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.

PhD Students

• Francesca Visalli, KTH, Sweden, 2031 (co-supervised with Fahim Ebrahimi and Matilda Larsson).

Master Students

• Marina Burgos Martín, KTH, Sweden, 2027 (co-supervised with Fahim Ebrahimi).
• Filip Forsberg, KTH, Sweden, 2027 (co-supervised with Fahim Ebrahimi).
• Victor Engdahl, KTH, Sweden, 2026 (co-supervised with Ninib Baryawno).
• Jonathan Axelsson, Chalmers University of Technology, Sweden, 2026 (co-supervised with Fahim Ebrahimi).
• Lucas Werelius, KTH, Sweden, 2026 (co-supervised with Ninib Baryawno).
• Xu Zuo, KTH, Sweden, 2026 (co-supervised with Silun Zhang).
• Carolina Zetterblad, KTH, Sweden, 2026.
• Helena Chamberlain Alvarado, KTH, Sweden, 2026 (co-supervised with Fahim Ebrahimi).
  Quantifying Fibrosis for Staging Metabolic Dysfunction-Associated Steatotic Liver Disease from Hispathology Images using Deep Learning [pdf].
• Joel Sundin, Uppsala University, Sweden, 2026 (co-supervised with Tania Costa and Fahim Ebrahimi).
• Lucia Karens, KTH, Sweden, 2026. Detecting Wetlands Using Self-Supervised Convolutional Neural Networks With Data Normalization [pdf].
• Heqiao Wang, KTH / Universidad Politécnica de Madrid, Sweden, 2026 (co-supervised with Ninib Baryawno). Transcriptomic Prediction of Five-Year Disease-Control Failure Across Nine TCGA Cohorts [pdf].
• 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].