Teaching
University of Twente
As an Assistant Professor in the DMB group I am involved in the following courses:
MSc course - Advanced Computer Vision and Pattern Recognition
∼60 STUDENTS AYs 2021/2022 2022/2023 This is a project-based course that addresses advanced methods for image segmentation, object tracking and motion analysis in images, 3D computer vision, and 3D reconstruction from e.g., stereo images and statistical pattern recognition for image analysis.
MSc course - Data Science
∼700 STUDENTS AYs 2021/2022 2022/2023 This is a project-based course and is taught three times a year. It is offered to students from different disciplines at UT. In my classes I present the basics of computer vision in relation to image classification.
BSc module - Artificial Intelligence and Cyber Security, within the Intelligent Interaction Design CS/BIT module
∼300 STUDENTS AYs 2021/2022 2022/2023 The Artificial Intelligence (AI) parts introduce basic AI formalisms and methods and their applications. The course provides knowledge and techniques in search, logic, probabilistic reasoning, machine learning and applications of AI in cybersecurity.
BSc module - Smart Ways to get smart Cities Smarter, within the Smart City Engineering Project module
∼30 STUDENTS AYs 2021/2022 2022/2023 My contribution to this module is a set of lectures under the theme Introduction to Machine Learning and Smart Buildings.
BSc module - M12 Final BSc project
∼40 STUDENTS AYs 2021/2022 2022/2023 My contribution to this module is the coordinator of Track 6, which groups students who work on data science related projects. These projects are proposed by staff members from the DMB group. The tasks related to this project is guidance through the project definition process, weekly meetings, support for the preparation of the final presentation and chairing of the track in the main conference organised at the end of the module.
University of Groningen
As a lecturer at the University of Groningen I was responsible and involved in the following courses:
Image Processing
∼30 STUDENTS AY 2020/2021 The course provides insight in the basic concepts of digital image processing, from image acquisition, digitisation, and pre-processing to image enhancement, compression, restoration, segmentation, and description.
Introduction to Scientific Computing
∼130 STUDENTS AYs 2019/2020 and 2020/2021 This course focuses on scientific problem solving on topic in the context of several real-world applications. The topics I cover are sequence alignment (string algorithms), cellular automata, fractals, tomographic reconstruction, ordinary and partial differential equations.
Introduction to Machine Learning
∼80 STUDENTS AY 2020/2021 This course was given together with Prof. Michael Biehl. It was divided in two parts, supervised and unsupervised learning. I focused on the unsupervised part and taught dimensionality reduction, clustering, and outlier detection.
Introduction to Intelligent Systems
∼90 STUDENTS AY 2020/2021 This course was given together with Prof. Michael Biehl. I covered the introduction of concepts such as pattern recognition, Bayes theorem, image processing with edge detection and decision trees.
Introduction to Computer Science
TUTOR/MENTOR ∼25 STUDENTS AYs 2019/2020 and 2020/2021 The tutorials for first-year CS students are aimed at acquiring knowledge, practising skills, and deepening awareness of societal, intercultural, and ethical issues involved in computer science.
Algorithms and Data Structures in C
∼230 STUDENTS AY 2019/2020 First year course that covers data structures, trees, and graphs in C.
Software Engineering
∼90 STUDENTS AY 2018/2019 Project-based course where students work in teams to implement a software demanded by a real customer. Students gain knowledge of the different phases of the software engineering lifecycle through Scrum, Agile and teamwork.