The Artificial Intelligence and Machine Learning [AIML] chair at the Institute of Computer Science covers the area of traditional machine learning and deep learning. Our research focuses on supervised and unsupervised learning focusing on deep neural networks with application areas in natural language processing, image recognition, video analysis, remote sensing and time series data in financial markets.

Data science refers to the use of scientific methods, processes, algorithms and systems to gain knowledge and insights from data in various forms, both structured and unstructured. The research focuses on the following areas: -Data Science, Artificial Intelligence, Machine Learning, Knowledge Representation; -Natural Language Processing, Word-Embedding, Distributional Semantics, Multimodal Semantics; -Big Data, Linked Data, Semantic Web, Knowledge Graphs

Our research focuses on coding theory and post-quantum cryptography. With our results we aim to improve digital communication technologies in their reliability, efficiency and security. In particular, we develop new error correcting codes and decoding algorithms for modern applications, such as distributed storage, network communication and quantum computers. Furthermore, we are very active in developing and analyzing new cryptographic methods for secure communication in the soon to come age of quantum computers. Here we mostly focus on code-based and isogeny-based cryptography.

In our research group, we explore interactions among devices and people in ubiquitous environments. Our focus is on the integration of physical things into the Web, on increasing the autonomy of Web-enabled devices and on making interactions of connected devices intelligible for people.

Our research interests are centered around information security and applied cryptography, with the larger goal of safeguarding communications and providing strong privacy guarantees. We are currently active in multiple areas including the design of provably secure cryptographic protocols and cryptographic primitives that can be employed for reliable authentication, outsourcing computations in cloud-assisted settings, network security problems as well as secure and privacy-preserving machine learning.

In the Programming Group, we enjoy working on Programming Languages and Software Engineering, including languages and architectures for Distributed Systems, Reactive Programming, DevOps Organizations, and Secure Software Systems.

The human-computer interaction (HCI) research group at the University of St. Gallen designs, develops and evaluates mobile and ubiquitous user interfaces that demonstrably enhance users’ lives. Our research mission is to fit human and technological needs and empower users when using novel interfaces.

In our research group, we focus on the development and evaluation of software artifacts. We cover topics in the areas of source code analysis, the Internet of Things, and process mining to study and build event-driven software systems that adapt based on the user’s behavior and context.