I am a researcher at the intersection of computer science, 3D imaging, and artificial intelligence, with a particular focus on forensic applications. In my role as a guest PhD candidate at the University of Twente, I investigate how advanced reconstruction techniques, such as neural rendering, Gaussian splatting, and photometric stereo, can be employed in crime scene analysis under challenging conditions like variable lighting. My expertise spans 3D reconstruction, imaging in adverse conditions, and AI to support forensic investigation workflows.

Within the Technologies for Criminal Investigations (TCI) research group, I lead the CrimeBots research line, which focuses on the integration of robotics, sensing technologies, and artificial intelligence in the context of crime investigation, security, and safety. Our work bridges the gap between research and practical application, developing innovative robotic systems, 3D reconstruction methods, and AI-driven tools to enhance the efficiency, reliability, and ethical use of technology in real investigative environments.

Expertise

  • Computer Science

    • 3d Reconstruction
    • Neural Radiance Field
    • Artificial Intelligence
    • Crime Scene Investigation
    • Learning System
    • Machine Learning
    • Phishing Detection
  • Social Sciences

    • Interactivity

Organisations

Publications

2026

Ethical Considerations in AI-Based Brain Tumour Diagnosis (2026)In Intelligent Systems and Applications: Proceedings of the 2025 Intelligent Systems Conference (IntelliSys) (pp. 60-77) (Lecture Notes in Networks and Systems (LNNS); Vol. 1660). Springer (E-pub ahead of print/First online). Rangelov, D., Miltchev, R. & Genchev, E.https://doi.org/10.1007/978-3-032-07109-5_5Inter-System Concordance and Short-Term Survey Repeatability of Two Ground-Penetrating Radar Acquisition–Interpretation Chains in Forensic Search: An Exploratory Field Study (2026)Forensic Sciences, 6(3). Article 81 (E-pub ahead of print/First online). Nijeholt, L. L. à., Rangelov, D. & Steenbeeke, M.https://doi.org/10.3390/forensicsci6030081From Fiction to Forensics: Mitigating the Digital CSI Effect Through Interactive Workshops on Artificial Intelligence and 3D Crime Scene Reconstruction (2026)Forensic Sciences, 6(3). Article 78 (E-pub ahead of print/First online). Bhandari, S., Rangelov, D., Waanders, K., Waanders, S. & van Keulen, M.https://doi.org/10.3390/forensicsci6030078Enhancing Crime Scene Investigations: From technology to evidence (2026)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Rangelov, D.https://doi.org/10.3990/1.9789036573344AI-Powered API for Brain Tumour Classification: A Deep Learning Approach to Accessible Medical Imaging (2026)In Flexible Query Answering Systems: 16th International Conference, FQAS 2025, Burgas, Bulgaria, September 11–13, 2025, Proceedings (pp. 53–65) (Lecture Notes in Computer Science; Vol. 16119). Springer. Rangelov, D., Miltchev, R. & Genchev, E.https://doi.org/10.1007/978-3-032-05607-8_7Surveillance Camera Image Dataset for Visual Classification in Criminal Investigation Research (CCTV Cameras) (2026)[Dataset Types › Dataset]. Zenodo. Rangelov, D., Rangelov, N., Miltchev, R. & Genchev, E.https://doi.org/10.5281/zenodo.19565334INTELKAMAT - Cervical Colposcopy Image Dataset (2026)[Dataset Types › Dataset]. Zenodo. Rangelov, D., Prandzhev, G. D. & Miltchev, R.https://doi.org/10.5281/zenodo.21442366Mitigating the CSI effect in learning about technological innovations in crime investigation (2026)[Contribution to conference › Abstract] 1st International Online Conference on Social Sciences, IOCSS 2026. Bhandari, S., Rangelov, D., Waanders, K., Waanders, S. & van Keulen, M.https://sciforum.net/paper/31172Evaluating 3D Reconstruction: A Side-by-Side Comparison of NeRF and Gaussian Splatting in Indoor and Outdoor Environments (2026)Engineering, Technology and Applied Science Research, 16(2), 33736-33745. Rangelov, D., Waanders, S., Waanders, K., Genchev, E., van Keulen, M. & Miltchev, R.https://doi.org/10.48084/etasr.16947A Comparative Study of Machine Learning and Neural Network Models for Phishing Detection (2026)In Data Information in Online Environments: 5th International Conference, DIONE 2024, Sanya, China, November 11, 2024, Proceedings (pp. 99–113) (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; Vol. 569). Springer. Rangelov, D., Miltchev, R. & Genchev, E.https://doi.org/10.1007/978-3-031-97352-9_8

Research profiles

I have an academic background in electrical engineering and computer science, with a strong focus on artificial intelligence, robotics, and 3D imaging. My educational path combines technical expertise with applied research in the field of forensic science. This multidisciplinary foundation enables me to approach complex research problems from both a technological and societal perspective.

I am currently pursuing my PhD (guest) at the University of Twente, where my research focuses on applying advanced 3D reconstruction techniques and AI methods to enhance crime scene analysis and digital forensics.

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