I'm Marko Lalovic, a PhD student at the Network Science Institute, Northeastern University London, advised by Prof István Kiss. My general research interests include optimization, graph theory, and algorithms, with a focus on their applications in network science.
Prior to starting my PhD, I worked on developing machine learning solutions for start-ups in medical technology and fraud detection. Previously, I was a student researcher at the Jozef Stefan Institute, where I was applying deep learning to robotics and evaluating machine learning algorithms.
I completed my master's thesis at the Institute for Algorithms and Complexity, TUHH, as part of my MSc in Industrial Mathematics at the University of Hamburg. Prior to that, I studied for an MSc in Applied Statistics and a BSc in Computer Science and Mathematics at the University of Ljubljana.
- The Paradox of Neglecting Changes in Behavior: How Standard Epidemic Models Misestimate Both Transmissibility and Final Epidemic Size, Binod Pant, Marko Lalovic, István Z. Kiss, and Mauricio Santillana. medRxiv:2025.12.07.25341782
- Exact Algorithms for MaxCut on Split Graphs, Marko Lalovic. arXiv:2405.20599
- latent2likert: Converting Latent Variables into Likert Scale Responses, Marko Lalovic. R package version 1.2.2