Zuhal Can
  • Slayt

Research Interest

Artificial Intelligence, Wireless Networks
 

Education 

Post-Doctoral Researcher (2015 - 2016) University at Buffalo, SUNY - Computer Science and Engineering 

PhD. (2009 - 2015) University at Buffalo, SUNY - Computer Science and Engineering

MS. (2008 - 2009) University of Connecticut - Computer Science and Engineering

BS. (2002 - 2006) Atilim University - Computer Engineering


Publications

  • Z. Can and B. Soyhan, “Spectro-Temporal-CNN Fusion for Deepfake Speech Detection and Spoof System Attribution,” IEEE Access, vol. 13, pp. 185802–185817, 2025.
  • K. Öztürk and Z. Can, “Predicting Air Quality in Izmir Using Artificial Intelligence and IoT,” J. Comput. Des., vol. 6, no. 2, pp. 341–364, 2025, doi: 10.53710/jcode.1536480.
  • Z. Can and E. Aydin, “Explainable CNN-Radiomics Fusion and Ensemble Learning for Multimodal Lesion Classification in Dental Radiographs,” Diagnostics, vol. 15, no. 16, p. 1997, 2025, doi: 10.3390/diagnostics15161997.
  • E. Aydin and Z. Can, “Explainable Multi-Modal CNN-Radiomics Ensemble for Dental Lesion Detection,” in 2nd International Symposium on Engineering, Design and Innovative Research (SEDIR) 2025, Sinop, Türkiye, May 2025.
  • B. Soyhan, Z. Can, and E. Atilgan, “Detecting Synthetic Voices with Deep Feature Fusion and Ensemble Learning,” in 2nd International Symposium on Engineering, Design and Innovative Research (SEDIR) 2025, Sinop, Türkiye, May 2025.
  • B. Önk and Z. Can, “Integrating IoT and Deep Learning for Traffic Analysis and Prediction with Weather Variables,” Eskisehir Türk Dünyası Uygul. ve Arastırma Merk. Bilişim Derg., vol. 6, no. 1, pp. 10–19, 2025, doi: 10.53608/estudambilisim.1574504.
  • B. Soyhan and Z. Can, “Enhancing Predictive Maintenance in Industrial IoT: A Machine Learning Approach for Real-time Anomaly Detection in Pressure Switches,” Eskisehir Türk Dünyası Uygul. ve Arastırma Merk. Bilişim Derg., vol. 6, no. 1, pp. 1–9, 2025, doi: 10.53608/estudambilisim.1574345.
  • L. F. Nobosse and Z. Can, “IoT Sistemleri ve Makine Öğrenmesi Teknikleri Kullanılarak Boğulma ve Yangın Risklerinin Tahmini,” Fırat Üniversitesi Fen Bilim. Derg., vol. 37, no. 1, pp. 19–26, 2025.
  • Z. Can, “ShoppingTotal: A Mobile Application Utilizing Assisted Rekognition Algorithm for Intelligent Price Detection from Shelf Label Images,” Bilgi ve İletisim Teknol. Derg., vol. 6, no. 1, pp. 57–74, 2024, doi: 10.53694/bited.1470771.
  • Z. Can, S. Isik, and Y. Anagun, “CVApool: using null-space of CNN weights for the tooth disease classification,” Neural Comput. Appl., pp. 1–13, 2024, doi: 10.1007/s00521-024-09995-2.
  • Z. Can and E. Atılgan, “A Review of Recent Machine Learning Approaches for Voice Authentication Systems,” Bilgi ve İletişim Teknol. Derg., vol. 5, no. 1, pp. 96–114, 2023, doi: 10.53694/bited.1296035.
  • A. A. Abdulrahman, S. Isik, Z. Can, and Y. Anagun, “Using Deep Learning Techniques for Tooth Decay Detection,” in International Marmara Sciences Congress (IMASCON) 2023, Kocaeli, Türkiye, Dec. 2023.
  • Z. Can and Ş. Işık, “Diagnosing diseases from fingernail images,” Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimar. Fakültesi Derg., vol. 30, no. 3, pp. 464–470, 2022, doi: 10.31796/ogummf.1111749.
  • S. Isik, Z. Can, Y. Anagun, and O. Güder, “Hafif Evrimsel Sinir Ağı İle Tırnak Hastalığı Sınıflandırması,” in 16. Uluslararası Sağlıkta Kalite, Akreditasyon ve Hasta Güvenliği Kongresi, Antalya, Türkiye, May 2022.
  • Z. Can and E. Değirmenci, “Energy Utilization Impacts in Detecting Abnormality on Wireless Sensor Networks,” Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimar. Fakültesi Derg., vol. 30, no. 1, pp. 1–6, 2021, doi: 10.31796/ogummf.869907.
  • Z. Can, K. Çağlar, B. Hesapdar, B. Önk, and B. Rahimi, “Akıllı Ev Sistemlerinde Nesnelerin İnterneti İçin Prototip Tasarımı,” in Fen Bilimleri, Matematik, Mühendislik ve Sağlık Bilimleri Alanında Yeni Trendler, Duvar Yayınları, 2022, ch. 12.
  • Z. Can, “Öğrenciler İçin Konaklama Yeri Arama Sistemi,” in International Aegean Conferences: Innovation Technologies & Engineering-V, Feb. 2022.
  • Z. Can and E. Değirmenci, “Network Load Effects on Wireless Sensor Network Node Activity,” Eskisehir Türk Dünyası Uygul. ve Arastırma Merk. Bilişim Derg., vol. 3, no. 1, pp. 6–10, 2022, doi: 10.53608/estudambilisim.1021409.
  • Z. Can, “Kurum İçi Maske Tespit ve Uyarı Sistemi,” in Uluslararası Bilimsel Gelişmeler Kongresi ICONSAD’21, 2021.
  • Z. Can and E. Değirmenci, “Effects of Network Density in Detecting Node Abnormality in Wireless Sensor Networks,” in Proceedings of the International Conference on Internet of Things, Big Data Analytics and Information Technology (ICITBDIT 2020), Istanbul, Turkey, 2020, pp. 36–40.
  • Z. Can and M. Demirbas, “Querying on federated sensor networks,” J. Sens. Actuator Networks, vol. 5, no. 3, p. 14, 2016, doi: 10.3390/jsan5030014.
  • Z. Can and M. Demirbas, “Smartphone-based data collection from wireless sensor networks in an urban environment,” J. Netw. Comput. Appl., vol. 58, pp. 208–216, 2015, doi: 10.1016/j.jnca.2015.08.013.
  • Z. Can and M. Demirbas, “Energy-efficient smartphone-based data collection from wireless sensor networks,” in 2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), 2015, pp. 643–647.
  • Z. Can and M. Demirbas, “A survey on in-network querying and tracking services for wireless sensor networks,” Ad Hoc Networks, vol. 11, no. 1, pp. 596–610, 2013, doi: 10.1016/j.adhoc.2012.08.007.
  • M. Demirbas and Z. T. Can, “Investigation of querying techniques for federated sensor networks,” in 2011 7th International Wireless Communications and Mobile Computing Conference, 2011, pp. 2034–2039.