Teaching

• Advanced Machine Learning for Data-driven-Health, KTH Royal Institute of Technology, Stockholm, Sweden, 2026.
• Software Engineering, Project Course, KTH Royal Institute of Technology, Stockholm, Sweden, 2025.
• Seminar Series on Data Science, University College Dublin, Dublin, Ireland, 2019 (Responsible for 20% of the course).
• Machine Learning, University College Dublin, Dublin, Ireland, 2019 (Guest Lecturer).
• Introduction to Object Oriented Programming, Universidad del Valle, Cali, Colombia, 2009.
• Algorithms and Programming, Universidad del Valle, Cali, Colombia, 2009.

Master Students

• Jonathan Axelsson, Chalmers University of Technology, Sweden, 2026.
• Lucas Werelius, KTH, Sweden, 2026 (co-supervised with Ninib Baryawno).
• Heqiao Wang, KTH / Universidad Politécnica de Madrid, Sweden, 2026 (co-supervised with Ninib Baryawno).
• Helena Chamberlain Alvarado, KTH, Sweden, 2026 (co-supervised with Fahim Ebrahimi).
• Miguel Caetano Nunes, KTH / Karolinska Institute / Stockholm University, Sweden, 2026 (co-supervised with Fahim Ebrahimi).
• Joel Sundin, Uppsala University, Sweden, 2026 (co-supervised with Tania Costa and Fahim Ebrahimi).
• Xu Zuo, KTH, Sweden, 2026 (co-supervised with Silun Zhang).
• Yuyun Pan, Stockholm University, Sweden, 2025 (co-supervised with Ninib Baryawno).
  Machine Learning for Liver Fibrosis Assessment Using Sirius Red-Stained Pathology Slides [pdf].
• Johanna Hansen, KTH, Sweden, 2023.
  Delineation of vegetated water through pre-trained convolutional networks [pdf].
• Ezio Cristofolu, KTH, Sweden, 2023.
  Using Satellite Images and Deep Learning to Detect Water Hidden Under the Vegetation [pdf].
• Ioannis Iakovidis, KTH, Sweden, 2023.
  Using Satellite Images And Self-supervised Deep Learning To Detect Water Hidden Under Vegetation [pdf].
• Robert-Andrei Damian, KTH, Sweden, 2022.
  Finding duplicate offers in the online marketplace catalogue using transformer based methods[pdf].
• Angel Luis Gonzalez, KTH and RISE, Sweden, 2021 (co-supervised with Amir H. Payberah).
  Transformer-based Multistage Architectures for Code Search [pdf].
• Marcus Hägglund, KTH and RISE, Sweden, 2021 (co-supervised with Amir H. Payberah and Martina Scolamiero).
  Deep Learning Approaches for Clustering Source Code by Functionality [pdf].