PUIU Andrei

Asistent universitar
Departamentul Automatică și Tehnologia Informației
Facultatea de Inginerie Electrică și Știința Calculatoarelor

Contact:

Mihai Viteazu 5, Brașov, Romania
Corp V, sala VI1b
Tel. : +40 745595447
E-mail: andrei.puiu@unitbv.ro

Descarcă CV

Interese de cercetare:

  • Data Science
  • Programare paralelă
  • Deep Learning

Publicații:

  • Puiu, A., Gómez Tapia, C., Weiss, M. E. R., Singh, V., Kamen, A., & Siebert, M. (2024). Prediction uncertainty estimates elucidate the limitation of current NSCLC subtype classification in representing mutational heterogeneity. Scientific Reports, 14(1), 6779. https://doi.org/10.1038/s41598-024-57057-3.  (SRI: 1.836)
  • Puiu, A., Reaungamornrat, S., Pheiffer, T., Itu, L. M., Suciu, C., Ghesu, F. C., & Mansi, T. (2022). Generative Adversarial CT Volume Extrapolation for Robust Small-to-Large Field of View Registration. Applied Sciences, 12(6), 2944. https://doi.org/10.3390/app12062944. 
  • Puiu, A., Vizitiu, A., Nita, C., Itu, L., Sharma, P., & Comaniciu, D. (2021). Privacy-Preserving and Explainable AI for Cardiovascular Imaging. Studies in Informatics and Control, 30(2), 21–32. https://doi.org/10.24846/v30i2y202102
  • Singh, V., Chaganti, S., Siebert, M., Rajesh, S., Puiu, A., Gopalan, R., Gramz, J., Comaniciu, D., & Kamen, A. (2025). Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers. Scientific Reports, 15(1), 12661. https://doi.org/10.1038/s41598-025-97331-6
  • Benedek, T., Ferent, I., Benedek, A., Cernica, D., Nita, C., Puiu, A., Itu, L., Rapaka, S., Puneet, S., & Benedek, I. S. (2020). P1434 Evolution of coronary wall shear stress following implantation of bioabsorbable vascular scaffolds—First results of a 1-year follow-up pilot study. European Heart Journal - Cardiovascular Imaging, 21(Supplement_1), jez319.863. https://doi.org/10.1093/ehjci/jez319.863. 
  • Ciusdel, C., Turcea, A., Puiu, A., Itu, L., Calmac, L., Weiss, E., Margineanu, C., Badila, E., Passerini, T., Gulsun, M., & Sharma, P. (2018). TCT-231 An artificial intelligence based solution for fully automated cardiac phase and end-diastolic frame detection on coronary angiographies. Journal of the American College of Cardiology, 72(13), B96–B97. https://doi.org/10.1016/j.jacc.2018.08.1356. 
  • Ciusdel, C., Turcea, A., Puiu, A., Itu, L., Calmac, L., Weiss, E., Margineanu, C., Badila, E., Berger, M., Redel, T., Passerini, T., Gulsun, M., & Sharma, P. (2020). Deep neural networks for ECG-free cardiac phase and end-diastolic frame detection on coronary angiographies. Computerized Medical Imaging and Graphics, 84, 101749. https://doi.org/10.1016/j.compmedimag.2020.101749. (SRI: 1,888)
  • Scafa-Udriște, A., Itu, L., Puiu, A., Stoian, A., Moldovan, H., & Popa-Fotea, N.-M. (2023). In-stent restenosis in acute coronary syndrome—a classic and a machine learning approach. Frontiers in Cardiovascular Medicine, 10. https://doi.org/10.3389/fcvm.2023.1270986.