventure in Compilers and Programming languages moving on then to Computational Geometry, Wireless Networks and Distributed Computing. Basically he enjoys (so far) solving problems with as little black magic (ML methods) as possible.

Adrian Hoff

… joined SQUARE in October ’20. His research interests are Software Engineering, Software Visualization and Software Product Lines. In his PhD project “Immersive Software Archaeology” (ISA), Adrian develops software visualizations in virtual reality as a means for rediscovering unfamiliar large-scale legacy software systems’ architecture and design.

Laura Weihl

… is a PhD Student at the SQUARE group since May 2021. Her background is in Maths, Computer Science and Machine Learning. She has worked on Facial Recognition using Neural Networks, more recently she has been interested in Risk Analysis in Iris recognition systems. Right now she is working on fusing Property-based Testing with Probabilistic Programming. If you don’t find her coding she is playing piano or singing in a choir.

Mahya Mohammadi Kashani

… is a PhD student on the project Reliable AI for Marine Robotics (REMARO) at the SQUARE group. Her main research interests are concentrated in the area of machine vision and pattern recognition. She has become interested in the assessment of plan selection of the robots and probabilistic decision making, recently. Before joining SQUARE group, she worked for one year as a computer vision engineer. There she was programming and developing vision of waste segregation robots. Before that she has acquired her M.Sc. degree in Computer Engineering with a major in AI and Robotics. Alongside AI & coding, she really cares about environmental issues and climate change.

Sergio Daniel Quijano

… is a PhD student on the project Reliable AI for Marine Robotics (REMARO). His research interests are (Model-Based) Systems and Software Engineering, Safety Engineering, Self-Adaptive and Multi-agent Cyber-Physical Systems. In his PhD project, Sergio investigates methods for Model-Based testing of probabilistic properties to support safety assessments for underwater robots.

Mohsen Ghaffari

… is a PhD student at the SQUARE group since November 2021. His research interests are Reinforcement Learning, Multi-agent systems, Smart Grids, and Game Theory. Mohsen has worked on Demand Management in Smart Grids using Multi-agent Reinforcement Learning, Shortest Path on Uncertain Networks, HMM-based Detecting and Predicting, and Police Patrolling. Recently he has been interested in the safety and explainability of Reinforcement Learning. Right now, he is working on symbolic Reinforcement Learning.

Luiza Ribeiro Marnet

… is a PhD student on the Reliable AI for Marine Robotics (REMARO) project at the SQUARE group. Luiza’s master degree was in Artificial Inteligence and had a focus on the usage of neural networks to analyze acoustic emission parameters to identify the propagation phase of pipeline cracks. In the REMARO project, Luiza works with deep learning models for classification and segmentation of underwater images. More specifically, Luiza is studying the use of predictive uncertainty for more efficient image selection with active learning, identification of shifts in data patterns and identification of predictions with large-error probability.