Teaching
Courses, labs, and student supervision
Courses
I have taught various courses in data science, machine learning, and computer science at multiple institutions.
Data Science
180 students
6 ECTS
Course (MSc)
Machine Learning and Data Mining
340 students
6 ECTS
Course (MSc)
Fundamentals of Medical Image Processing
15 students
5 ECTS
Course (BSc)
Introduction to Computer Science
700 students
2 ECTS
Course (BSc)
Web Information Retrieval
120 students
6 ECTS
Course (MSc)
Big Data
220 students
6 ECTS
Course (MSc)
Data Mining
20 students
5 ECTS
Course (MSc)
Pattern Recognition
10 students
5 ECTS
Course (MSc)
Research Labs & Seminars
Supervised research labs where students work on practical machine learning and data science projects.
Sensory Data
SD+KO
15 students
12 ECTS
Research lab (MSc and BSc)
Deep Learning
DL+KO
15 students
12 ECTS
Research lab (MSc and BSc)
Machine Learning Application
MLA+KO
15 students
12 ECTS
Research lab (MSc and BSc)
Supervised Theses
I have supervised numerous bachelor, master, and doctoral theses in various areas of computer science and AI.
PhD Theses
Enabling FAIR Data Exchange and Management in Data Spaces: Frameworks, Challenges, and Solutions
Enhancing Medical Data Management Through FAIR Digital Objects
Adaptive Weighting Strategies in Multi-Agent Reinforcement Learning for Large Language Models
Master Theses
Calibrated Multi-Objective Activation Steering for Structured Generation
Incremental Disclosure-Risk Constraints for Synthetic Record Generation
Online Inference of User Preference Weights in Multi-Objective LLM Alignment
Semantic-Constrained Decoding for Knowledge Graph Generation
Preference-Aware Coefficient Correction for Rewarded-Soups-Style Model Merging
Representing Evolving Knowledge Graphs through Incremental Embeddings
A Framework for Complex Natural Language to SPARQL Translation Using Large Language Models and Policy-Based Reinforcement Learning
LLM-based Tool for FAIR Data Assessment
Exploring In-Context Learning Abilities in Compressed Large Language Models
Aligning Large Language Models at Inference-Time with Preference Vectors using Hypernetworks
Cryptocurrency Price Prediction using Ensemble Learning
Deep Learning for Differential Diagnosis and Prediction in EHR Data with Knowledge Graph Embedding
Sensory Data Mining for Human Activity Recognition using Latent Dirichlet Allocation (LDA)
Generalized Log Parsing Using Memory-Augmented Neural Networks
Interpretable AI: from Machine Learning Models to Human Understandable Rules
AI-based Smart contracts classification: Comparative study
Probabilistic Approach for Author Name Disambiguation
Bachelor Theses
A Pipeline for Spike Detection in Microneurography with Wavelet Denoising and Machine Learning
Early Detection of Abnormal Behaviour in Crowded Scenes
Eye Blinking Detection using SVM