Roberts Kadiķis has been working at the Institute of Electronics and Computer Science (EDI) since 2011 and has been conducting research in the fields of computer vision and artificial intelligence ever since. He graduated from Riga Technical University, where he obtained a PhD in electronics program in 2018, defending his dissertation “Efficient methods for detection and characterization of moving objects in video.”
Roberts’ research interests include image processing, computer vision, and machine learning, as well as the application of these methods to practical tasks in medicine, robotics, intelligent transportation systems, and the field of autonomous driving. Currently, his research focus is generative artificial intelligence and its use in developing synthetic data suitable for training perception models.
From 2019 to 2025, Roberts led EDI’s Robotics and Machine Perception Laboratory and served as Chair of the EDI Scientific Council (2019-2021, 2024). He has led the institute’s teams in Horizon, ERAF, and LZP projects, as well as in contract research. He currently supervises several doctoral dissertations and is a member of the University of Latvia Promotion Council. Outside his research, Roberts works on developing Ascent Lumina, the company he co-founded, and enjoys making music and exploring other creative expressions of natural and artificial intelligence.
Recent projects
- AI-improved organ on chip cultivation for personalised medicine (AImOOC)
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Augmenting and Evaluating the Physical and Digital Infrastructure for CCAM deployment (AUGMENTED CCAM) #Horizon Europe
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Histological recognition and analysis of veterinary tumors surgical margins by using artificial intelligence and multimodal imaging (HAVeT-AI ) #Horizon Europe
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Holographic microscopy- and artificial intelligence-based digital pathology for the next generation of cytology in veterinary medicine (VetCyto) #Horizon Europe
- Soil biological quality index (QBS) determination using machine learning (QBS) #LZP FLPP
Recent publications
- Ivanovs, Maksims, Kaspars Ozols, Artis Dobrajs, and Roberts Kadikis. 2022. "Improving Semantic Segmentation of Urban Scenes for Self-Driving Cars with Synthetic Images" Sensors 22, no. 6: 2252. https://doi.org/10.3390/s22062252
- Arents, J., Lesser, B., Bizuns, A., Kadikis, R., Buls, E., Greitans, M. (2022). Synthetic Data of Randomly Piled, Similar Objects for Deep Learning-Based Object Detection. In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13232. Springer, Cham. https://doi.org/10.1007/978-3-031-06430-2_59
- Mindaugas Tamošiūnas, Roberts Kadiķis, Mikus Melderis, Romāns Maļiks, Diāna Duplevska, Daira Viškere, Ilze Matīse-van Houtana, Blaž Cugmas. 2023. "Wide-field Raman spectral band imaging of tumor lesions in veterinary medicine" Translational Biophotonics: Diagnostics and Therapeutics III, 12627: pp. 295-302. https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12627/1262737/Wide-field-Raman-spectral-band-imaging-of-tumor-lesions-in/10.1117/12.2686917.short
- Valērija Movčana, Arnis Strods, Karīna Narbute, Fēlikss Rūmnieks, Roberts Rimša, Gatis Mozoļevskis, Maksims Ivanovs, Roberts Kadiķis, Kārlis Gustavs Zviedris, Laura Leja, Anastasija Zujeva, Tamāra Laimiņa, Arturs Abols. "Organ-On-A-Chip (OOC) Image Dataset for Machine Learning and Tissue Model Evaluation" Data , 9(2), pp.28. https://doi.org/10.5281/zenodo.10203721
- Blaz Cugmas, Eva Štruc, Inese Bērziņa, Mindaugas Tamošiūnas, Laura Goldberga, Thierry Olivry, Kārlis Zviedris, Roberts Kadiķis, Maksims Ivanovs, Miran Bürmen, Peter Naglič. "Automated classification of pollens relevant to veterinary medicine" 2024 IEEE 14th International Conference Nanomaterials: Applications & Properties (NAP) https://ieeexplore.ieee.org/document/10739713
- warn Singh Warshaneyan, Maksims Ivanovs, Blaž Cugmas, Inese Bērziņa, Laura Goldberga, Mindaugas Tamosiunas, Roberts Kadiķis. 2025. Automated Pollen Recognition in Optical and Holographic Microscopy Images. 1(1). https://ieeexplore.ieee.org/document/11064260
- Tamošiūnas Mindaugas, Maciulevičius, Martynas, Maļiks Romans, Dupļevska Diāna Viškere Daira, Matīse-van Houtana Ilze, Kadiķis Roberts, Cugmas Blaž, Raišutis Renaldas. 2025. Raman spectral band imaging for the diagnostics and classification of canine and feline cutaneous tumors. Veterinary Quarterly, 45(1): pp.1–17. https://www.tandfonline.com/doi/full/10.1080/01652176.2025.2486771?src=
- Daira Viškere, Mindaugas Tamošiūnas, Romans Maļiks, Diāna Dupļevska, Ilze Matīse-van Houtana, Roberts Kadiķis, Blaž Cugmas. 2025. Virtual Staining From Optical Coherence Tomography to Hematoxylin and Eosin Stained Skin Tumor Samples in Pets.
- Simkuns Arturs, Saltanovs Rodions, Ivanovs Maksims, Kadiķis Roberts. Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics. 2025. Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics. Sensors, 25(5). https://www.scopus.com/inward/record.uri?eid=2-s2.0-86000607914&doi=10.3390%2Fs25051576&partnerID=40&md5=9f00c1e98522d8c10d0dc50798f3628e