Academic Work

2025

  • Master Thesis Main Supervisor: Interactive Explanations in Clinical Decision Support: A Comparative Study of Exploratory and Explanatory XUIs for Clinical Prediction Models (30 ECTS). Supervised student: Kent Fredriksdotter.
  • Master Thesis Main Supervisor: Assessing Explainable Machine Learning Tools for Predicting Depressive Disorders in Primary Care: A Usability and Trust Evaluation (30 ECTS). Supervised student: Guilherme Gryschek.
  • Master Thesis Main Supervisor: AI-Driven Approaches for Developing a Decision-Support System in Tuberculosis Diagnosis Using Chest X-Ray Data (30 ECTS). Supervised student: Sreeja Mohanan Nair.
  • Master Thesis Main Supervisor: Global Sensitivity Analysis for Drug-Drug Interaction Prediction Models: A Case Study (30 ECTS). Supervised student: Muna Mohammad Ahmad Shati.
  • Master Thesis Main Supervisor: Reusable Template for Decision-Making on Imaging Needs in Urinary Tract Infection Cases Using Data Mining in Healthcare Operations (30 ECTS). Supervised student: Prabhu Raj Singh.

2024

  • Master Thesis Main Supervisor: Improving Customer Churn Prediction Using Machine Learning (30 ECTS). Supervised student: Achyut Jagini.
  • Bachelor Thesis Main Supervisor: Go Phish – Detecting Phishing Attacks with Pre-Prompted LLMs as Evaluation Tools (15 ECTS). Supervised students: Sebastian Fredriksson Karvelas, Karl Frohm Krischel.
  • Bachelor Thesis Main Supervisor: Literature Review on Threats of AI for Cybersecurity (15 ECTS). Supervised students: Velvet Paul, Rebeka Borovnik.
  • Bachelor Thesis Main Supervisor: Literature Review on Bias in Generative AI: How the Specific Data Input can Affect the Result (15 ECTS). Supervised students: Olivia Lindh, Marlene Lund.
  • Bachelor Thesis Main Supervisor: Machine Translation Between Swedish and Japanese (15 ECTS). Supervised students: Mats Jarnstam, Patrick Westberg.
  • Bachelor Thesis Main Supervisor: Ethics of Artificial Intelligence in Mental Health Treatment (15 ECTS). Supervised student: Victor Reinmann.
  • Bachelor Thesis Main Supervisor: Automated testing – Angluins Algorithm (15 ECTS). Supervised student: Mårten Mckie.
  • Master Thesis Main Supervisor: Enhancing Multi-Agent Double Deep Q-Networks (MADDQN) for Financial Trading: A Multi-Faceted Optimization Approach (30 ECTS). Supervised students: Michael Beck, Augustas Perminas.
  • Teaching Assistant: Machine Learning (VT 2024), M. Sc. Course, Department of Computer and Systems Sciences, Faculty of Social Sciences, Stockholm University, Sweden. Direct supervisor: Professor Panagiotis Papapetrou.

2023

  • Master Thesis Main Supervisor: Image Counterfactual Explanations using Deep Generative Adversarial Networks. (15 ECTS). Supervised students: Ning Wang.
  • Master Thesis Main Supervisor: A Distance Measure For Both Continuous and Categorical features in a Data Vector. (30 ECTS). Supervised students: Salam Hilmi, Elina Zake.
  • Master Thesis Main Supervisor: Application of Inherently Interpretable, Highly Accurate Machine Learning. (30 ECTS). Supervised students: Maria Luiza Chirita, Bernardo Cunha de Miranda.
  • Master Thesis Main Supervisor: Developing a Highly Accurate, Locally Interpretable Neural Network for Medical Image Analysis (30 ECTS). Supervised student: Rony Ventura.
  • Master Thesis Main Supervisor: Improving XAI Explanations for Clinical DecisionMaking – the Physicians’ Perspective (30 ECTS). Supervised student: Ulf Lesley.
  • Teaching Assistant: Principles and Foundations of Artificial Intelligence (HT 2023), M. Sc. Course, Department of Computer and Systems Sciences, Faculty of Social Sciences, Stockholm University, Sweden. Direct supervisor: Tony Lindgren, Ph.D.

2022

  • Master Thesis Co-supervisor: Design of an Interpretability Measuring Scale (30 ECTS). Supervised students: Tauri Viil. Main supervisor: Jaakko Hollmén, Ph.D.
  • Master Thesis Co-supervisor: Discovering Characteristics and Actionable Features for the Prevention of Cancer (30 ECTS). Supervised students: Sigrid Sandström. Main supervisor: Jaakko Hollmén, Ph.D.
  • Teaching Assistant: Programming for Data Science (HT 2022), M. Sc. Course, Department of Computer and Systems Sciences, Faculty of Social Sciences, Stockholm University, Sweden. Direct supervisor: Jaakko Hollmén, Ph.D.

2021

  • Master Thesis Co-supervisor: Specifying and Weighting Criteria to Choose a Long-Term Romantic Partner (30 ECTS). Supervised students: Maria de las Mercedes Contreras Arteaga, Katrina Marie Novakovic. Main supervisor: Sindri Magnússon, Ph.D.
  • Master Thesis Co-supervisor: Machine Learning post-hoc, model-agnostic interpretable algorithm comparison (30 ECTS). Supervised student: Nina Brudermanns. Main supervisor: Jaakko Hollmén, Ph.D.
  • Teaching Assistant: Programming for Data Science (HT 2021), M. Sc. Course, Department of Computer and Systems Sciences, Faculty of Social Sciences, Stockholm University, Sweden. Direct supervisor: Jaakko Hollmén, Ph.D.

2020

  • Teaching Assistant: Programming for Data Science (HT 2020), M. Sc. Course, Department of Computer and Systems Sciences, Faculty of Social Sciences, Stockholm University, Sweden. Direct supervisor: Jaakko Hollmén, Ph.D.

2018

  • Teaching Assistant: Robust Mechatronics, M.Sc. Course, Department of Machine Design, School of Industrial Engineering and Management, KTH – Royal Institute of Technology, Sweden. Direct supervisor: Mikael Hellgren, Ph.D.