rel="stylesheet">
Creating and sharing knowledge in communications and information technology
... Petia Georgieva

Researcher

Petia Georgieva

Academic position: Associate Professor
Joining date: 01-04-2019
Roles in IT: Researcher
Thematic Line: Basic Sciences and Enabling Technologies
Group: Applied Mathematics - Av
IT – Aveiro
Instituto de Telecomunicações
Campus Universitário de Santiago
P-3810-193 AVEIRO - PORTUGAL
Tel: +351 234 377 900
Email: Send Email
SCOPUSSCHOLARLinkedIn
ORCID iD
CienciaID
Collaboration Network

Scientific Achievements

  • Agregação, Universidade de Aveiro, 16-12-2022
  • PhD, Faculdade de Engenharia da Universidade do Porto, 15-04-2003
  • European Commission, 17-06-2010, External Evaluator
  • Universidade de Aveiro, 01-09-2003, Assoc. Professor with habilitation
  • Machine Learning, Deep Learning, Data mining, Artificial Intelligence, Medical imaging, 5G networks
7Supervision of MSc theses
As Supervisor
As Co-supervisor
1Books
2Books Chapters
  • D.C. Canedo, P.F. Fonseca, P. Georgieva, A. J. R. N Neves, An Innovative Vision System for Floor-Cleaning Robots Based on YOLOv5, Chapter in, Iberian Conference on Pattern Recognition and Image Analysis, Pinho, A.J., Georgieva, P., Teixeira, L.F., Sánchez, J.A, Springer Nature Switzerland AG, Aveiro, 2022
  • P. Georgieva, A. Brandao, Automatic Log Analysis to Prevent Cyber Attacks, Chapter in, Advances in Intelligent Systems Research and Innovation, Springer, Cham, Springer, 2022
23Papers in Journals
22Papers in Conferences
  • P. Georgieva, Explainable AI for Intrusion Detection in Connected Vehicles, Principle and practice of data and Knowledge Acquisition Workshop, Wellington, New Zealand, November, 2025 | BibTex
  • R. Barbosa, M. Araújo, P. Georgieva, S. Sargento, Graph Convolutional Network-Based Approach for Dynamic Connectivity Prediction in 5G Networks, IEEE Conf. on Computer Communications - INFOCOM, Conference online, Vol., pp. -, May, 2025 | BibTex
  • F. Santana, J. Brito, P. Georgieva, Deep Learning for Multi-class Diagnosis of Thyroid Disorders using Selective Features, Artificial Intelligence: Methodology, Systems, and Applications AIMSA, Varna, Bulgaria, September, 2024 | BibTex
  • M. Neves, P. Loureiro, T. Slavov, P. Georgieva, End-to-End Learning System for Symbol Decoding in Optical Communication, IEEE 12th International Conference on Intelligent Systems IS, Varna, Bulgaria, August, 2024 | BibTex
  • J. António, L. Mihaylova, P. Georgieva, Efficient News Synopsis Generation with T5 Transformers, IEEE 12th International Conference on Intelligent Systems IS, Varna, Bulgaria, August, 2024 | BibTex
  • J. António, P. Georgieva, Iterative Stacking Regression for Materials Properties Prediction, IEEE International Joint Conference on Neural Networks IJCNN, Yokohama, Japan, July, 2024 | BibTex
  • R. Barbosa, P. Georgieva, S. Sargento, P. Rito, M. Araújo, A. Goes, Forecasting and Improving Latency in 5G V2X Networks for Autonomous Driving Scenario, IEEE Mediterranean Electrotechnical Conference - MELECON, Porto, Portugal, June, 2024 | Full text (PDF 503 KBs) | BibTex
  • B. Mesquita, B. Duarte, F. Silva, P. Georgieva, Predictive Analytics for Customer Behavior - Top Up Propensity and Account Balance Predictions in Prepaid Mobile Services, IEEE Mediterranean Electrotechnical Conference - MELECON, Porto, Portugal, June, 2024 | BibTex
  • D. Correia, F. Pinto, S. Sargento, P. Georgieva, Cluster-Based Approach for Cellular Traffic Prediction with Machine Learning Methods, IEEE Mediterranean Electrotechnical Conference - MELECON, Porto, Portugal, June, 2024 | BibTex
  • A. Gomes, R. Pascoal, D.C. Canedo, A. Neves, P. Georgieva, Archaeological site detection on remote-sensed images using U-net, International Conference Automatics, Robotics and Artificial Intelligence, Sozopol, Bulgaria, June, 2024 | BibTex
  • F. D. L. C. Coutinho, H. Silva, P. Georgieva, A. Oliveira, On the Performance Analysis of DL-based Data Detection Algorithms in M-QAM Satellite Links, 28th IEEE Workshop on Signal and Power Integrity, Lisboa, Portugal, Vol., pp. -, May, 2024 | BibTex
  • F. D. L. C. Coutinho, H. Silva, P. Georgieva, A. Oliveira, CNN Architecture Design Impact in DL-Based Channel Estimation Algorithms, IEEE Workshop on Communication Networks and Power Systems IEEE WCNPS, Brasília, Brazil, November, 2023,
    | Abstract     | Full text (PDF 1 MB) | BibTex
  • B. Costa, P. Georgieva, Explainable Artificial Intelligence in Healthcare Applications: A Systematic Review, International Scientific Conference on Computer Science COMSCI, Sozopol, Bulgaria, September, 2023 | BibTex
  • R. Lourenço, E. Cueto, P. Georgieva, A. Andrade-Campos, On the constraints and consistency in implicit constitutive modelling using ANNs and indirect training, 26 International Conference on Material Forming ESAFORM, Krakow, Poland, April, 2023 | BibTex
  • F. D. L. C. Coutinho, H. Silva, P. Georgieva, A. Oliveira, Quantization Effects in a CNN-based Channel Estimator, IEEE Radio and Wireless Symp. - RWS, Las Vegas, United States, January, 2023,
    | Abstract     | Full text (PDF 335 KBs) | BibTex
  • F. D. L. C. Coutinho, H. Silva, P. Georgieva, A. Oliveira, CNN-based Algorithm for Joint Channel and Phase Noise Estimation in OFDM Relay Systems, IEEE Latin-American Conference on Communications, Rio de Janeiro, Brazil, December, 2022,
    | Abstract     | Full text (PDF 499 KBs) | BibTex
  • F. D. L. C. Coutinho, H. Silva, P. Georgieva, A. Oliveira, A Flexible CNN Architecture for Real-Time FPGA Implementation, III International Conference on Machine Learning & Applied Network Technologies, Conference online, Vol., pp. -, December, 2022 | BibTex
  • P.S André, P. Georgieva, J. F. Pina, P. E. D. Cruz, R. Pousa, Machine Learning Approach for Online Monitoring of Quality of Transmission Performance Indicators in Optical Fiber Networks, European Conference on Optical Communication ECOC, Bordeux, France, Vol., pp. -, September, 2021 | BibTex
  • D.Gomes Gomes, R. Jesus, M. Antunes, P. Georgieva, R. Aguiar, Stream Generation: Markov Chains vs GANs, International Conference on Internet of Things, Big Data and Security IoTDBS, Crete, Greece, June, 2019,
    | Abstract     | BibTex
  • J. Sanson, P. M. Tomé, P. Georgieva, Enabling MIMO beaforming through compressed CSI feedback based on principal component analysis, Academia Militar - PORTUGUESE CONFERENCE ON PATTERN RECOGNITION - RECPAD, Lisboa, Portugal, October, 2017 | BibTex
  • D. Duarte, N. D. Oliveira Oliveira, P. Georgieva, R.N. Nogueira, L. Bilro, Wine classification and turbidity measurement by clustering and regression models, Conf. on Telecommunications - ConfTele, Aveiro, Portugal, Vol. 0, pp. 0 - 0, September, 2015,
    | Abstract     | BibTex
  • D. Duarte, S. Prats, J. J. Keizer, P. Georgieva, R.N. Nogueira, L. Bilro, Novel approach for simultaneous sediment classification and concentration determination of water turbidity, International Conference on Optical Fibre Sensors 24th International Conference on Optical Fibre Sensors OFS24, Curitiba, Brazil, Vol. 9634, pp. 96342U-1 - 96342U-4, September, 2015,
    | Abstract     | BibTex
1Patents

Closed Projects4

Acronym Name Funding Agency Start date Ending date
Dior Deep Intelligent Optical and Radio Communication Networks EC 01-12-2021 31-05-2026
FreeCom-B5G Ultra-high-capacity free-space optical communications for beyond 5G IT 01-01-2020 31-12-2022
OptWire Next-Generation Optical Wireless Communications Enabled by Artificial Intelligence FCT 01-12-2021 30-11-2024
REVOLUTION REVOLUTIONIZING RADAR THROUGH COMMUNICATIONS TOWARDS ENVIRONMENT SENSING FCT/PTDC 01-03-2023 28-02-2026
1Awards
  • P. Georgieva, M. V. Drummond, 3D Object Detection for Self-Driving Vehicles Enhanced by Object Velocity, E Proof Received 7 December 2023, accepted 24 December 2023. Date of publication 00 xxxx 0000, date of current version 00 xxxx 0000. Digital Object Identifier 10.1109/ACCESS.2024.3353051 3D Object Detection for Self-Driving Vehicles Enhanced by Object Velocity LEANDRO ALEXANDRINO 1,2,3, HADI Z. OLYAEI3, ANDRÉ ALBUQUERQUE3, PETIA GEORGIEVA 1,2,4, (Senior Member, IEEE), AND MIGUEL V. DRUMMOND 1,2, (Member, IEEE) 1 AQ:2 Instituto de Telecomunicações, 3810-193 Aveiro, Portugal 2 AQ:3 Universidade de Aveiro, 3810-193 Aveiro, Portugal 3 AQ:4 Bosch Car Multimedia, 4705-820 Braga, Portugal 4 AQ:5 Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal AQ:6 Corresponding author: Leandro Alexandrino (l.alexandrino@ua.pt) AQ:7 This work was supported in part by the European Union (EU)-NextGenerationEU through the National Recovery and Resilience Plan, Bulgaria, under Project BG-RRP-2.004-0005; and in part by FCT/MCTES through the National Funds co-funded EU Funds under Project UIDB/50008/2020-UIDP/50008/2020. 1 2 3 4 5 6 7 8 9 ABSTRACT AQ:8 A large number of vision sensors has been proposed for enabling self-driving vehicles to perceive their surroundings. Among them, Light Detection And Ranging (LiDAR) presents the unique advantage of acquiring a high resolution 3D representation of the vehicle surroundings, in the form of point clouds, which enables accurate 3D object detection. The success of the fi rst (and current) generation LiDARs has motivated the development of a second generation of this sensor, now based on coherent detection. Second generation LiDARs thus enable not only estimating radial distance, but also radial velocity for each point of the point cloud. The objective of this work is to investigate which benefi ts can be obtained by considering such an additional information – radial velocity – in 3D object detection. Results show that considering object velocity is particularly helpful in objects represented by a small number of points., 30-11-2023

Activities from this researcher fall under the following United Nations Strategic Development Goals (SDGs):

© 2026, IT - Instituto de Telecomunicações | All Rights Reserved